Po-Chung (Bryan) Hsieh

Po-Chung (Bryan) Hsieh

M.S. Student in Electrical and Computer Engineering
I am an M.S. student in Electrical and Computer Engineering at UC San Diego, with a B.S. in Electrical Engineering from National Taiwan University. I build AI agents and reinforcement learning methods for scientific discovery, including multi-agent systems for biomedical feature discovery and policy optimization for discrete generative models, and I previously worked as an LLM engineer intern at the Inventec Artificial Intelligence Center.

Discrete Flow Matching Policy Optimization

Introduces DoMinO, an RL framework that treats discrete flow-matching inference as an inner MDP. Outperforms prior state-of-the-art by 10.6% on regulatory DNA design and 15.4% on …

m.-su
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The Binding Effect: Analyzing How Multi-Dimensional Cues Form Gender Bias in Instruction TTS

Accepted to INTERSPEECH 2026.

k.-y.-chen
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Dual-Process Scaffold Reasoning for Enhancing LLM Code Debugging

A dual-process scaffold reasoning framework for LLM code debugging, reaching an 88.91% pass rate on DebugBench.

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Po-Chung (Bryan) Hsieh
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