| 2026 | ASPLOS | Lobster: A GPU-Accelerated Framework for Neurosymbolic Programming. | Paul Biberstein, Ziyang Li, Joseph Devietti, Mayur Naik |
| 2025 | ICLR | LASER: A Neuro-Symbolic Framework for Learning Spatio-Temporal Scene Graphs with Weak Supervision. | Jiani Huang, Ziyang Li, Mayur Naik, Ser-Nam Lim |
| 2025 | ICLR | IRIS: LLM-Assisted Static Analysis for Detecting Security Vulnerabilities. | Ziyang Li, Saikat Dutta, Mayur Naik |
| 2025 | ICML | DOLPHIN: A Programmable Framework for Scalable Neurosymbolic Learning. | Aaditya Naik, Jason Liu, Claire Wang, Amish Sethi, Saikat Dutta, Mayur Naik, Eric Wong |
| 2025 | ICST | Understanding the Effectiveness of Large Language Models in Detecting Security Vulnerabilities. | Avishree Khare, Saikat Dutta, Ziyang Li, Alaia Solko-Breslin, Rajeev Alur, Mayur Naik |
| 2024 | AAAI | Relational Programming with Foundational Models. | Ziyang Li, Jiani Huang, Jason Liu, Felix Zhu, Eric Zhao, William Dodds, Neelay Velingker, Rajeev Alur, Mayur Naik |
| 2024 | ICML | Towards Compositionality in Concept Learning. | Adam Stein, Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong |
| 2024 | ICML | DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation. | Yinjun Wu, Mayank Keoliya, Kan Chen, Neelay Velingker, Ziyang Li, Emily J. Getzen, Qi Long, Mayur Naik, Ravi B. Parikh, Eric Wong |
| 2023 | AAAI | Learning to Select Pivotal Samples for Meta Re-weighting. | Yinjun Wu, Adam Stein, Jacob R. Gardner, Mayur Naik |
| 2023 | ACL | Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming. | Hanlin Zhang, Jiani Huang, Ziyang Li, Mayur Naik, Eric P. Xing |
| 2023 | ICML | Do Machine Learning Models Learn Statistical Rules Inferred from Data? | Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong |
| 2022 | AsiaCCS | PacJam: Securing Dependencies Continuously via Package-Oriented Debloating. | Pardis Pashakhanloo, Aravind Machiry, Hyon-Young Choi, Anthony Canino, Kihong Heo, Insup Lee, Mayur Naik |
| 2022 | ICLR | CodeTrek: Flexible Modeling of Code using an Extensible Relational Representation. | Pardis Pashakhanloo, Aaditya Naik, Yuepeng Wang, Hanjun Dai, Petros Maniatis, Mayur Naik |
| 2021 | AAAI | GENSYNTH: Synthesizing Datalog Programs without Language Bias. | Jonathan Mendelson, Aaditya Naik, Mukund Raghothaman, Mayur Naik |
| 2021 | PLDI | Example-guided synthesis of relational queries. | Aalok Thakkar, Aaditya Naik, Nathaniel Sands, Rajeev Alur, Mayur Naik, Mukund Raghothaman |
| 2021 | UIST | Sporq: An Interactive Environment for Exploring Code using Query-by-Example. | Aaditya Naik, Jonathan Mendelson, Nathaniel Sands, Yuepeng Wang, Mayur Naik, Mukund Raghothaman |
| 2021 | SP | ARBITRAR: User-Guided API Misuse Detection. | Ziyang Li, Aravind Machiry, Binghong Chen, Mayur Naik, Ke Wang, Le Song |
| 2020 | CAV | Code2Inv: A Deep Learning Framework for Program Verification. | Xujie Si, Aaditya Naik, Hanjun Dai, Mayur Naik, Le Song |
| 2020 | ICLR | Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs. | Elizabeth Dinella, Hanjun Dai, Ziyang Li, Mayur Naik, Le Song, Ke Wang |
| 2020 | ICML | Generating Programmatic Referring Expressions via Program Synthesis. | Jiani Huang, Calvin Smith, Osbert Bastani, Rishabh Singh, Aws Albarghouthi, Mayur Naik |
| 2019 | ICLR | Learning a Meta-Solver for Syntax-Guided Program Synthesis. | Xujie Si, Yuan Yang, Hanjun Dai, Mayur Naik, Le Song |
| 2019 | ICLR | Learning Neurosymbolic Generative Models via Program synthesis. | Halley Young, Osbert Bastani, Mayur Naik |
| 2019 | ICML | Learning Neurosymbolic Generative Models via Program Synthesis. | Halley Young, Osbert Bastani, Mayur Naik |
| 2019 | IJCAI | Synthesizing Datalog Programs using Numerical Relaxation. | Xujie Si, Mukund Raghothaman, Kihong Heo, Mayur Naik |
| 2019 | PLDI | Continuously reasoning about programs using differential Bayesian inference. | Kihong Heo, Mukund Raghothaman, Xujie Si, Mayur Naik |
| 2019 | SAS | Rethinking Static Analysis by Combining Discrete and Continuous Reasoning. | Mayur Naik |
| 2018 | CCS | Effective Program Debloating via Reinforcement Learning. | Kihong Heo, Woosuk Lee, Pardis Pashakhanloo, Mayur Naik |
| 2018 | CCS | FEAST'18 - 2018 Workshop on Forming an Ecosystem around Software Transformation. | Yan Shoshitaishvili, Mayur Naik |
| 2018 | PLDI | Accelerating search-based program synthesis using learned probabilistic models. | Woosuk Lee, Kihong Heo, Rajeev Alur, Mayur Naik |
| 2018 | PLDI | User-guided program reasoning using Bayesian inference. | Mukund Raghothaman, Sulekha Kulkarni, Kihong Heo, Mayur Naik |
| 2017 | CAV | Maximum Satisfiability in Software Analysis: Applications and Techniques. | Xujie Si, Xin Zhang, Radu Grigore, Mayur Naik |
| 2017 | CP | Constraint-Based Synthesis of Datalog Programs. | Aws Albarghouthi, Paraschos Koutris, Mayur Naik, Calvin Smith |
| 2017 | PLDI | Combining the logical and the probabilistic in program analysis. | Xin Zhang, Xujie Si, Mayur Naik |
| 2016 | AAAI | Scaling Relational Inference Using Proofs and Refutations. | Ravi Mangal, Xin Zhang, Aditya Kamath, Aditya V. Nori, Mayur Naik |
| 2016 | CP | On Incremental Core-Guided MaxSAT Solving. | Xujie Si, Xin Zhang, Vasco Manquinho, Mikols Janota, Alexey Ignatiev, Mayur Naik |
| 2016 | OOPSLA | Accelerating program analyses by cross-program training. | Sulekha Kulkarni, Ravi Mangal, Xin Zhang, Mayur Naik |
| 2016 | POPL | Query-guided maximum satisfiability. | Xin Zhang, Ravi Mangal, Aditya V. Nori, Mayur Naik |
| 2015 | SAS | Modularity in Lattices: A Case Study on the Correspondence Between Top-Down and Bottom-Up Analysis. | Ghila Castelnuovo, Mayur Naik, Noam Rinetzky, Mooly Sagiv, Hongseok Yang |
| 2015 | SAT | Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances. | Ravi Mangal, Xin Zhang, Aditya V. Nori, Mayur Naik |
| 2014 | ESOP | A Correspondence between Two Approaches to Interprocedural Analysis in the Presence of Join. | Ravi Mangal, Mayur Naik, Hongseok Yang |
| 2014 | MOBIHOC | COSMOS: computation offloading as a service for mobile devices. | Cong Shi, Karim Habak, Pranesh Pandurangan, Mostafa H. Ammar, Mayur Naik, Ellen W. Zegura |
| 2014 | PLDI | Large-scale configurable static analysis. | Mayur Naik |
| 2014 | PLDI | On abstraction refinement for program analyses in Datalog. | Xin Zhang, Ravi Mangal, Radu Grigore, Mayur Naik, Hongseok Yang |
| 2014 | PLDI | Hybrid top-down and bottom-up interprocedural analysis. | Xin Zhang, Ravi Mangal, Mayur Naik, Hongseok Yang |
| 2013 | PLDI | Finding optimum abstractions in parametric dataflow analysis. | Xin Zhang, Mayur Naik, Hongseok Yang |
| 2013 | USENIX | Mantis: Automatic Performance Prediction for Smartphone Applications. | Yongin Kwon, Sangmin Lee, Hayoon Yi, Donghyun Kwon, Seungjun Yang, Byung-Gon Chun, Ling Huang, Petros Maniatis, Mayur Naik, Yunheung Paek |
| 2012 | POPL | Abstractions from tests. | Mayur Naik, Hongseok Yang, Ghila Castelnuovo, Mooly Sagiv |
| 2012 | SIGCOMM | Computing in cirrus clouds: the challenge of intermittent connectivity. | Cong Shi, Mostafa H. Ammar, Ellen W. Zegura, Mayur Naik |
| 2011 | EuroSys | CloneCloud: elastic execution between mobile device and cloud. | Byung-Gon Chun, Sunghwan Ihm, Petros Maniatis, Mayur Naik, Ashwin Patti |
| 2011 | PLDI | Scaling abstraction refinement via pruning. | Percy Liang, Mayur Naik |
| 2011 | POPL | Learning minimal abstractions. | Percy Liang, Omer Tripp, Mayur Naik |
| 2010 | OOPSLA | A dynamic evaluation of the precision of static heap abstractions. | Percy Liang, Omer Tripp, Mayur Naik, Mooly Sagiv |
| 2009 | CAV | CalFuzzer: An Extensible Active Testing Framework for Concurrent Programs. | Pallavi Joshi, Mayur Naik, Chang-Seo Park, Koushik Sen |
| 2009 | ICSE | Effective static deadlock detection. | Mayur Naik, Chang-Seo Park, Koushik Sen, David Gay |
| 2009 | PLDI | Lightweight annotations for controlling sharing in concurrent data structures. | Zachary R. Anderson, David Gay, Mayur Naik |
| 2009 | PLDI | A randomized dynamic program analysis technique for detecting real deadlocks. | Pallavi Joshi, Chang-Seo Park, Koushik Sen, Mayur Naik |
| 2007 | POPL | Conditional must not aliasing for static race detection. | Mayur Naik, Alex Aiken |
| 2006 | ICML | Statistical debugging: simultaneous identification of multiple bugs. | Alice X. Zheng, Michael I. Jordan, Ben Liblit, Mayur Naik, Alex Aiken |
| 2006 | PLDI | Effective static race detection for Java. | Mayur Naik, Alex Aiken, John Whaley |
| 2005 | ESOP | A Type System Equivalent to a Model Checker. | Mayur Naik, Jens Palsberg |
| 2005 | PLDI | Scalable statistical bug isolation. | Ben Liblit, Mayur Naik, Alice X. Zheng, Alex Aiken, Michael I. Jordan |
| 2003 | POPL | From symptom to cause: localizing errors in counterexample traces. | Thomas Ball, Mayur Naik, Sriram K. Rajamani |