ABOUT ME
About
Associate Research Fellow · IHEP-CAS · PI of the Neutrino AI Lab
I build computational tools for neutrino physics, scientific machine learning, and AI-assisted research.
From JUNO solar and reactor neutrinos to scientific AI agents and CPU/GPU-accelerated reconstruction — I work where detector physics meets modern software.
Where I’m headed
I have been working on large-language-model (LLM) research; going forward I am moving into AI for science along two directions: (1) scaling the models behind AI-for-Science, and (2) building the AI runtime for research.
Education
PhD in Astroparticle Physics
2015 – 2019GSSI (L'Aquila) & SISSA (Trieste), Italy
High-precision spectroscopy of solar neutrinos with Borexino and JUNO. Proposed the TFC method helping JUNO reach a 2 MeV threshold for ⁸B solar neutrinos.
Read thesis ↗MSc in Theoretical Physics
2012 – 2015Wuhan University, China
BSc in Physics
2008 – 2012Wuhan University (Physics base classes), China
Experience
Associate Research Fellow
2023 – presentIHEP-CAS, Beijing
- ·Lead solar neutrino physics; developing machine-learning-based directionality to improve the signal-to-background ratio.
- ·Physics R&D for a new time projection chamber (TPC) detector to measure the low-energy reactor neutrino spectrum.
Postdoctoral Research Associate
2019 – 2022Princeton University, USA
- ·Developed the analysis strategy for the CNO solar neutrino measurement with Borexino Phase-III data.
- ·Developed the BAMBI method, improving Borexino CNO sensitivity from 2σ to 5σ.
Research funding
Principal investigator on ~¥10M of research funding — overseas young-talent grants, topic at my discretion:
- Chinese Academy of Sciences · PI · ¥3M
- National Natural Science Foundation of China · PI · ¥3M
- National Key R&D Program of China (MOST) — sub-project · PI · ¥3M
- Institute of High Energy Physics, CAS · PI · ¥1M