My interests are in the design and analysis of reliable intelligent systems, and I am currently working on precise and robust medical image analysis for cancer treatment.
In the past, together with wonderful colleagues, I have worked on exploring various synergies between programming languages and machine learning: a) ML4PL: the use of machine learning techniques in program verification, specification inference via Bayesian analysis, and b) PL4ML: probabilistic programming via program analysis, and productivity tools for machine learning tasks. I have also built a number of programmer productivity tools, and this includes the Yogi software model checker for device drivers.
A complete list of publications can be found here.
- Aleksandar Chakarov, Aditya V. Nori, Sriram K. Rajamani, Shayak Sen, and Deepak Vijaykeerthy. Debugging Machine Learning Tasks. CoRR abs/1603.07292 (2016)
- Ravi Mangal, Xin Zhang, Aditya Kamath, Aditya V. Nori, and Mayur Naik. Scaling Relational Inference using Proofs and Refutations. In AAAI '16: AAAI Conference on Artificial Intelligence, February 2016
- Xin Zhang, Ravi Mangal, Aditya V. Nori, and Mayur Naik. Query-guided Maximum Satisfiability. In POPL '16: Principles of Programming Languages, January 2016
- Chung-Kil Hur, Aditya V. Nori, Sriram K. Rajamani, and Selva Samuel. A Provably Correct Sampler for Probabilistic Programs. In FSTTCS '15: Foundations of Software Technology and Theoretical Computer Science, December 2015
- Ravi Mangal, Xin Zhang, Aditya V. Nori, and Mayur Naik. Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances. In SAT '15: International Conference on Theory and Applications of Satisfiability Testing, September 2015
- Ravi Mangal, Xin Zhang, Aditya V. Nori, and Mayur Naik. A User-Guided Approach to Program Analysis. In FSE '15: Foundations of Software Engineering (ACM SIGSOFT Distinguished Paper), August 2015
- He Zhu, Aditya V. Nori, and Suresh Jagannathan. Learning Refinement Types. In ICFP '15: International Conference on Functional Programming, August 2015
- Aditya V. Nori, Sherjil Ozair, Sriram K. Rajamani, and Deepak Vijaykeerthy. Efficient Synthesis of Probabilistic Programs. In PLDI '15: Programming Languages Design and Implementation, June 2015
- He Zhu, Aditya V. Nori, and Suresh Jagannathan. Dependent Array Type Inference from Tests. In VMCAI '15: Verification, Model Checking and Abstract Interpretation, January 2015
- Venkatesh Vinayakarao, Rahul Purandare, and Aditya V. Nori. Structurally Heterogeneous Source Code Examples from Unstructured Knowledge Sources. In PEPM '15: Partial Evaluation and Program Manipulation, January 2015
- Invited talks: DARPA PPAML 2016, ACM-SIGSOFT-Webinar 2015, CAV-SYNT 2015, IISc-CSA Summer School 2014, Formalise 2014, Formal Methods Update 2014, IISc-CSA Summer School 2013, Formal Methods Workshop 2013, WING 2012, IMPECS CSA Workshop 2012, 17th CREST workshop 2012, Mysore Workshop on Machine Learning 2012
- Program Committees:
- 2016: ICSE Demos (co-chair), FSE
- 2015: ML4PL, POPL-OBT
- 2014: CSTVA, SAS, FSE, ICSE SRC (co-chair), ICSE SEIP, ISEC, POPL, HVC
- 2013: PASTE, VSTTE, ICSE Tutorials (co-chair), PLDI (ERC), ACM SIGSOFT Doctoral Dissertation Committee, ICST MP
- 2012: ATVA, FTfJP, ICSE SRC, ISSTA, POPL (ERC), FSE
- 2011: ISSTA, ICSE SRC, TOOLS Europe, ICST
- 2010: SAVCBS, APLAS, ICST
- 2009: ISSRE, SSS, FSTTCS, SAS, ISSTA
- 2008: ISSRE
- Teaching: Program Analysis & Verification, Indian Institute of Science, Fall 2008, Fall 2007 (with Deepak D'Souza and Sriram Rajamani)
Here is a list of interns and students I have advised in the past. Please email me if you are interested in working on problems \in (PL \cap ML).
Microsoft Research Ltd, 21 Station Road, Cambridge CB1 2FB, United Kingdom
Email: adityan AT microsoft.com
Phone: +44 1223 479700