I am a fourth year PhD student in CS at Arizona State University, advised by Chitta Baral in the Cognition and Intelligence Lab. I previously interned at Microsoft Research, where I worked on automating synthetic data generation pipelines to build capable LLM agents.
My research focuses on post-training and alignment of LLMs (TPO, DCPO), building reliable agentic systems (IRMA, FAMA), and scaling synthetic data generation for agent learning (VULCAN, CAST, ML-AutoResearch). More broadly, I am interested in developing reliable LLM agents for complex real-world settings, as well as agentic systems for scientific discovery and automated research.
I am actively looking for industry research positions focused on agentic systems, LLM post-training, and synthetic data generation. Feel free to reach out!
ML-AutoResearch: Training Machine Learning Research Agents with Automatically Generated Environments
NeurIPS 2026
CAST: Critique-Aware Supervision for Training Reliable Long-Horizon Tool-Calling Agents
EMNLP 2026
FAMA: Failure-Aware Meta-Agentic Framework for Open-Source LLMs in Interactive Tool Use Environments
ACL 2026 Findings
How Can Input Reformulation Improve Tool Usage Accuracy in a Complex Dynamic Environment? A Study on ฯ-bench
EMNLP 2025 Findings ยท MTI-LLM Workshop at NeurIPS 2025
When "Competency" in Reasoning Opens the Door to Vulnerability: Jailbreaking LLMs via Novel Complex Ciphers
Reliable ML Workshop at NeurIPS 2025
Evaluating Multimodal Large Language Models Across Distribution Shifts and Augmentations
EVGENFM Workshop at CVPR 2024
Investigating and Addressing Hallucinations of LLMs in Tasks Involving Negation
TrustNLP Workshop at NAACL 2025
Insights into Alignment: Evaluating DPO and its Variants Across Multiple Tasks
SRW Workshop at ACL 2025