I do research on AI safety and security. Reach out to me via email if you’d like to get in contact for discussion or collaboration. I’m always open to talk about research ideas.

I’m broadly interested in the security and robustness for deep learning models as well as understanding their capabilities for generalization in out of distribution settings. I’ve recently been researching the ability of LLMs to encode and interpret information that is subliminal to humans. Currently, I’m focused on defending against data poisoning threats, which I believe pose a critical risk as the adoption of AI increases exponentially.

I’m currently advised by Shi Feng under the MATS research fellowship. At NYU, I’m advised by Rico Angell in He He’s research group. I’m also extremely fortunate for the mentorship of Chawin Sitawarin (Google DeepMind) during my undergraduate studies at UC Berkeley as a part of David Wagner’s group.

I’m a fan of landscape photography. Here’s a randomly sampled photo from my portfolio, most of which were taken on my Canon EOS R50:

Publications

On-Policy Consistency Training Improves LLM Safety with Minimal Capability Degradation
Han, A.*, Fujimoto, K.*, Shah, A.*, Nguyen, K., Xu, K., Yueh-Han, C., Sucholutsky, I., & Angell, R.
arxiv, 2026
On-Policy Consistency Training (OPCT) supervises a model on its own responses conditioned on contrastive prompts, reducing sycophancy and maintaining jailbreak defense without the capability degradation that supervised fine-tuning induces.

Rapid Poison: Practical Poisoning Attacks Against the Rapid Response Framework
Huang, D.*, Chang, J.*, Shah, A.*, Mittal, P., & Sitawarin, C.
ICML (Spotlight), 2026
Practical prompt-injection-based poisoning attacks against the Rapid Response jailbreak detection framework, including a novel Omission Attack that flips ~90% of target labels with only 1% poisoning rate.

Stronger Universal and Transfer Attacks by Suppressing Refusals
Huang, D., Shah, A., Araujo, A., Wagner, D., & Sitawarin, C.
NAACL, 2025
A novel algorithm leveraging model refusal representation for automated jailbreaking suffix generation on LLMs

Efficient Mitigation of Bus Bunching through Setter-Based Curriculum Learning
Shah, A., Tran, D., & Tang, Y.
arxiv, 2023
Explores efficient solutions for transportation optimization via model based curriculum learning