About Me

I am a first-year Computer Science PhD student at the University of Wisconsin-Madison, advised by Prof. Junjie Hu, and I'm fortunate to be supported by the NSF Graduate Research Fellowship (GRFP). I previously earned my bachelor's degree in Computer Science from the University of Massachusetts Amherst.

Research Interests

My research seeks to understand model reasoning as an emergent capability across diverse settings, evaluate whether it is faithful, trustworthy, and safe, and harness it to build AI systems that can improve themselves. I approach these questions through:

AI Safety

Understanding and mitigating harmful behaviors in reasoning models

  • Mechanistic interpretability
  • Chain-of-thought faithfulness & monitorability
  • Jailbreak analysis & robustness
  • LLM-as-judge evaluation & reliability

Self-improving Agentic Systems

The development of agentic systems that improve their own reasoning in open-ended settings

  • Open-ended & evolutionary search (e.g., DGM / AlphaEvolve-style methods)
  • Self-evolving systems & recursive self-improvement
  • Evaluator design & reward modeling
  • Test-time adaptation & inference-time scaling

Publications

COLM
2026

When Safety Fails Before the Answer: Benchmarking Harmful Behavior Detection in Reasoning Chains

Ishita Kakkar, Enze Zhang, Rheeya Uppaal, Junjie Hu

We introduce a step-level taxonomy and an annotated dataset HarmThoughts, that traces how harm emerges and propagates through a model's reasoning.

ICWSM
2026

Fluent but Unfeeling: The Emotional Blind Spots of Language Models

Bangzhao Shu, Isha Joshi, Melissa Karnaze, Anh C Pham, Ishita Kakkar, Sindhu Kothe, Arpine Hovasapian, Mai ElSherief

We introduce EXPRESS, a benchmark of 251 fine-grained, self-disclosed emotion labels from Reddit, and show that even strong LLMs struggle to match how people actually describe their own emotions.

Awards

Personal

I love graphic design and calligraphy! Check out my work here.