Aditya Nori

Vice President, Lab Director

Publications

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- Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology
  
  Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob
  
  ACM ToCHI | August 2025, Vol 32(2): pp. 1-61
  
  Publication DOI Project
- Re-Imagine: Symbolic Benchmark Synthesis for Reasoning Evaluation
  
  Xinnuo Xu, Rachel Lawrence, Kshitij Dubey, Atharva Pandey, Fabian Falck, Risa Ueno, Aditya Nori, Rahul Sharma, Amit Sharma, Javier González
  
  ICLR 2025 - Workshop on Reasoning and Planning for LLMs | March 2025
  
  Publication PDF
- Reasoning Elicitation in Language Models via Counterfactual Feedback
  
  Alihan Hüyük, Xinnuo Xu, Jacqueline Maasch, Aditya Nori, Javier González
  
  ICLR 2025 | March 2025
  
  DOI
- Compositional Causal Reasoning Evaluation in Language Models
  
  Jacqueline Maasch, Alihan Hüyük, Xinnuo Xu, Aditya Nori, Javier González
  
  ICML 2025 | March 2025
  
  DOI Publication Publication
- Does Reasoning Emerge? Examining the Probabilities of Causation in Large Language Models
  
  Javier González, Aditya Nori
  
  NeurIPS 2024 | August 2024
  
  Publication DOI
- Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology
  
  Nur Yildirim, Hannah Richardson (nee Murfet), Maria T Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme
  
  CHI 2024 | May 2024
  
  Preprint Publication Project
- Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology
  
  Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel Coelho de Castro, Anton Schwaighofer, Maximilian Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O'Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle
  
  Nature Communications | March 2024, Vol 15
  
  DOI Publication PDF
- RadEdit: Stress-Testing Biomedical Vision Models via Diffusion Image Editing
  
  Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel Coelho de Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson (nee Murfet), Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse
  
  ECCV 2024 | December 2023
  
  Publication DOI Preprint Access Project
- Deep learning for the prediction of clinical outcomes in internet-delivered CBT for depression and anxiety
  
  Niranjani Prasad, Isabel Chien, Tim Regan, Angel Enrique, Jorge Palacios, Dessie Kegan, Usman Munir, Ryutaro Tanno, Hannah Richardson (nee Murfet), Aditya Nori, Derek Richards, Gavin Doherty, Danielle Belgrave, Anja Thieme
  
  PLOS ONE | November 2023, Vol 18(11)
  
  PDF Publication DOI Project
- TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Models
  
  Javier González, Cliff Wong, Zelalem Gero, Jaspreet Bagga, Risa Ueno, Isabel Chien, Eduard Orakvin, Emre Kiciman, Aditya Nori, R. Weerasinghe, R. Leidner, B. Piening, Tristan Naumann, C. Bifulco, Hoifung Poon
  
  ArXiv | November 2023
  
  DOI Publication Publication
- Exploring the Boundaries of GPT-4 in Radiology
  
  Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle
  
  EMNLP 2023 | October 2023
  
  PDF Publication Project
- Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
  
  Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay
  
  The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023
  
  Preprint Access Project
- Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward
  
  Anja Thieme, Aditya Nori, Marzyeh Ghassemi, Rishi Bommasani, Tariq Osman Andersen, Ewa Luger
  
  CHI 2023 | April 2023
  
  Publication Project
- Compositional Zero-Shot Domain Transfer with Text-to-Text Models
  
  Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie Hyland
  
  TACL 2023 | March 2023
  
  Publication Project
- Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing
  
  Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay
  
  The European Conference on Computer Vision (ECCV) | October 2022
  
  Preprint Video Access Access Project
- Repairing Neural Networks by Leaving the Right Past Behind
  
  Ryutaro Tanno, Melanie Fernandez Pradier, Aditya Nori, Yingzhen Li
  
  Neural Information Processing Systems | July 2022
  
  Publication
- Active label cleaning for improved dataset quality under resource constraints
  
  Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
  
  Nature Communications | March 2022, Vol 13(1161): pp. 1-11
  
  Publication Project Project
- Artificial intelligence in healthcare: transforming the practice of medicine
  
  Junaid Bajwa, Aditya Nori, Bryan Williams, Usman Munir
  
  Future Healthcare Journal | July 2021
  
  Publication Video
- Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
  
  Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
  
  ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
  
  PDF Preprint Project Project Project Project
- Secure Medical Image Analysis with CrypTFlow
  
  Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare
  
  NeurIPS PPML Workshop | December 2020
  
  Publication Project Project
- Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers
  
  Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Gill Barnett, David Noble, Yvonne Rimmer, Rajesh Jena, Ben Glocker, Kenton O'Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori
  
  JAMA | November 2020
  
  Publication Video Project
- Towards Compliant Data Management Systems for Healthcare ML
  
  Goutham Ramakrishnan, Aditya Nori, Hannah Richardson (nee Murfet), Pashmina Cameron
  
  November 2020
  
  November 2020
  
  Publication
- Alleviating Privacy Attacks via Causal Learning
  
  Shruti Tople, Amit Sharma, Aditya V. Nori
  
  International Conference on Machine Learning (ICML) | July 2020
  
  Publication Github Project Project
- A Machine Learning Approach to Understanding Patterns of Engagement With Internet-Delivered Mental Health Interventions.
  
  Isabel Chien, Angel Enrique, Jorge Palacios, Tim Regan, Dessie Keegan, David Carter, Sebastian Tschiatschek, Aditya Nori, Anja Thieme, Derek Richards, Gavin Doherty, Danielle Belgrave
  
  JAMA Network | June 2020, Vol 3(7)
  
  DOI Publication Project
- Overfitting in Synthesis: Theory and Practice
  
  Saswat Padhi, Todd Millstein, Aditya Nori, Rahul Sharma
  
  Computer Aided Verification (CAV) | July 2019
  
  Publication
- Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features
  
  M. W. Macomber, M. H. Phillips, Ivan Tarapov, R. Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, M. J. Nyflot
  
  Physics in Medicine and Biology | November 2018, Vol 63(23): pp. 235002-235002
  
  DOI PDF Publication
- Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features
  
  Meghan W Macomber, Mark Phillips, Ivan Tarapov, Rajesh Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, Matthew J Nyflot
  
  Physics in Medicine & Biology | November 2018, Vol 63(23)
  
  Publication Project
- Autofocus Layer for Semantic Segmentation
  
  Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya Nori
  
  International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI) | September 2018
  
  DOI Publication Project
- Semi-Supervised Learning via Compact Latent Space Clustering
  
  Konstantinos Kamnitsas, Daniel C. Castro, Loic Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya Nori
  
  International Conference on Machine Learning (ICML) | June 2018
  
  Publication Publication Project
- FairSquare: Probabilistic Verification for Program Fairness
  
  Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya Nori
  
  OOPSLA '17: OO Programming, Systems, Languages, and Applications | October 2017
  
  Publication
- Unsupervised domain adaptation in brain lesion segmentation with adversarial networks
  
  Konstantinos Kamnitsas, Christian Baumgartner, Christian Ledig, Virginia F.J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
  
  Information Processing in Medical Imaging (IPMI) | June 2017
  
  Publication Project
- Spectral Kernels for Probabilistic Analysis and Clustering of Shapes
  
  Loic Le Folgoc, Aditya Nori, Antonio Criminisi
  
  Information Processing in Medical Imaging (IPMI) | June 2017
  
  DOI PDF Publication Project
- Fairness as a Program Property
  
  Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya Nori
  
  Fairness, Accountability, and Transparency in Machine Learning (FATML) | November 2016
  
  Publication
- DeepMedic for Brain Tumor Segmentation
  
  Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
  
  MICCAI Brain Lesion Workshop | October 2016
  
  DOI PDF Publication Project
- Lifted Auto-Context Forests for Brain Tumour Segmentation
  
  Loic Le Folgoc, Aditya Nori, Siddharth Ancha, Antonio Criminisi
  
  MICCAI Brain Lesion Workshop | October 2016
  
  DOI PDF Publication Project
- Measuring Neural Net Robustness with Constraints
  
  Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya Nori, Antonio Criminisi
  
  Neural Information Processing Systems (NIPS) | May 2016
  
  Publication
- Debugging Machine Learning Tasks
  
  Aleksandar Chakarov, Aditya Nori, Sriram Rajamani, Shayak Sen, Deepak Vijaykeerthy
  
  MSR-TR-2016-1135 | March 2016
  
  PDF
- A Provably Correct Sampler for Probabilistic Programs
  
  Chung-Kil Hur, Aditya Nori, Sriram Rajamani
  
  Foundations of Software Technology and Theoretical Computer Science (FSTTCS) | December 2015
  
  PDF Project
- Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances
  
  Ravi Mangal, Xin Zhang, Mayur Naik, Aditya Nori
  
  SAT '15: International Conference on Theory and Applications of Satisfiability Testing | September 2015
  
  PDF
- A User-Guided Approach to Program Analysis
  
  Ravi Mangal, Xin Zhang, Mayur Naik, Aditya Nori
  
  Foundations of Software Engineering (FSE) | August 2015
  
  Foundations of Software Engineering (FSE) - ACM SIGSOFT Distinguished Paper
  
  ACM SIGSOFT Distinguished Paper
  
  PDF
- Learning Refinement Types
  
  He Zhu, Aditya Nori, Suresh Jagannathan
  
  International Conference on Functional Programming (ICFP) | August 2015
  
  International Conference on Functional Programming (ICFP)
  
  PDF
- Efficient Synthesis of Probabilistic Programs
  
  Aditya Nori, Sherjil Ozair, Sriram Rajamani, Deepak Vijaykeerthy,
  
  Programming Language Design and Implementation (PLDI) | June 2015
  
  PDF PDF Publication Project
- Dependent Array Type Inference from Tests
  
  He Zhu, Aditya Nori, Suresh Jagannathan
  
  VMCAI '15: Verification, Model Checking and Abstract Interpretation | January 2015
  
  PDF
- Structurally Heterogeneous Source Code Examples from Unstructured Knowledge Sources
  
  Venkatesh Vinayakarao, Rahul Purandare, Aditya Nori
  
  Partial Evaluation and Program Manipulation (PEPM) | January 2015
  
  PDF
- R2: An Efficient MCMC Sampler for Probabilistic Programs
  
  Aditya Nori, Chung-Kil Hur, Sriram Rajamani, Selva Samuel
  
  AAAI Conference on Artificial Intelligence (AAAI) | July 2014
  
  PDF Project
- Slicing Probabilistic Programs
  
  Chung-Kil Hur, Aditya Nori, Sriram Rajamani, Selva Samuel
  
  Programming Language Design and Implementation (PLDI) | June 2014
  
  PDF Project
- MUX: Algorithm Selection for Software Model Checkers
  
  Varun Tulsian, Aditya Kanade, Rahul Kumar, Akash Lal, Aditya Nori
  
  Mining Software Repositories (MSR) | May 2014
  
  PDF
- Probabilistic Programming
  
  Andy Gordon, Thomas A. Henzinger, Aditya Nori, Sriram Rajamani
  
  International Conference on Software Engineering (ICSE Future of Software Engineering) | May 2014
  
  Publication Project
- Bias-Variance Tradeoffs in Program Analysis
  
  Alex Aiken, Aditya Nori, Rahul Sharma
  
  Principles of Programming Languages (POPL) | January 2014
  
  PDF
- A Colorful Approach to Text Processing by Example
  
  Kuat Yessenov, Shubham Tulsiani, Aditya Menon, Robert C. Miller, Sumit Gulwani, Butler Lampson, Adam Tauman Kalai
  
  UIST '13 Proceedings of the 26th annual ACM symposium on User interface software and technology | October 2013
  
  PDF DOI Project
- Semantics Sensitive Sampling for Probabilistic Programs
  
  Aditya Nori, Chung-Kil Hur, Sriram Rajamani, Selva Samuel
  
  MSR-TR-2013-109 | October 2013
  
  PDF Project
- Bayesian Inference Using Data Flow Analysis
  
  Guillaume Claret, Sriram Rajamani, Aditya Nori, Andy Gordon, Johannes Borgström
  
  ESEC/FSE 2013 Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering | August 2013
  
  Publication Publication Project
- Termination Proofs from Tests
  
  Aditya Nori, Rahul Sharma
  
  Foundations of Software Engineering (FSE) | August 2013
  
  PDF
- Combining Relational Learning with SMT Solvers using CEGAR
  
  Arun Chaganty, Akash Lal, Aditya Nori, Sriram Rajamani
  
  Computer Aided Verification (CAV) | July 2013
  
  PDF
- One-bit Compressed Sensing: Provable Support and Vector Recovery
  
  Sivakanth Gopi, Praneeth Netrapalli, Prateek Jain, Aditya Nori
  
  International Conference on Machine Learning (ICML) | June 2013
  
  Publication Publication
- Verification as Learning Geometric Concepts
  
  , Saurabh Gupta, Bharath Hariharan, Alex Aiken, Aditya Nori
  
  Static Analysis Symposium (SAS) | June 2013
  
  Static Analysis Symposium (SAS)
  
  PDF
- Efficiently Sampling Probabilistic Programs via Program Analysis
  
  Arun T. Chaganty, Aditya Nori, Sriram Rajamani
  
  Artificial Intelligence and Statistics (AISTATS) | April 2013
  
  PDF Project
- A Data Driven Approach for Algebraic Loop Invariants
  
  , Saurabh Gupta, Bharath Hariharan, Alex Aiken, Percy Liang, Aditya Nori
  
  European Symposium on Programming (ESOP) | March 2013
  
  PDF
- A Model-Learner Pattern for Bayesian Reasoning
  
  Andrew D. Gordon, Mihhail Aizatulin, Guillaume Claret, Thore Graepel, Aditya Nori, Sriram Rajamani, Claudio Russo, Johannes Borgstroem, Andy Gordon
  
  MSR-TR-2013-1 | January 2013
  
  Published by Microsoft
  
  Publication Publication Project Project
- Probabilistic Inference Using Program Analysis
  
  Andy Gordon, Aditya Nori, Sriram Rajamani
  
  January 2013
  
  PDF Project
- Interpolants as Classifiers
  
  Aditya Nori, Alex Aiken
  
  Computer Aided Verification | July 2012
  
  Computer Aided Verification
  
  PDF
- Parallelizing Top-Down Interprocedural Analyses
  
  Aws Albarghouthi, Rahul Kumar, Aditya Nori, Sriram Rajamani
  
  Programming Languages Design and Implementation (PLDI) | June 2012
  
  PDF Project
- Interpolants as Classifiers
  
  Rahul Sharma, Aditya Nori, Alex Aiken,
  
  MSR-TR-2012-13 | January 2012
  
  PDF
- Bottom-up shape analysis using LISF
  
  Bhargav Gulavani, Supratik Chakraborty, G. Ramalingam, Aditya Nori, G. Ramalingam
  
  November 2011
  
  Publication
- Probabilistic, Modular and Scalable Inference of Typestate Specifications
  
  Nels E. Beckman, Aditya Nori
  
  PLDI '11: Programming Languages Design and Implementation | June 2011
  
  PDF
- Alternation for Termination
  
  William R. Harris, Akash Lal, Aditya Nori, Sriram Rajamani
  
  SAS '10: Static Analysis Symposium | September 2010
  
  PDF Project
- An Empirical Study of Optimizations in Yogi
  
  Aditya Nori, Sriram Rajamani
  
  International Conference on Software Engineering (ICSE) | May 2010
  
  PDF Project
- Proofs from Tests
  
  Nels E. Beckman, Aditya Nori, Sriram Rajamani, Robert J. Simmons, Sai Deep Tetali, Aditya V. Thakur
  
  IEEE Transactions on Software Engineering (special issue on the ISSTA 2008 best papers) | March 2010
  
  ISSTA 2008 best papers
  
  PDF Project
- Compositional May-Must Program Analysis: Unleashing the Power of Alternation
  
  Patrice Godefroid, Aditya Nori, Sriram Rajamani, Sai Deep Tetali
  
  Principles of Programming Languages (POPL) | January 2010
  
  PDF Project Project
- Bottom-up Shape Analysis
  
  Bhargav Gulavani, Supratik Chakraborty, G. Ramalingam, Aditya Nori
  
  SAS '09: Static Analysis Symposium | August 2009
  
  PDF
- Measuring the Loss of Privacy from Statistics
  
  Michael C. Tschantz, Aditya Nori
  
  Workshop on Quantitative Analysis of Software | June 2009
  
  PDF
- Merlin: Specification Inference for Explicit Information Flow Problems
  
  Ben Livshits, Aditya Nori, Sriram Rajamani, Anindya Banerjee
  
  ACM SIGPLAN 2009 Conference on Programming Language Design and Implementation (PLDI) | June 2009
  
  PDF
- Holmes: Effective Statistical Debugging via Efficient Path Profiling
  
  Trishul Chilimbi, Ben Liblit, Krishna Mehra, Aditya Nori, Kapil Vaswani
  
  Proceedings of the International Conference on Software Engineering (ICSE) | May 2009
  
  PDF
- The Yogi Project: Software Property Checking via Static Analysis and Testing
  
  Aditya Nori, Sriram Rajamani, Sai Deep Tetali, Aditya V. Thakur,
  
  TACAS '09: Tools and Algorithms for the Construction and Analysis of Systems | March 2009
  
  PDF Project
- Automated Software Testing Using Program Analysis
  
  Patrice Godefroid, Jonathan "Peli" de Halleux, Aditya Nori, Sriram Rajamani, Wolfram Schulte, Nikolai Tillmann, Michael Y. Levin
  
  IEEE Software, Special Issue on Software Development Tools | October 2008
  
  PDF Publication Project Project Project
- Automatically Refining Abstract Interpretations
  
  Bhargav Gulavani, Supratik Chakraborty, Aditya Nori, Sriram Rajamani
  
  Proceedings of the 14th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS) | March 2008
  
  PDF Project
- Quantifying the Effectiveness of Testing via Efficient Residual Path Profiling
  
  Trishul Chilimbi, Aditya Nori, Kapil Vaswani
  
  Proceedings of the Symposium on Foundations of Software Engineering (FSE) | September 2007
  
  PDF
- Preferential Path Profiling: Compactly Numbering Interesting Paths
  
  Kapil Vaswani, Aditya Nori, Trishul Chilimbi
  
  Proceedings of the Symposium on Principles of Programming Languages (POPL) | January 2007
  
  PDF
- Unifying Views of Tail-Biting Constructions for Linear Block Codes
  
  Aditya Nori, Priti Shankar
  
  IEEE Transactions on Information Theory | October 2006
  
  PDF
- SYNERGY : A New Algorithm for Property Checking
  
  Bhargav Gulavani, Thomas Henzinger, Yamini Kannan, Aditya Nori, Sriram Rajamani
  
  MSR-TR-2006-76 | April 2006
  
  PDF
- Exact And Approximate Algorithms for ML Decoding on Tail-Biting Trellises
  
  Priti Shankar, Madhu A. S, Aditya Nori
  
  March 2005
  
  PDF
- Unifying Views of Tail-Biting Trellises for Linear Block Codes
  
  Aditya Nori
  
  January 2005
  
  January 2005
  
  PDF
- A Coset Construction for Tail-Biting Trellises
  
  Aditya Nori, Priti Shankar
  
  Proceedings of the International Symposium on Information Theory and its Applications (ISITA) | October 2004
  
  Proceedings of the International Symposium on Information Theory and its Applications (ISITA)
  
  PDF
- Decoding Codes on Graphs: Probabilistic Decoding
  
  Madhu A. S, Aditya Nori
  
  Resonance: Journal of Science Education, Indian Academy of Sciences | February 2004
  
  Resonance: Journal of Science Education, Indian Academy of Sciences
  
  PDF
- Tail-Biting Trellises for Linear Codes and their Duals
  
  Aditya Nori, Priti Shankar
  
  Proceedings of the Forty-First Annual Allerton Conference on Communication, Control and Computing (Allerton) | October 2003
  
  PDF
- Decoding Codes on Graphs: Low Density Parity Check Codes
  
  Aditya Nori
  
  Resonance: Journal of Science Education, Indian Academy of Sciences | September 2003
  
  PDF
- A BCJR-like Labeling Algorithm for Tail-Biting Trellises
  
  Aditya Nori, Priti Shankar
  
  Proceedings of the IEEE International Symposium on Information Theory (ISIT) | July 2003
  
  PDF
- A Technique for Model-Based Testing of Classes
  
  Aditya Nori, Ashok Sreenivas
  
  Proceedings of the Second International Workshop on Software Engineering Tools and Techniques | January 2001
  
  PDF

- Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology
  
  Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob
  
  ACM ToCHI | August 2025, Vol 32(2): pp. 1-61
  
  Publication DOI Project
- Re-Imagine: Symbolic Benchmark Synthesis for Reasoning Evaluation
  
  Xinnuo Xu, Rachel Lawrence, Kshitij Dubey, Atharva Pandey, Fabian Falck, Risa Ueno, Aditya Nori, Rahul Sharma, Amit Sharma, Javier González
  
  ICLR 2025 - Workshop on Reasoning and Planning for LLMs | March 2025
  
  Publication PDF
- Reasoning Elicitation in Language Models via Counterfactual Feedback
  
  Alihan Hüyük, Xinnuo Xu, Jacqueline Maasch, Aditya Nori, Javier González
  
  ICLR 2025 | March 2025
  
  DOI
- Compositional Causal Reasoning Evaluation in Language Models
  
  Jacqueline Maasch, Alihan Hüyük, Xinnuo Xu, Aditya Nori, Javier González
  
  ICML 2025 | March 2025
  
  DOI Publication Publication
- Does Reasoning Emerge? Examining the Probabilities of Causation in Large Language Models
  
  Javier González, Aditya Nori
  
  NeurIPS 2024 | August 2024
  
  Publication DOI
- Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology
  
  Nur Yildirim, Hannah Richardson (nee Murfet), Maria T Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme
  
  CHI 2024 | May 2024
  
  Preprint Publication Project
- Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology
  
  Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel Coelho de Castro, Anton Schwaighofer, Maximilian Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O'Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle
  
  Nature Communications | March 2024, Vol 15
  
  DOI Publication PDF
- RadEdit: Stress-Testing Biomedical Vision Models via Diffusion Image Editing
  
  Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel Coelho de Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson (nee Murfet), Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse
  
  ECCV 2024 | December 2023
  
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- Deep learning for the prediction of clinical outcomes in internet-delivered CBT for depression and anxiety
  
  Niranjani Prasad, Isabel Chien, Tim Regan, Angel Enrique, Jorge Palacios, Dessie Kegan, Usman Munir, Ryutaro Tanno, Hannah Richardson (nee Murfet), Aditya Nori, Derek Richards, Gavin Doherty, Danielle Belgrave, Anja Thieme
  
  PLOS ONE | November 2023, Vol 18(11)
  
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- TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Models
  
  Javier González, Cliff Wong, Zelalem Gero, Jaspreet Bagga, Risa Ueno, Isabel Chien, Eduard Orakvin, Emre Kiciman, Aditya Nori, R. Weerasinghe, R. Leidner, B. Piening, Tristan Naumann, C. Bifulco, Hoifung Poon
  
  ArXiv | November 2023
  
  DOI Publication Publication
- Exploring the Boundaries of GPT-4 in Radiology
  
  Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle
  
  EMNLP 2023 | October 2023
  
  PDF Publication Project
- Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
  
  Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay
  
  The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023
  
  Preprint Access Project
- Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward
  
  Anja Thieme, Aditya Nori, Marzyeh Ghassemi, Rishi Bommasani, Tariq Osman Andersen, Ewa Luger
  
  CHI 2023 | April 2023
  
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- Compositional Zero-Shot Domain Transfer with Text-to-Text Models
  
  Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie Hyland
  
  TACL 2023 | March 2023
  
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- Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing
  
  Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay
  
  The European Conference on Computer Vision (ECCV) | October 2022
  
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- Repairing Neural Networks by Leaving the Right Past Behind
  
  Ryutaro Tanno, Melanie Fernandez Pradier, Aditya Nori, Yingzhen Li
  
  Neural Information Processing Systems | July 2022
  
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- Active label cleaning for improved dataset quality under resource constraints
  
  Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
  
  Nature Communications | March 2022, Vol 13(1161): pp. 1-11
  
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- Artificial intelligence in healthcare: transforming the practice of medicine
  
  Junaid Bajwa, Aditya Nori, Bryan Williams, Usman Munir
  
  Future Healthcare Journal | July 2021
  
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- Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
  
  Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
  
  ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
  
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- Secure Medical Image Analysis with CrypTFlow
  
  Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare
  
  NeurIPS PPML Workshop | December 2020
  
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- Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers
  
  Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Gill Barnett, David Noble, Yvonne Rimmer, Rajesh Jena, Ben Glocker, Kenton O'Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori
  
  JAMA | November 2020
  
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- Towards Compliant Data Management Systems for Healthcare ML
  
  Goutham Ramakrishnan, Aditya Nori, Hannah Richardson (nee Murfet), Pashmina Cameron
  
  November 2020
  
  November 2020
  
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- Alleviating Privacy Attacks via Causal Learning
  
  Shruti Tople, Amit Sharma, Aditya V. Nori
  
  International Conference on Machine Learning (ICML) | July 2020
  
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- A Machine Learning Approach to Understanding Patterns of Engagement With Internet-Delivered Mental Health Interventions.
  
  Isabel Chien, Angel Enrique, Jorge Palacios, Tim Regan, Dessie Keegan, David Carter, Sebastian Tschiatschek, Aditya Nori, Anja Thieme, Derek Richards, Gavin Doherty, Danielle Belgrave
  
  JAMA Network | June 2020, Vol 3(7)
  
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- Overfitting in Synthesis: Theory and Practice
  
  Saswat Padhi, Todd Millstein, Aditya Nori, Rahul Sharma
  
  Computer Aided Verification (CAV) | July 2019
  
  Publication
- Autofocus Layer for Semantic Segmentation
  
  Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya Nori
  
  International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI) | September 2018
  
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- Semi-Supervised Learning via Compact Latent Space Clustering
  
  Konstantinos Kamnitsas, Daniel C. Castro, Loic Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya Nori
  
  International Conference on Machine Learning (ICML) | June 2018
  
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- Unsupervised domain adaptation in brain lesion segmentation with adversarial networks
  
  Konstantinos Kamnitsas, Christian Baumgartner, Christian Ledig, Virginia F.J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
  
  Information Processing in Medical Imaging (IPMI) | June 2017
  
  Publication Project
- Spectral Kernels for Probabilistic Analysis and Clustering of Shapes
  
  Loic Le Folgoc, Aditya Nori, Antonio Criminisi
  
  Information Processing in Medical Imaging (IPMI) | June 2017
  
  DOI PDF Publication Project
- Fairness as a Program Property
  
  Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya Nori
  
  Fairness, Accountability, and Transparency in Machine Learning (FATML) | November 2016
  
  Publication
- Lifted Auto-Context Forests for Brain Tumour Segmentation
  
  Loic Le Folgoc, Aditya Nori, Siddharth Ancha, Antonio Criminisi
  
  MICCAI Brain Lesion Workshop | October 2016
  
  DOI PDF Publication Project
- DeepMedic for Brain Tumor Segmentation
  
  Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
  
  MICCAI Brain Lesion Workshop | October 2016
  
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- Measuring Neural Net Robustness with Constraints
  
  Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya Nori, Antonio Criminisi
  
  Neural Information Processing Systems (NIPS) | May 2016
  
  Publication
- Debugging Machine Learning Tasks
  
  Aleksandar Chakarov, Aditya Nori, Sriram Rajamani, Shayak Sen, Deepak Vijaykeerthy
  
  MSR-TR-2016-1135 | March 2016
  
  PDF
- A Provably Correct Sampler for Probabilistic Programs
  
  Chung-Kil Hur, Aditya Nori, Sriram Rajamani
  
  Foundations of Software Technology and Theoretical Computer Science (FSTTCS) | December 2015
  
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- Efficient Synthesis of Probabilistic Programs
  
  Aditya Nori, Sherjil Ozair, Sriram Rajamani, Deepak Vijaykeerthy,
  
  Programming Language Design and Implementation (PLDI) | June 2015
  
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- R2: An Efficient MCMC Sampler for Probabilistic Programs
  
  Aditya Nori, Chung-Kil Hur, Sriram Rajamani, Selva Samuel
  
  AAAI Conference on Artificial Intelligence (AAAI) | July 2014
  
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- Slicing Probabilistic Programs
  
  Chung-Kil Hur, Aditya Nori, Sriram Rajamani, Selva Samuel
  
  Programming Language Design and Implementation (PLDI) | June 2014
  
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- MUX: Algorithm Selection for Software Model Checkers
  
  Varun Tulsian, Aditya Kanade, Rahul Kumar, Akash Lal, Aditya Nori
  
  Mining Software Repositories (MSR) | May 2014
  
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- Probabilistic Programming
  
  Andy Gordon, Thomas A. Henzinger, Aditya Nori, Sriram Rajamani
  
  International Conference on Software Engineering (ICSE Future of Software Engineering) | May 2014
  
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- Semantics Sensitive Sampling for Probabilistic Programs
  
  Aditya Nori, Chung-Kil Hur, Sriram Rajamani, Selva Samuel
  
  MSR-TR-2013-109 | October 2013
  
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- Termination Proofs from Tests
  
  Aditya Nori, Rahul Sharma
  
  Foundations of Software Engineering (FSE) | August 2013
  
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- Bayesian Inference Using Data Flow Analysis
  
  Guillaume Claret, Sriram Rajamani, Aditya Nori, Andy Gordon, Johannes Borgström
  
  ESEC/FSE 2013 Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering | August 2013
  
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- One-bit Compressed Sensing: Provable Support and Vector Recovery
  
  Sivakanth Gopi, Praneeth Netrapalli, Prateek Jain, Aditya Nori
  
  International Conference on Machine Learning (ICML) | June 2013
  
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- Efficiently Sampling Probabilistic Programs via Program Analysis
  
  Arun T. Chaganty, Aditya Nori, Sriram Rajamani
  
  Artificial Intelligence and Statistics (AISTATS) | April 2013
  
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- Probabilistic Inference Using Program Analysis
  
  Andy Gordon, Aditya Nori, Sriram Rajamani
  
  January 2013
  
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- A Model-Learner Pattern for Bayesian Reasoning
  
  Andrew D. Gordon, Mihhail Aizatulin, Guillaume Claret, Thore Graepel, Aditya Nori, Sriram Rajamani, Claudio Russo, Johannes Borgstroem, Andy Gordon
  
  MSR-TR-2013-1 | January 2013
  
  Published by Microsoft
  
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- Interpolants as Classifiers
  
  Aditya Nori, Alex Aiken
  
  Computer Aided Verification | July 2012
  
  Computer Aided Verification
  
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- Interpolants as Classifiers
  
  Rahul Sharma, Aditya Nori, Alex Aiken,
  
  MSR-TR-2012-13 | January 2012
  
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- Probabilistic, Modular and Scalable Inference of Typestate Specifications
  
  Nels E. Beckman, Aditya Nori
  
  PLDI '11: Programming Languages Design and Implementation | June 2011
  
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- Measuring the Loss of Privacy from Statistics
  
  Michael C. Tschantz, Aditya Nori
  
  Workshop on Quantitative Analysis of Software | June 2009
  
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- Merlin: Specification Inference for Explicit Information Flow Problems
  
  Ben Livshits, Aditya Nori, Sriram Rajamani, Anindya Banerjee
  
  ACM SIGPLAN 2009 Conference on Programming Language Design and Implementation (PLDI) | June 2009
  
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- Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology
  
  Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob
  
  ACM ToCHI | August 2025, Vol 32(2): pp. 1-61
  
  Publication DOI Project
- Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology
  
  Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel Coelho de Castro, Anton Schwaighofer, Maximilian Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O'Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle
  
  Nature Communications | March 2024, Vol 15
  
  DOI Publication PDF
- RadEdit: Stress-Testing Biomedical Vision Models via Diffusion Image Editing
  
  Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel Coelho de Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson (nee Murfet), Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse
  
  ECCV 2024 | December 2023
  
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- TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Models
  
  Javier González, Cliff Wong, Zelalem Gero, Jaspreet Bagga, Risa Ueno, Isabel Chien, Eduard Orakvin, Emre Kiciman, Aditya Nori, R. Weerasinghe, R. Leidner, B. Piening, Tristan Naumann, C. Bifulco, Hoifung Poon
  
  ArXiv | November 2023
  
  DOI Publication Publication
- Exploring the Boundaries of GPT-4 in Radiology
  
  Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle
  
  EMNLP 2023 | October 2023
  
  PDF Publication Project
- Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
  
  Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay
  
  The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023
  
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- Compositional Zero-Shot Domain Transfer with Text-to-Text Models
  
  Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie Hyland
  
  TACL 2023 | March 2023
  
  Publication Project
- Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing
  
  Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay
  
  The European Conference on Computer Vision (ECCV) | October 2022
  
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- Active label cleaning for improved dataset quality under resource constraints
  
  Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
  
  Nature Communications | March 2022, Vol 13(1161): pp. 1-11
  
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- Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
  
  Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
  
  ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
  
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- Secure Medical Image Analysis with CrypTFlow
  
  Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare
  
  NeurIPS PPML Workshop | December 2020
  
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- Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers
  
  Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Gill Barnett, David Noble, Yvonne Rimmer, Rajesh Jena, Ben Glocker, Kenton O'Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori
  
  JAMA | November 2020
  
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- Towards Compliant Data Management Systems for Healthcare ML
  
  Goutham Ramakrishnan, Aditya Nori, Hannah Richardson (nee Murfet), Pashmina Cameron
  
  November 2020
  
  November 2020
  
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- A Machine Learning Approach to Understanding Patterns of Engagement With Internet-Delivered Mental Health Interventions.
  
  Isabel Chien, Angel Enrique, Jorge Palacios, Tim Regan, Dessie Keegan, David Carter, Sebastian Tschiatschek, Aditya Nori, Anja Thieme, Derek Richards, Gavin Doherty, Danielle Belgrave
  
  JAMA Network | June 2020, Vol 3(7)
  
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- Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features
  
  M. W. Macomber, M. H. Phillips, Ivan Tarapov, R. Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, M. J. Nyflot
  
  Physics in Medicine and Biology | November 2018, Vol 63(23): pp. 235002-235002
  
  DOI PDF Publication
- Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features
  
  Meghan W Macomber, Mark Phillips, Ivan Tarapov, Rajesh Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, Matthew J Nyflot
  
  Physics in Medicine & Biology | November 2018, Vol 63(23)
  
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- Unsupervised domain adaptation in brain lesion segmentation with adversarial networks
  
  Konstantinos Kamnitsas, Christian Baumgartner, Christian Ledig, Virginia F.J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
  
  Information Processing in Medical Imaging (IPMI) | June 2017
  
  Publication Project
- Spectral Kernels for Probabilistic Analysis and Clustering of Shapes
  
  Loic Le Folgoc, Aditya Nori, Antonio Criminisi
  
  Information Processing in Medical Imaging (IPMI) | June 2017
  
  DOI PDF Publication Project
- Lifted Auto-Context Forests for Brain Tumour Segmentation
  
  Loic Le Folgoc, Aditya Nori, Siddharth Ancha, Antonio Criminisi
  
  MICCAI Brain Lesion Workshop | October 2016
  
  DOI PDF Publication Project
- DeepMedic for Brain Tumor Segmentation
  
  Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
  
  MICCAI Brain Lesion Workshop | October 2016
  
  DOI PDF Publication Project
- RadEdit: Stress-Testing Biomedical Vision Models via Diffusion Image Editing
  
  Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel Coelho de Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson (nee Murfet), Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse
  
  ECCV 2024 | December 2023
  
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- Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
  
  Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay
  
  The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023
  
  Preprint Access Project
- Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing
  
  Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay
  
  The European Conference on Computer Vision (ECCV) | October 2022
  
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- Active label cleaning for improved dataset quality under resource constraints
  
  Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
  
  Nature Communications | March 2022, Vol 13(1161): pp. 1-11
  
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- Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
  
  Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
  
  ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
  
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- Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features
  
  M. W. Macomber, M. H. Phillips, Ivan Tarapov, R. Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, M. J. Nyflot
  
  Physics in Medicine and Biology | November 2018, Vol 63(23): pp. 235002-235002
  
  DOI PDF Publication
- Measuring Neural Net Robustness with Constraints
  
  Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya Nori, Antonio Criminisi
  
  Neural Information Processing Systems (NIPS) | May 2016
  
  Publication
- Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology
  
  Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob
  
  ACM ToCHI | August 2025, Vol 32(2): pp. 1-61
  
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- Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology
  
  Nur Yildirim, Hannah Richardson (nee Murfet), Maria T Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme
  
  CHI 2024 | May 2024
  
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- Deep learning for the prediction of clinical outcomes in internet-delivered CBT for depression and anxiety
  
  Niranjani Prasad, Isabel Chien, Tim Regan, Angel Enrique, Jorge Palacios, Dessie Kegan, Usman Munir, Ryutaro Tanno, Hannah Richardson (nee Murfet), Aditya Nori, Derek Richards, Gavin Doherty, Danielle Belgrave, Anja Thieme
  
  PLOS ONE | November 2023, Vol 18(11)
  
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- Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward
  
  Anja Thieme, Aditya Nori, Marzyeh Ghassemi, Rishi Bommasani, Tariq Osman Andersen, Ewa Luger
  
  CHI 2023 | April 2023
  
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- A Machine Learning Approach to Understanding Patterns of Engagement With Internet-Delivered Mental Health Interventions.
  
  Isabel Chien, Angel Enrique, Jorge Palacios, Tim Regan, Dessie Keegan, David Carter, Sebastian Tschiatschek, Aditya Nori, Anja Thieme, Derek Richards, Gavin Doherty, Danielle Belgrave
  
  JAMA Network | June 2020, Vol 3(7)
  
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- A Technique for Model-Based Testing of Classes
  
  Aditya Nori, Ashok Sreenivas
  
  Proceedings of the Second International Workshop on Software Engineering Tools and Techniques | January 2001
  
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  Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare
  
  NeurIPS PPML Workshop | December 2020
  
  Publication Project Project
- Overfitting in Synthesis: Theory and Practice
  
  Saswat Padhi, Todd Millstein, Aditya Nori, Rahul Sharma
  
  Computer Aided Verification (CAV) | July 2019
  
  Publication
- FairSquare: Probabilistic Verification for Program Fairness
  
  Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya Nori
  
  OOPSLA '17: OO Programming, Systems, Languages, and Applications | October 2017
  
  Publication
- Fairness as a Program Property
  
  Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya Nori
  
  Fairness, Accountability, and Transparency in Machine Learning (FATML) | November 2016
  
  Publication
- Debugging Machine Learning Tasks
  
  Aleksandar Chakarov, Aditya Nori, Sriram Rajamani, Shayak Sen, Deepak Vijaykeerthy
  
  MSR-TR-2016-1135 | March 2016
  
  PDF
- A Provably Correct Sampler for Probabilistic Programs
  
  Chung-Kil Hur, Aditya Nori, Sriram Rajamani
  
  Foundations of Software Technology and Theoretical Computer Science (FSTTCS) | December 2015
  
  PDF Project
- Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances
  
  Ravi Mangal, Xin Zhang, Mayur Naik, Aditya Nori
  
  SAT '15: International Conference on Theory and Applications of Satisfiability Testing | September 2015
  
  PDF
- A User-Guided Approach to Program Analysis
  
  Ravi Mangal, Xin Zhang, Mayur Naik, Aditya Nori
  
  Foundations of Software Engineering (FSE) | August 2015
  
  Foundations of Software Engineering (FSE) - ACM SIGSOFT Distinguished Paper
  
  ACM SIGSOFT Distinguished Paper
  
  PDF
- Learning Refinement Types
  
  He Zhu, Aditya Nori, Suresh Jagannathan
  
  International Conference on Functional Programming (ICFP) | August 2015
  
  International Conference on Functional Programming (ICFP)
  
  PDF
- Efficient Synthesis of Probabilistic Programs
  
  Aditya Nori, Sherjil Ozair, Sriram Rajamani, Deepak Vijaykeerthy,
  
  Programming Language Design and Implementation (PLDI) | June 2015
  
  PDF PDF Publication Project
- Structurally Heterogeneous Source Code Examples from Unstructured Knowledge Sources
  
  Venkatesh Vinayakarao, Rahul Purandare, Aditya Nori
  
  Partial Evaluation and Program Manipulation (PEPM) | January 2015
  
  PDF
- Dependent Array Type Inference from Tests
  
  He Zhu, Aditya Nori, Suresh Jagannathan
  
  VMCAI '15: Verification, Model Checking and Abstract Interpretation | January 2015
  
  PDF
- R2: An Efficient MCMC Sampler for Probabilistic Programs
  
  Aditya Nori, Chung-Kil Hur, Sriram Rajamani, Selva Samuel
  
  AAAI Conference on Artificial Intelligence (AAAI) | July 2014
  
  PDF Project
- Slicing Probabilistic Programs
  
  Chung-Kil Hur, Aditya Nori, Sriram Rajamani, Selva Samuel
  
  Programming Language Design and Implementation (PLDI) | June 2014
  
  PDF Project
- MUX: Algorithm Selection for Software Model Checkers
  
  Varun Tulsian, Aditya Kanade, Rahul Kumar, Akash Lal, Aditya Nori
  
  Mining Software Repositories (MSR) | May 2014
  
  PDF
- Probabilistic Programming
  
  Andy Gordon, Thomas A. Henzinger, Aditya Nori, Sriram Rajamani
  
  International Conference on Software Engineering (ICSE Future of Software Engineering) | May 2014
  
  Publication Project
- Bias-Variance Tradeoffs in Program Analysis
  
  Alex Aiken, Aditya Nori, Rahul Sharma
  
  Principles of Programming Languages (POPL) | January 2014
  
  PDF
- A Colorful Approach to Text Processing by Example
  
  Kuat Yessenov, Shubham Tulsiani, Aditya Menon, Robert C. Miller, Sumit Gulwani, Butler Lampson, Adam Tauman Kalai
  
  UIST '13 Proceedings of the 26th annual ACM symposium on User interface software and technology | October 2013
  
  PDF DOI Project
- Semantics Sensitive Sampling for Probabilistic Programs
  
  Aditya Nori, Chung-Kil Hur, Sriram Rajamani, Selva Samuel
  
  MSR-TR-2013-109 | October 2013
  
  PDF Project
- Termination Proofs from Tests
  
  Aditya Nori, Rahul Sharma
  
  Foundations of Software Engineering (FSE) | August 2013
  
  PDF
- Bayesian Inference Using Data Flow Analysis
  
  Guillaume Claret, Sriram Rajamani, Aditya Nori, Andy Gordon, Johannes Borgström
  
  ESEC/FSE 2013 Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering | August 2013
  
  Publication Publication Project
- Combining Relational Learning with SMT Solvers using CEGAR
  
  Arun Chaganty, Akash Lal, Aditya Nori, Sriram Rajamani
  
  Computer Aided Verification (CAV) | July 2013
  
  PDF
- Verification as Learning Geometric Concepts
  
  , Saurabh Gupta, Bharath Hariharan, Alex Aiken, Aditya Nori
  
  Static Analysis Symposium (SAS) | June 2013
  
  Static Analysis Symposium (SAS)
  
  PDF
- Efficiently Sampling Probabilistic Programs via Program Analysis
  
  Arun T. Chaganty, Aditya Nori, Sriram Rajamani
  
  Artificial Intelligence and Statistics (AISTATS) | April 2013
  
  PDF Project
- A Data Driven Approach for Algebraic Loop Invariants
  
  , Saurabh Gupta, Bharath Hariharan, Alex Aiken, Percy Liang, Aditya Nori
  
  European Symposium on Programming (ESOP) | March 2013
  
  PDF
- Probabilistic Inference Using Program Analysis
  
  Andy Gordon, Aditya Nori, Sriram Rajamani
  
  January 2013
  
  PDF Project
- A Model-Learner Pattern for Bayesian Reasoning
  
  Andrew D. Gordon, Mihhail Aizatulin, Guillaume Claret, Thore Graepel, Aditya Nori, Sriram Rajamani, Claudio Russo, Johannes Borgstroem, Andy Gordon
  
  MSR-TR-2013-1 | January 2013
  
  Published by Microsoft
  
  Publication Publication Project Project
- Interpolants as Classifiers
  
  Aditya Nori, Alex Aiken
  
  Computer Aided Verification | July 2012
  
  Computer Aided Verification
  
  PDF
- Parallelizing Top-Down Interprocedural Analyses
  
  Aws Albarghouthi, Rahul Kumar, Aditya Nori, Sriram Rajamani
  
  Programming Languages Design and Implementation (PLDI) | June 2012
  
  PDF Project
- Interpolants as Classifiers
  
  Rahul Sharma, Aditya Nori, Alex Aiken,
  
  MSR-TR-2012-13 | January 2012
  
  PDF
- Bottom-up shape analysis using LISF
  
  Bhargav Gulavani, Supratik Chakraborty, G. Ramalingam, Aditya Nori, G. Ramalingam
  
  November 2011
  
  Publication
- Probabilistic, Modular and Scalable Inference of Typestate Specifications
  
  Nels E. Beckman, Aditya Nori
  
  PLDI '11: Programming Languages Design and Implementation | June 2011
  
  PDF
- Alternation for Termination
  
  William R. Harris, Akash Lal, Aditya Nori, Sriram Rajamani
  
  SAS '10: Static Analysis Symposium | September 2010
  
  PDF Project
- An Empirical Study of Optimizations in Yogi
  
  Aditya Nori, Sriram Rajamani
  
  International Conference on Software Engineering (ICSE) | May 2010
  
  PDF Project
- Proofs from Tests
  
  Nels E. Beckman, Aditya Nori, Sriram Rajamani, Robert J. Simmons, Sai Deep Tetali, Aditya V. Thakur
  
  IEEE Transactions on Software Engineering (special issue on the ISSTA 2008 best papers) | March 2010
  
  ISSTA 2008 best papers
  
  PDF Project
- Compositional May-Must Program Analysis: Unleashing the Power of Alternation
  
  Patrice Godefroid, Aditya Nori, Sriram Rajamani, Sai Deep Tetali
  
  Principles of Programming Languages (POPL) | January 2010
  
  PDF Project Project
- Bottom-up Shape Analysis
  
  Bhargav Gulavani, Supratik Chakraborty, G. Ramalingam, Aditya Nori
  
  SAS '09: Static Analysis Symposium | August 2009
  
  PDF
- Measuring the Loss of Privacy from Statistics
  
  Michael C. Tschantz, Aditya Nori
  
  Workshop on Quantitative Analysis of Software | June 2009
  
  PDF
- Merlin: Specification Inference for Explicit Information Flow Problems
  
  Ben Livshits, Aditya Nori, Sriram Rajamani, Anindya Banerjee
  
  ACM SIGPLAN 2009 Conference on Programming Language Design and Implementation (PLDI) | June 2009
  
  PDF
- Holmes: Effective Statistical Debugging via Efficient Path Profiling
  
  Trishul Chilimbi, Ben Liblit, Krishna Mehra, Aditya Nori, Kapil Vaswani
  
  Proceedings of the International Conference on Software Engineering (ICSE) | May 2009
  
  PDF
- The Yogi Project: Software Property Checking via Static Analysis and Testing
  
  Aditya Nori, Sriram Rajamani, Sai Deep Tetali, Aditya V. Thakur,
  
  TACAS '09: Tools and Algorithms for the Construction and Analysis of Systems | March 2009
  
  PDF Project
- Automated Software Testing Using Program Analysis
  
  Patrice Godefroid, Jonathan "Peli" de Halleux, Aditya Nori, Sriram Rajamani, Wolfram Schulte, Nikolai Tillmann, Michael Y. Levin
  
  IEEE Software, Special Issue on Software Development Tools | October 2008
  
  PDF Publication Project Project Project
- Automatically Refining Abstract Interpretations
  
  Bhargav Gulavani, Supratik Chakraborty, Aditya Nori, Sriram Rajamani
  
  Proceedings of the 14th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS) | March 2008
  
  PDF Project
- Quantifying the Effectiveness of Testing via Efficient Residual Path Profiling
  
  Trishul Chilimbi, Aditya Nori, Kapil Vaswani
  
  Proceedings of the Symposium on Foundations of Software Engineering (FSE) | September 2007
  
  PDF
- A Coset Construction for Tail-Biting Trellises
  
  Aditya Nori, Priti Shankar
  
  Proceedings of the International Symposium on Information Theory and its Applications (ISITA) | October 2004
  
  Proceedings of the International Symposium on Information Theory and its Applications (ISITA)
  
  PDF
- Secure Medical Image Analysis with CrypTFlow
  
  Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare
  
  NeurIPS PPML Workshop | December 2020
  
  Publication Project Project
- Alleviating Privacy Attacks via Causal Learning
  
  Shruti Tople, Amit Sharma, Aditya V. Nori
  
  International Conference on Machine Learning (ICML) | July 2020
  
  Publication Github Project Project
- Measuring the Loss of Privacy from Statistics
  
  Michael C. Tschantz, Aditya Nori
  
  Workshop on Quantitative Analysis of Software | June 2009
  
  PDF
- Merlin: Specification Inference for Explicit Information Flow Problems
  
  Ben Livshits, Aditya Nori, Sriram Rajamani, Anindya Banerjee
  
  ACM SIGPLAN 2009 Conference on Programming Language Design and Implementation (PLDI) | June 2009
  
  PDF
- One-bit Compressed Sensing: Provable Support and Vector Recovery
  
  Sivakanth Gopi, Praneeth Netrapalli, Prateek Jain, Aditya Nori
  
  International Conference on Machine Learning (ICML) | June 2013
  
  Publication Publication
- Compositional May-Must Program Analysis: Unleashing the Power of Alternation
  
  Patrice Godefroid, Aditya Nori, Sriram Rajamani, Sai Deep Tetali
  
  Principles of Programming Languages (POPL) | January 2010
  
  PDF Project Project
- Bottom-up Shape Analysis
  
  Bhargav Gulavani, Supratik Chakraborty, G. Ramalingam, Aditya Nori
  
  SAS '09: Static Analysis Symposium | August 2009
  
  PDF
- Merlin: Specification Inference for Explicit Information Flow Problems
  
  Ben Livshits, Aditya Nori, Sriram Rajamani, Anindya Banerjee
  
  ACM SIGPLAN 2009 Conference on Programming Language Design and Implementation (PLDI) | June 2009
  
  PDF
- SYNERGY : A New Algorithm for Property Checking
  
  Bhargav Gulavani, Thomas Henzinger, Yamini Kannan, Aditya Nori, Sriram Rajamani
  
  MSR-TR-2006-76 | April 2006
  
  PDF
- Exact And Approximate Algorithms for ML Decoding on Tail-Biting Trellises
  
  Priti Shankar, Madhu A. S, Aditya Nori
  
  March 2005
  
  PDF
- Decoding Codes on Graphs: Probabilistic Decoding
  
  Madhu A. S, Aditya Nori
  
  Resonance: Journal of Science Education, Indian Academy of Sciences | February 2004
  
  Resonance: Journal of Science Education, Indian Academy of Sciences
  
  PDF
- Tail-Biting Trellises for Linear Codes and their Duals
  
  Aditya Nori, Priti Shankar
  
  Proceedings of the Forty-First Annual Allerton Conference on Communication, Control and Computing (Allerton) | October 2003
  
  PDF
- A BCJR-like Labeling Algorithm for Tail-Biting Trellises
  
  Aditya Nori, Priti Shankar
  
  Proceedings of the IEEE International Symposium on Information Theory (ISIT) | July 2003
  
  PDF
- Preferential Path Profiling: Compactly Numbering Interesting Paths
  
  Kapil Vaswani, Aditya Nori, Trishul Chilimbi
  
  Proceedings of the Symposium on Principles of Programming Languages (POPL) | January 2007
  
  PDF
- Unifying Views of Tail-Biting Constructions for Linear Block Codes
  
  Aditya Nori, Priti Shankar
  
  IEEE Transactions on Information Theory | October 2006
  
  PDF
- Unifying Views of Tail-Biting Trellises for Linear Block Codes
  
  Aditya Nori
  
  January 2005
  
  January 2005
  
  PDF
- Decoding Codes on Graphs: Low Density Parity Check Codes
  
  Aditya Nori
  
  Resonance: Journal of Science Education, Indian Academy of Sciences | September 2003
  
  PDF

- A Technique for Model-Based Testing of Classes
  
  Aditya Nori, Ashok Sreenivas
  
  Proceedings of the Second International Workshop on Software Engineering Tools and Techniques | January 2001
  
  PDF
- Re-Imagine: Symbolic Benchmark Synthesis for Reasoning Evaluation
  
  Xinnuo Xu, Rachel Lawrence, Kshitij Dubey, Atharva Pandey, Fabian Falck, Risa Ueno, Aditya Nori, Rahul Sharma, Amit Sharma, Javier González
  
  ICLR 2025 - Workshop on Reasoning and Planning for LLMs | March 2025
  
  Publication PDF
- Reasoning Elicitation in Language Models via Counterfactual Feedback
  
  Alihan Hüyük, Xinnuo Xu, Jacqueline Maasch, Aditya Nori, Javier González
  
  ICLR 2025 | March 2025
  
  DOI
- Compositional Causal Reasoning Evaluation in Language Models
  
  Jacqueline Maasch, Alihan Hüyük, Xinnuo Xu, Aditya Nori, Javier González
  
  ICML 2025 | March 2025
  
  DOI Publication Publication
- Does Reasoning Emerge? Examining the Probabilities of Causation in Large Language Models
  
  Javier González, Aditya Nori
  
  NeurIPS 2024 | August 2024
  
  Publication DOI
- Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology
  
  Nur Yildirim, Hannah Richardson (nee Murfet), Maria T Wetscherek, Junaid Bajwa, Joseph Jacob, Mark A Pinnock, Stephen Harris, Daniel Coelho de Castro, Shruthi Bannur, Stephanie Hyland, Pratik Ghosh, Mercy Ranjit, Kenza Bouzid, Anton Schwaighofer, Fernando Pérez-García, Harshita Sharma, Ozan Oktay, Matthew P Lungren, Javier Alvarez-Valle, Aditya Nori, Anja Thieme
  
  CHI 2024 | May 2024
  
  Preprint Publication Project
- RadEdit: Stress-Testing Biomedical Vision Models via Diffusion Image Editing
  
  Fernando Pérez-García, Sam Bond-Taylor, Pedro P. Sanchez, Boris van Breugel, Daniel Coelho de Castro, Harshita Sharma, Valentina Salvatelli, Maria T. A. Wetscherek, Hannah Richardson (nee Murfet), Matthew P Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay, Maximilian Ilse
  
  ECCV 2024 | December 2023
  
  Publication DOI Preprint Access Project
- Exploring the Boundaries of GPT-4 in Radiology
  
  Qianchu Liu, Stephanie Hyland, Shruthi Bannur, Kenza Bouzid, Daniel Coelho de Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García, Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle
  
  EMNLP 2023 | October 2023
  
  PDF Publication Project
- Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
  
  Shruthi Bannur, Stephanie Hyland, Flora Liu, Fernando Pérez-García, Maximilian Ilse, Daniel Coelho de Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Teodora Wetscherek, Matthew Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay
  
  The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) | June 2023
  
  Preprint Access Project
- Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward
  
  Anja Thieme, Aditya Nori, Marzyeh Ghassemi, Rishi Bommasani, Tariq Osman Andersen, Ewa Luger
  
  CHI 2023 | April 2023
  
  Publication Project
- Compositional Zero-Shot Domain Transfer with Text-to-Text Models
  
  Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie Hyland
  
  TACL 2023 | March 2023
  
  Publication Project
- Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing
  
  Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay
  
  The European Conference on Computer Vision (ECCV) | October 2022
  
  Preprint Video Access Access Project
- Repairing Neural Networks by Leaving the Right Past Behind
  
  Ryutaro Tanno, Melanie Fernandez Pradier, Aditya Nori, Yingzhen Li
  
  Neural Information Processing Systems | July 2022
  
  Publication
- Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
  
  Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
  
  ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
  
  PDF Preprint Project Project Project Project
- Secure Medical Image Analysis with CrypTFlow
  
  Javier Alvarez-Valle, Pratik Bhatu, Nishanth Chandran, Divya Gupta, Aditya Nori, Aseem Rastogi, Mayank Rathee, Rahul Sharma, Shubham Ugare
  
  NeurIPS PPML Workshop | December 2020
  
  Publication Project Project
- Alleviating Privacy Attacks via Causal Learning
  
  Shruti Tople, Amit Sharma, Aditya V. Nori
  
  International Conference on Machine Learning (ICML) | July 2020
  
  Publication Github Project Project
- Overfitting in Synthesis: Theory and Practice
  
  Saswat Padhi, Todd Millstein, Aditya Nori, Rahul Sharma
  
  Computer Aided Verification (CAV) | July 2019
  
  Publication
- Autofocus Layer for Semantic Segmentation
  
  Yao Qin, Konstantinos Kamnitsas, Siddharth Ancha, Jay Nanavati, Garrison W. Cottrell, Antonio Criminisi, Aditya Nori
  
  International Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI) | September 2018
  
  DOI Publication Project
- Semi-Supervised Learning via Compact Latent Space Clustering
  
  Konstantinos Kamnitsas, Daniel C. Castro, Loic Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya Nori
  
  International Conference on Machine Learning (ICML) | June 2018
  
  Publication Publication Project
- FairSquare: Probabilistic Verification for Program Fairness
  
  Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya Nori
  
  OOPSLA '17: OO Programming, Systems, Languages, and Applications | October 2017
  
  Publication
- Unsupervised domain adaptation in brain lesion segmentation with adversarial networks
  
  Konstantinos Kamnitsas, Christian Baumgartner, Christian Ledig, Virginia F.J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
  
  Information Processing in Medical Imaging (IPMI) | June 2017
  
  Publication Project
- Spectral Kernels for Probabilistic Analysis and Clustering of Shapes
  
  Loic Le Folgoc, Aditya Nori, Antonio Criminisi
  
  Information Processing in Medical Imaging (IPMI) | June 2017
  
  DOI PDF Publication Project
- Fairness as a Program Property
  
  Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya Nori
  
  Fairness, Accountability, and Transparency in Machine Learning (FATML) | November 2016
  
  Publication
- Lifted Auto-Context Forests for Brain Tumour Segmentation
  
  Loic Le Folgoc, Aditya Nori, Siddharth Ancha, Antonio Criminisi
  
  MICCAI Brain Lesion Workshop | October 2016
  
  DOI PDF Publication Project
- DeepMedic for Brain Tumor Segmentation
  
  Konstantinos Kamnitsas, Enzo Ferrante, Sarah Parisot, Christian Ledig, Aditya Nori, Antonio Criminisi, Daniel Rueckert, Ben Glocker
  
  MICCAI Brain Lesion Workshop | October 2016
  
  DOI PDF Publication Project
- Measuring Neural Net Robustness with Constraints
  
  Osbert Bastani, Yani Ioannou, Leonidas Lampropoulos, Dimitrios Vytiniotis, Aditya Nori, Antonio Criminisi
  
  Neural Information Processing Systems (NIPS) | May 2016
  
  Publication
- A Provably Correct Sampler for Probabilistic Programs
  
  Chung-Kil Hur, Aditya Nori, Sriram Rajamani
  
  Foundations of Software Technology and Theoretical Computer Science (FSTTCS) | December 2015
  
  PDF Project
- Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances
  
  Ravi Mangal, Xin Zhang, Mayur Naik, Aditya Nori
  
  SAT '15: International Conference on Theory and Applications of Satisfiability Testing | September 2015
  
  PDF
- A User-Guided Approach to Program Analysis
  
  Ravi Mangal, Xin Zhang, Mayur Naik, Aditya Nori
  
  Foundations of Software Engineering (FSE) | August 2015
  
  Foundations of Software Engineering (FSE) - ACM SIGSOFT Distinguished Paper
  
  ACM SIGSOFT Distinguished Paper
  
  PDF
- Learning Refinement Types
  
  He Zhu, Aditya Nori, Suresh Jagannathan
  
  International Conference on Functional Programming (ICFP) | August 2015
  
  International Conference on Functional Programming (ICFP)
  
  PDF
- Efficient Synthesis of Probabilistic Programs
  
  Aditya Nori, Sherjil Ozair, Sriram Rajamani, Deepak Vijaykeerthy,
  
  Programming Language Design and Implementation (PLDI) | June 2015
  
  PDF PDF Publication Project
- Structurally Heterogeneous Source Code Examples from Unstructured Knowledge Sources
  
  Venkatesh Vinayakarao, Rahul Purandare, Aditya Nori
  
  Partial Evaluation and Program Manipulation (PEPM) | January 2015
  
  PDF
- Dependent Array Type Inference from Tests
  
  He Zhu, Aditya Nori, Suresh Jagannathan
  
  VMCAI '15: Verification, Model Checking and Abstract Interpretation | January 2015
  
  PDF
- R2: An Efficient MCMC Sampler for Probabilistic Programs
  
  Aditya Nori, Chung-Kil Hur, Sriram Rajamani, Selva Samuel
  
  AAAI Conference on Artificial Intelligence (AAAI) | July 2014
  
  PDF Project
- Slicing Probabilistic Programs
  
  Chung-Kil Hur, Aditya Nori, Sriram Rajamani, Selva Samuel
  
  Programming Language Design and Implementation (PLDI) | June 2014
  
  PDF Project
- MUX: Algorithm Selection for Software Model Checkers
  
  Varun Tulsian, Aditya Kanade, Rahul Kumar, Akash Lal, Aditya Nori
  
  Mining Software Repositories (MSR) | May 2014
  
  PDF
- Probabilistic Programming
  
  Andy Gordon, Thomas A. Henzinger, Aditya Nori, Sriram Rajamani
  
  International Conference on Software Engineering (ICSE Future of Software Engineering) | May 2014
  
  Publication Project
- Bias-Variance Tradeoffs in Program Analysis
  
  Alex Aiken, Aditya Nori, Rahul Sharma
  
  Principles of Programming Languages (POPL) | January 2014
  
  PDF
- A Colorful Approach to Text Processing by Example
  
  Kuat Yessenov, Shubham Tulsiani, Aditya Menon, Robert C. Miller, Sumit Gulwani, Butler Lampson, Adam Tauman Kalai
  
  UIST '13 Proceedings of the 26th annual ACM symposium on User interface software and technology | October 2013
  
  PDF DOI Project
- Termination Proofs from Tests
  
  Aditya Nori, Rahul Sharma
  
  Foundations of Software Engineering (FSE) | August 2013
  
  PDF
- Bayesian Inference Using Data Flow Analysis
  
  Guillaume Claret, Sriram Rajamani, Aditya Nori, Andy Gordon, Johannes Borgström
  
  ESEC/FSE 2013 Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering | August 2013
  
  Publication Publication Project
- Combining Relational Learning with SMT Solvers using CEGAR
  
  Arun Chaganty, Akash Lal, Aditya Nori, Sriram Rajamani
  
  Computer Aided Verification (CAV) | July 2013
  
  PDF
- Verification as Learning Geometric Concepts
  
  , Saurabh Gupta, Bharath Hariharan, Alex Aiken, Aditya Nori
  
  Static Analysis Symposium (SAS) | June 2013
  
  Static Analysis Symposium (SAS)
  
  PDF
- One-bit Compressed Sensing: Provable Support and Vector Recovery
  
  Sivakanth Gopi, Praneeth Netrapalli, Prateek Jain, Aditya Nori
  
  International Conference on Machine Learning (ICML) | June 2013
  
  Publication Publication
- Efficiently Sampling Probabilistic Programs via Program Analysis
  
  Arun T. Chaganty, Aditya Nori, Sriram Rajamani
  
  Artificial Intelligence and Statistics (AISTATS) | April 2013
  
  PDF Project
- A Data Driven Approach for Algebraic Loop Invariants
  
  , Saurabh Gupta, Bharath Hariharan, Alex Aiken, Percy Liang, Aditya Nori
  
  European Symposium on Programming (ESOP) | March 2013
  
  PDF
- Probabilistic Inference Using Program Analysis
  
  Andy Gordon, Aditya Nori, Sriram Rajamani
  
  January 2013
  
  PDF Project
- Interpolants as Classifiers
  
  Aditya Nori, Alex Aiken
  
  Computer Aided Verification | July 2012
  
  Computer Aided Verification
  
  PDF
- Parallelizing Top-Down Interprocedural Analyses
  
  Aws Albarghouthi, Rahul Kumar, Aditya Nori, Sriram Rajamani
  
  Programming Languages Design and Implementation (PLDI) | June 2012
  
  PDF Project
- Bottom-up shape analysis using LISF
  
  Bhargav Gulavani, Supratik Chakraborty, G. Ramalingam, Aditya Nori, G. Ramalingam
  
  November 2011
  
  Publication
- Probabilistic, Modular and Scalable Inference of Typestate Specifications
  
  Nels E. Beckman, Aditya Nori
  
  PLDI '11: Programming Languages Design and Implementation | June 2011
  
  PDF
- Alternation for Termination
  
  William R. Harris, Akash Lal, Aditya Nori, Sriram Rajamani
  
  SAS '10: Static Analysis Symposium | September 2010
  
  PDF Project
- An Empirical Study of Optimizations in Yogi
  
  Aditya Nori, Sriram Rajamani
  
  International Conference on Software Engineering (ICSE) | May 2010
  
  PDF Project
- Proofs from Tests
  
  Nels E. Beckman, Aditya Nori, Sriram Rajamani, Robert J. Simmons, Sai Deep Tetali, Aditya V. Thakur
  
  IEEE Transactions on Software Engineering (special issue on the ISSTA 2008 best papers) | March 2010
  
  ISSTA 2008 best papers
  
  PDF Project
- Compositional May-Must Program Analysis: Unleashing the Power of Alternation
  
  Patrice Godefroid, Aditya Nori, Sriram Rajamani, Sai Deep Tetali
  
  Principles of Programming Languages (POPL) | January 2010
  
  PDF Project Project
- Bottom-up Shape Analysis
  
  Bhargav Gulavani, Supratik Chakraborty, G. Ramalingam, Aditya Nori
  
  SAS '09: Static Analysis Symposium | August 2009
  
  PDF
- Measuring the Loss of Privacy from Statistics
  
  Michael C. Tschantz, Aditya Nori
  
  Workshop on Quantitative Analysis of Software | June 2009
  
  PDF
- Merlin: Specification Inference for Explicit Information Flow Problems
  
  Ben Livshits, Aditya Nori, Sriram Rajamani, Anindya Banerjee
  
  ACM SIGPLAN 2009 Conference on Programming Language Design and Implementation (PLDI) | June 2009
  
  PDF
- Holmes: Effective Statistical Debugging via Efficient Path Profiling
  
  Trishul Chilimbi, Ben Liblit, Krishna Mehra, Aditya Nori, Kapil Vaswani
  
  Proceedings of the International Conference on Software Engineering (ICSE) | May 2009
  
  PDF
- The Yogi Project: Software Property Checking via Static Analysis and Testing
  
  Aditya Nori, Sriram Rajamani, Sai Deep Tetali, Aditya V. Thakur,
  
  TACAS '09: Tools and Algorithms for the Construction and Analysis of Systems | March 2009
  
  PDF Project
- Automatically Refining Abstract Interpretations
  
  Bhargav Gulavani, Supratik Chakraborty, Aditya Nori, Sriram Rajamani
  
  Proceedings of the 14th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS) | March 2008
  
  PDF Project
- Quantifying the Effectiveness of Testing via Efficient Residual Path Profiling
  
  Trishul Chilimbi, Aditya Nori, Kapil Vaswani
  
  Proceedings of the Symposium on Foundations of Software Engineering (FSE) | September 2007
  
  PDF
- Preferential Path Profiling: Compactly Numbering Interesting Paths
  
  Kapil Vaswani, Aditya Nori, Trishul Chilimbi
  
  Proceedings of the Symposium on Principles of Programming Languages (POPL) | January 2007
  
  PDF
- Unifying Views of Tail-Biting Constructions for Linear Block Codes
  
  Aditya Nori, Priti Shankar
  
  IEEE Transactions on Information Theory | October 2006
  
  PDF
- Exact And Approximate Algorithms for ML Decoding on Tail-Biting Trellises
  
  Priti Shankar, Madhu A. S, Aditya Nori
  
  March 2005
  
  PDF
- A Coset Construction for Tail-Biting Trellises
  
  Aditya Nori, Priti Shankar
  
  Proceedings of the International Symposium on Information Theory and its Applications (ISITA) | October 2004
  
  Proceedings of the International Symposium on Information Theory and its Applications (ISITA)
  
  PDF
- Decoding Codes on Graphs: Probabilistic Decoding
  
  Madhu A. S, Aditya Nori
  
  Resonance: Journal of Science Education, Indian Academy of Sciences | February 2004
  
  Resonance: Journal of Science Education, Indian Academy of Sciences
  
  PDF
- Tail-Biting Trellises for Linear Codes and their Duals
  
  Aditya Nori, Priti Shankar
  
  Proceedings of the Forty-First Annual Allerton Conference on Communication, Control and Computing (Allerton) | October 2003
  
  PDF
- A BCJR-like Labeling Algorithm for Tail-Biting Trellises
  
  Aditya Nori, Priti Shankar
  
  Proceedings of the IEEE International Symposium on Information Theory (ISIT) | July 2003
  
  PDF
- Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology
  
  Anja Thieme, Abhijith Rajamohan, Benjamin Cooper, Heather Groombridge, Robert Simister, Barney Wong, Nicholas Woznitza, Mark Ames Pinnock, Maria Teodora Wetscherek, Cecily Morrison, Hannah Richardson (nee Murfet), Fernando Pérez-García, Stephanie Hyland, Shruthi Bannur, Daniel Coelho de Castro, Kenza Bouzid, Anton Schwaighofer, Mercy Ranjit, Harshita Sharma, Matthew P Lungren, Ozan Oktay, Javier Alvarez-Valle, Aditya Nori, Stephen Harris, Joseph Jacob
  
  ACM ToCHI | August 2025, Vol 32(2): pp. 1-61
  
  Publication DOI Project
- Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology
  
  Kenza Bouzid, Harshita Sharma, Sarah Killcoyne, Daniel Coelho de Castro, Anton Schwaighofer, Maximilian Ilse, Valentina Salvatelli, Ozan Oktay, Sumanth Murthy, Lucas Bordeaux, Luiza Moore, Maria O'Donovan, Anja Thieme, Aditya Nori, Marcel Gehrung, Javier Alvarez-Valle
  
  Nature Communications | March 2024, Vol 15
  
  DOI Publication PDF
- Deep learning for the prediction of clinical outcomes in internet-delivered CBT for depression and anxiety
  
  Niranjani Prasad, Isabel Chien, Tim Regan, Angel Enrique, Jorge Palacios, Dessie Kegan, Usman Munir, Ryutaro Tanno, Hannah Richardson (nee Murfet), Aditya Nori, Derek Richards, Gavin Doherty, Danielle Belgrave, Anja Thieme
  
  PLOS ONE | November 2023, Vol 18(11)
  
  PDF Publication DOI Project
- TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Models
  
  Javier González, Cliff Wong, Zelalem Gero, Jaspreet Bagga, Risa Ueno, Isabel Chien, Eduard Orakvin, Emre Kiciman, Aditya Nori, R. Weerasinghe, R. Leidner, B. Piening, Tristan Naumann, C. Bifulco, Hoifung Poon
  
  ArXiv | November 2023
  
  DOI Publication Publication
- Active label cleaning for improved dataset quality under resource constraints
  
  Melanie Bernhardt, Daniel Coelho de Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem C. Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay
  
  Nature Communications | March 2022, Vol 13(1161): pp. 1-11
  
  Publication Project Project
- Artificial intelligence in healthcare: transforming the practice of medicine
  
  Junaid Bajwa, Aditya Nori, Bryan Williams, Usman Munir
  
  Future Healthcare Journal | July 2021
  
  Publication Video
- Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers
  
  Ozan Oktay, Jay Nanavati, Anton Schwaighofer, David Carter, Melissa Bristow, Ryutaro Tanno, Gill Barnett, David Noble, Yvonne Rimmer, Rajesh Jena, Ben Glocker, Kenton O'Hara, Christopher Bishop, Javier Alvarez-Valle, Aditya Nori
  
  JAMA | November 2020
  
  Publication Video Project
- A Machine Learning Approach to Understanding Patterns of Engagement With Internet-Delivered Mental Health Interventions.
  
  Isabel Chien, Angel Enrique, Jorge Palacios, Tim Regan, Dessie Keegan, David Carter, Sebastian Tschiatschek, Aditya Nori, Anja Thieme, Derek Richards, Gavin Doherty, Danielle Belgrave
  
  JAMA Network | June 2020, Vol 3(7)
  
  DOI Publication Project
- Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features
  
  M. W. Macomber, M. H. Phillips, Ivan Tarapov, R. Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, M. J. Nyflot
  
  Physics in Medicine and Biology | November 2018, Vol 63(23): pp. 235002-235002
  
  DOI PDF Publication
- Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features
  
  Meghan W Macomber, Mark Phillips, Ivan Tarapov, Rajesh Jena, Aditya Nori, David Carter, Loic Le Folgoc, Antonio Criminisi, Matthew J Nyflot
  
  Physics in Medicine & Biology | November 2018, Vol 63(23)
  
  Publication Project
- Automated Software Testing Using Program Analysis
  
  Patrice Godefroid, Jonathan "Peli" de Halleux, Aditya Nori, Sriram Rajamani, Wolfram Schulte, Nikolai Tillmann, Michael Y. Levin
  
  IEEE Software, Special Issue on Software Development Tools | October 2008
  
  PDF Publication Project Project Project
- Decoding Codes on Graphs: Low Density Parity Check Codes
  
  Aditya Nori
  
  Resonance: Journal of Science Education, Indian Academy of Sciences | September 2003
  
  PDF
- Towards Compliant Data Management Systems for Healthcare ML
  
  Goutham Ramakrishnan, Aditya Nori, Hannah Richardson (nee Murfet), Pashmina Cameron
  
  November 2020
  
  November 2020
  
  Publication
- Debugging Machine Learning Tasks
  
  Aleksandar Chakarov, Aditya Nori, Sriram Rajamani, Shayak Sen, Deepak Vijaykeerthy
  
  MSR-TR-2016-1135 | March 2016
  
  PDF
- Semantics Sensitive Sampling for Probabilistic Programs
  
  Aditya Nori, Chung-Kil Hur, Sriram Rajamani, Selva Samuel
  
  MSR-TR-2013-109 | October 2013
  
  PDF Project
- A Model-Learner Pattern for Bayesian Reasoning
  
  Andrew D. Gordon, Mihhail Aizatulin, Guillaume Claret, Thore Graepel, Aditya Nori, Sriram Rajamani, Claudio Russo, Johannes Borgstroem, Andy Gordon
  
  MSR-TR-2013-1 | January 2013
  
  Published by Microsoft
  
  Publication Publication Project Project
- Interpolants as Classifiers
  
  Rahul Sharma, Aditya Nori, Alex Aiken,
  
  MSR-TR-2012-13 | January 2012
  
  PDF
- SYNERGY : A New Algorithm for Property Checking
  
  Bhargav Gulavani, Thomas Henzinger, Yamini Kannan, Aditya Nori, Sriram Rajamani
  
  MSR-TR-2006-76 | April 2006
  
  PDF
- Unifying Views of Tail-Biting Trellises for Linear Block Codes
  
  Aditya Nori
  
  January 2005
  
  January 2005
  
  PDF

Aditya Nori

Publications

Challenges for Responsible AI Design and Workflow Integration in Healthcare: A Case Study of Automatic Feeding Tube Qualification in Radiology

Re-Imagine: Symbolic Benchmark Synthesis for Reasoning Evaluation

Reasoning Elicitation in Language Models via Counterfactual Feedback

Compositional Causal Reasoning Evaluation in Language Models

Does Reasoning Emerge? Examining the Probabilities of Causation in Large Language Models

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

Enabling large-scale screening of Barrett’s esophagus using weakly supervised deep learning in histopathology

RadEdit: Stress-Testing Biomedical Vision Models via Diffusion Image Editing

Deep learning for the prediction of clinical outcomes in internet-delivered CBT for depression and anxiety

TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Models

Exploring the Boundaries of GPT-4 in Radiology

Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing

Foundation Models in Healthcare: Opportunities, Risks & Strategies Forward

Compositional Zero-Shot Domain Transfer with Text-to-Text Models

Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Repairing Neural Networks by Leaving the Right Past Behind

Active label cleaning for improved dataset quality under resource constraints

Artificial intelligence in healthcare: transforming the practice of medicine

Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs

Secure Medical Image Analysis with CrypTFlow

Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers

Towards Compliant Data Management Systems for Healthcare ML

Alleviating Privacy Attacks via Causal Learning

A Machine Learning Approach to Understanding Patterns of Engagement With Internet-Delivered Mental Health Interventions.

Overfitting in Synthesis: Theory and Practice

Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features

Autosegmentation of prostate anatomy for radiation treatment planning using deep decision forests of radiomic features

Autofocus Layer for Semantic Segmentation

Semi-Supervised Learning via Compact Latent Space Clustering

FairSquare: Probabilistic Verification for Program Fairness

Unsupervised domain adaptation in brain lesion segmentation with adversarial networks

Spectral Kernels for Probabilistic Analysis and Clustering of Shapes

Fairness as a Program Property

DeepMedic for Brain Tumor Segmentation

Lifted Auto-Context Forests for Brain Tumour Segmentation

Measuring Neural Net Robustness with Constraints

Debugging Machine Learning Tasks

A Provably Correct Sampler for Probabilistic Programs

Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances

A User-Guided Approach to Program Analysis

Learning Refinement Types

Efficient Synthesis of Probabilistic Programs

Dependent Array Type Inference from Tests

Structurally Heterogeneous Source Code Examples from Unstructured Knowledge Sources

R2: An Efficient MCMC Sampler for Probabilistic Programs

Slicing Probabilistic Programs

MUX: Algorithm Selection for Software Model Checkers

Probabilistic Programming

Bias-Variance Tradeoffs in Program Analysis

A Colorful Approach to Text Processing by Example

Semantics Sensitive Sampling for Probabilistic Programs

Bayesian Inference Using Data Flow Analysis

Termination Proofs from Tests

Combining Relational Learning with SMT Solvers using CEGAR

One-bit Compressed Sensing: Provable Support and Vector Recovery

Verification as Learning Geometric Concepts

Efficiently Sampling Probabilistic Programs via Program Analysis

A Data Driven Approach for Algebraic Loop Invariants

A Model-Learner Pattern for Bayesian Reasoning

Probabilistic Inference Using Program Analysis

Interpolants as Classifiers

Parallelizing Top-Down Interprocedural Analyses

Interpolants as Classifiers

Bottom-up shape analysis using LISF

Probabilistic, Modular and Scalable Inference of Typestate Specifications

Alternation for Termination

An Empirical Study of Optimizations in Yogi

Proofs from Tests

Compositional May-Must Program Analysis: Unleashing the Power of Alternation

Bottom-up Shape Analysis

Measuring the Loss of Privacy from Statistics

Merlin: Specification Inference for Explicit Information Flow Problems

Holmes: Effective Statistical Debugging via Efficient Path Profiling

The Yogi Project: Software Property Checking via Static Analysis and Testing

Automated Software Testing Using Program Analysis

Automatically Refining Abstract Interpretations

Quantifying the Effectiveness of Testing via Efficient Residual Path Profiling

Preferential Path Profiling: Compactly Numbering Interesting Paths