Anmol Kabra
anmol (at) cs.cornell.edu • CV • google scholar • github • linkedin • bsky • twitter

I am a Computer Science PhD student at Cornell University, advised by Carla Gomes and Kilian Weinberger. I study and develop reasoning and agentic capabilities in LLMs, with applications in AI for Science. Driven by these applications, my research has focused on reinforcemment learning, multimodal models, and distribution shifts.
Previously, I was a Research Engineer at ASAPP working on LLMs, privacy, and anomaly detection with Ethan Elenberg and Kilian Weinberger. I was also an AI/ML Quant intern at Bloomberg working on quantitative trading strategies and LLMs with the AI Engineering team.
I received my Bachelors in Science in Computer Science and Applied Math from Cornell University in Spring 2020 and was named a Merrill Presidential Scholar. I had the good fortune of doing ML research at the Computational Sustainability lab with Carla Gomes. During my undergraduate years, I was generously supported by the Tata Scholarship and Telluride Scholarship. Before returning to Cornell for my PhD, I studied ML for decision-making at Toyota Technological Institute at Chicago (TTIC).
news
Jun 2025
- Paper accepted to ICML 2025: PhantomWiki: On-Demand Datasets for Reasoning and Retrieval Evaluation with code on github. Also accepted to ICML Workshop on Long-Context Foundation Models.
2024
- Paper released on arxiv: AiSciVision: A Framework for Specializing Large Multimodal Models in Scientific Image Classification with code on github.
- Started PhD at Cornell Computer Science.
- Paper accepted to ICML Workshop on Humans, Algorithmic Decision-Making and Society: The Limitations of Model Retraining in the Face of Performativity.
- Talk and poster at Foundations of Responsible Computing (FORC) 2024: Score Design for Multi-Criteria Incentivization.
- Joined Bloomberg LP as an AI/ML Quant Intern in New York City.
- Paper accepted to Foundations of Responsible Computing (FORC) 2024: Score Design for Multi-Criteria Incentivization.
- Talk at TTIC’s Annual Student Workshop: Surrogate score design to incentivize behavior in rating systems.
2023
- Paper accepted to Findings of EMNLP 2023: Domain Private Transformers for Multi-Domain Dialog Systems.
- Presented at IDEAL Institute’s Workshop on Machine Learning, Interpretability, and Logic: Reasonable modeling assumptions for real-world Principal-Agent games.
2022
- Received the Best Poster Award at TTIC’s Annual Student Workshop.
- Paper accepted to NeurIPS 2022 (Oral award): Exponential Family Model-Based Reinforcement Learning via Score Matching.
- Joined ASAPP as a Research Intern.
- Attended Deep Learning Theory Workshop and Summer School at the Simons Institute at Berkeley.
- Visited the Simons Institute at Berkeley for the summer cluster on Interpretable ML.
- Attended the ML Theory summer school at Princeton.
2021
- Started graduate studies at Toyota Technological Institute at Chicago (TTIC).
- Paper accepted to AAAI 2021: Characterizing the Loss Landscape in Non-Negative Matrix Factorization.
2020
- Joined ASAPP as a Research Engineer in Ithaca, NY.
- Graduated from Cornell!
- Recognized as a 2020 Merrill Presidential Scholar (top 1% of graduating class).
- Received the 2020 Computer Science Prize for Academic Excellence (highest undergraduate honor in the CS department).
2019
- Featured among 10 out of 200 young researchers at the 2019 Heidelberg Laureate Forum.
- Recognized for outstanding performance (top-10%) at 2019 ACM Summer School on HPC Architectures for AI and Dedicated Applications, Barcelona.
- Recognized as an Outstanding Teaching Assistant for CS 4850: Math Foundations of the Info Age.
- Paper accepted to ACM COMPASS 2019: GPU-accelerated Principal-Agent Game for Scalable Citizen Science.
- Best poster at 2019 Ivy League Undergraduate Research Symposium at University of Pennsylvania.
- 2 awards at Cornell CIS’s BOOM 2019 project symposium (Sponsor Award by Air Liquide and Statistics Award by Cornell’s Statistics Department).
- Joined ASAPP as a Research Engineer Intern.
selected papers
* equal contributions
on a less academic note, I like
(listed in increasing order of number of characters in each bullet)
- biking
- cooking
- running
- playing Table Tennis
- following Formula 1 and motorsports
- walking fast so that my legs heat up
- reading books, newspapers, and research papers — mostly high-fantasy and non-fiction these days