I am a PhD student at the University of Michigan, Ann Arbor advised by (Prof. Gabriel Poesia).
I love abstractions. They are the strange inventions of the mind that allow us to move through a world far too large and complicated to understand directly. We turn experiences into concepts, concepts into rules, and rules into reusable ideas. We recognize a pattern once, give it a name, and suddenly we can see it everywhere.
I am interested in whether machines can do the same. My research explores how AI systems can learn abstractions from experience: discovering concepts, programs, and reusable structures that allow them to generalize beyond what they have seen. I am particularly interested in the connection between learning and programming—how experiences can become abstractions, and how those abstractions can become the building blocks of increasingly rich models of the world. For fun, I do lot of things and I am almost always interested to try soemthing new lately I have been learning tennis.
Previously, I was a Research Fellow (Pre-Doctoral) at Microsoft Research India, where I was part of the program synthesis group (PROSE) and the AI4Code team. I was privileged to work with Aditya Kanade, Ashish Tiwari, Gustavo Soares, Arjun Radhakrishna, Sumit Gulwani, and Arun Iyer.
Most recent publications on Google Scholar.
‡ indicates equal contribution.
Improving Language Agents with BREW:
Shashank Kirtania, Param Biyani, Priyanshu Gupta, Yasharth Bajpai, Roshni Iyer, Sumit Gulwani, Gustavo Soares
Conference of Language Modeling 2026, Multi-Turn Interaction Workshop at NeurIPS 2025
Activation Steering in Theorem Prover LLMs
Shashank Kirtania, Arun Iyer
FM in Wild Workshop ICLR'2025
STACKFEED: Structured Textual Actor-Critic Knowledge Base Editing with Feedback
Shashank Kirtania‡, Naman Gupta‡, Priyanshu Gupta, Krishna Kariya, Sumit Gulwani, Arun Iyer, Suresh Parthasarathy, Arjun Radhakrishna, Sriram K. Rajamani, Gustavo Soares
Empirical Methods in Natural Language Processing 2025, DL for Code Workshop NeurIPS 2025
MetaReflection: Learning Instructions for Language Agents using Past Reflections
Shashank Kirtania‡, Priyanshu Gupta‡, Annanya Singha‡, Sumit Gulwani, Arjun Radhakrishna, Sherry Shi, Gustavo Soares
Empirical Methods in Natural Language Processing 2024
Improving Language Agents with BREW:
Shashank Kirtania, Param Biyani, Priyanshu Gupta, Yasharth Bajpai, Roshni Iyer, Sumit Gulwani, Gustavo Soares
Conference of Language Modeling 2026, Multi-Turn Interaction Workshop at NeurIPS 2025
Activation Steering in Theorem Prover LLMs
Shashank Kirtania, Arun Iyer
FM in Wild Workshop ICLR'2025
STACKFEED: Structured Textual Actor-Critic Knowledge Base Editing with Feedback
Shashank Kirtania‡, Naman Gupta‡, Priyanshu Gupta, Krishna Kariya, Sumit Gulwani, Arun Iyer, Suresh Parthasarathy, Arjun Radhakrishna, Sriram K. Rajamani, Gustavo Soares
Empirical Methods in Natural Language Processing 2025, DL for Code Workshop NeurIPS 2025
MetaReflection: Learning Instructions for Language Agents using Past Reflections
Shashank Kirtania‡, Priyanshu Gupta‡, Annanya Singha‡, Sumit Gulwani, Arjun Radhakrishna, Sherry Shi, Gustavo Soares
Empirical Methods in Natural Language Processing 2024
LOGIC-LM++: Multi-Step Refinement for Symbolic Formulations
Shashank Kirtania, Priyanshu Gupta, Arjun Radhakrishna
Workshop on Natural Language Reasoning at ACL 2024
DWT-CompCNN: Deep Image Classification Network for High Throughput JPEG 2000 Compressed Documents
Tejasvee Bisen, Mohammed Javed, Shashank Kirtania, P Nagabhushan
Pattern Analysis and Applications, Springer, 2023.
A collection of trains of thought and lines of research, inspired by Kartik Chandra and Shubhra Mishra.
Full Resume in PDF.