Hansi Zeng 曾翰偲
PhD Student · UMass Amherst, CICS · Information Retrieval & LLMs
About
I am a final‑year PhD student at the University of Massachusetts Amherst, advised by Prof. Hamed Zamani. My research centers on core information retrieval (IR) and agentic reinforcement learning (RL).
In core retrieval, I study optimization, scaling, and new search paradigms and modeling. We use curriculum‑learning–based knowledge distillation to enable compact dense retrievers to match larger models in CL‑DRD [SIGIR’22] (Best Short Paper). I analyze the scaling behavior of sparse and dense retrieval in decoder‑only LLMs [SIGIR’25]. I develop generative‑retrieval methods that generalize to web‑scale corpora [WWW’24], with search‑aware decoding that plans ahead [SIGIR’24], and explore LMs as semantic indexers bridging retrieval and representation learning [ICML’24]. Recently, I work on agentic RL: training LLMs with RL to reason and leverage web search for information‑seeking tasks (Search‑R1) [COLM’25].
🚨 I am currently on the job market! I am actively seeking full-time industry roles (e.g., Applied Scientist / Research Scientist) starting in Summer or Fall 2026.
Selected Publications
Experience
