| 2019 | CCS | CADENCE: Conditional Anomaly Detection for Events Using Noise-Contrastive Estimation. | Mohammad Ruhul Amin, Pranav Garg, Baris Coskun |
| 2019 | SAS | Sorcar: Property-Driven Algorithms for Learning Conjunctive Invariants. | Daniel Neider, Shambwaditya Saha, Pranav Garg, P. Madhusudan |
| 2018 | TACAS | Invariant Synthesis for Incomplete Verification Engines. | Daniel Neider, Pranav Garg, P. Madhusudan, Shambwaditya Saha, Daejun Park |
| 2017 | ICST | Efficient Incrementalized Runtime Checking of Linear Measures on Lists. | Alex Gyori, Pranav Garg, Edgar Pek, P. Madhusudan |
| 2016 | POPL | Learning invariants using decision trees and implication counterexamples. | Pranav Garg, Daniel Neider, P. Madhusudan, Dan Roth |
| 2015 | CAV | Alchemist: Learning Guarded Affine Functions. | Shambwaditya Saha, Pranav Garg, P. Madhusudan |
| 2014 | CAV | ICE: A Robust Framework for Learning Invariants. | Pranav Garg, Christof Lding, P. Madhusudan, Daniel Neider |
| 2014 | OOPSLA | Natural proofs for asynchronous programs using almost-synchronous reductions. | Ankush Desai, Pranav Garg, P. Madhusudan |
| 2013 | CAV | Learning Universally Quantified Invariants of Linear Data Structures. | Pranav Garg, Christof Lding, P. Madhusudan, Daniel Neider |
| 2013 | ICSE | Feedback-directed unit test generation for C/C++ using concolic execution. | Pranav Garg, Franjo Ivancic, Gogul Balakrishnan, Naoto Maeda, Aarti Gupta |
| 2013 | PLDI | Natural proofs for structure, data, and separation. | Xiaokang Qiu, Pranav Garg, Andrei Stefanescu, Parthasarathy Madhusudan |
| 2013 | SAS | Quantified Data Automata on Skinny Trees: An Abstract Domain for Lists. | Pranav Garg, P. Madhusudan, Gennaro Parlato |
| 2011 | ISCA | Rebound: scalable checkpointing for coherent shared memory. | Rishi Agarwal, Pranav Garg, Josep Torrellas |
| 2011 | TACAS | Compositionality Entails Sequentializability. | Pranav Garg, P. Madhusudan |