Biosketch

Kumar Madhukar joined the department of Computer Science and Engineering at IIT Delhi in October 2021. Before that, he was working with TCS Research in Pune. He completed his Ph.D. from the Chennai Mathematical Institute (CMI) in 2018. Prior to that, he had done a Bachelor in Mathematics (Hons.), and a Master in Computer Science, also from CMI. His research interests broadly lie in Software Verification, Synthesis, Model Checking and Deep Learning.

Recent Publications

• Mukhopadhyay, D., Siddiqui, S., Karmarkar, H., Madhukar, K., & Katz, G. (2024, October). Learning DNN Abstractions using Gradient Descent. In Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering (pp. 2299-2303).
• Siddiqui, S., Mukhopadhyay, D., Afzal, M., Karmarkar, H., & Madhukar, K. (2024, August). Unifying Syntactic and Semantic Abstractions for Deep Neural Networks. In International Conference on Formal Methods for Industrial Critical Systems (pp. 201-219). Cham: Springer Nature Switzerland.
• Shenoy, A., Prabhu, S., Madhukar, K., Shemer, R., & Srivas, M. (2023, October). Automated Property Directed Self Composition. In International Symposium on Automated Technology for Verification and Analysis (pp. 139-158). Cham: Springer Nature Switzerland.
• Mukhopadhyay, D., Madhukar, K., & Srivas, M. (2022, May). Permutation Invariance of Deep Neural Networks with ReLUs. In NASA Formal Methods Symposium (pp. 318-337). Cham: Springer International Publishing.
• Prabhu, S., Fedyukovich, G., Madhukar, K., & D'Souza, D. (2021, June). Specification synthesis with constrained Horn clauses. In Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation (pp. 1203-1217).