AI for Life Sciences
Multi-omics, spatial biology, single-cell epigenomics, RNA design, and biological representation learning for scientific discovery.
About Me
I am a Principal Research Scientist at the Shanghai Academy of Artificial Intelligence for Science (SAIS), where I work on AI for life sciences and scientific discovery. My research focuses on multi-omics, biological representation learning, scientific foundation models, and AI systems that can support reliable discovery workflows.
Representative work includes FLAG for spatial gene expression prediction, ChromFound for single-cell chromatin accessibility modeling, and SOLD for structure-based RNA design. Before SAIS, I spent eight years at Ant and Alibaba Group building applied AI systems across computer vision, multimodal perception, and foundation models, with earlier research and engineering experience at Sony and Tractable in Europe.
20+
papers
10+
international patents
10+
years in AI
Research Highlights
Multimodal Scientific Foundation Models
Foundation models for heterogeneous scientific data, aligning molecular, omics, imaging, and structured biological signals into reusable representations.
Scientific Agentic AI
Reasoning and tool-using AI systems that plan, call scientific tools, and support reliable discovery workflows.
Automated Labs for Closed-Loop Discovery
AI-driven experimental platforms that connect hypothesis generation, experiment planning, robotic execution, measurement, and feedback.
Selected Publications
View all publications →* Equal contribution · ✉ Corresponding Author
HorusEye: a self-supervised foundation model for generalizable X-ray tomography restoration
Nature Computational Science, 2026
Sprint or Delve: A Distribution-Aware Approach to Efficient Reasoning
IJCAI 2026
Recent News
More news →🏅 Honored to receive the ICML 2026 Silver Reviewer Award. Grateful for the recognition and for the opportunity to contribute to the research community.
🎉 Two papers accepted: FLAG, on foundation-model-aligned latent diffusion for spatial gene expression prediction, at ICML 2026; and "Sprint or Delve: A Distribution-Aware Approach to Efficient Reasoning" at IJCAI 2026. Congrats to all co-authors!
📚 Two recent works have been published: one in Nature Computational Science on generalizable X-ray tomography restoration, and another in AAAI 2026 focusing on structure-based RNA design using latent diffusion models.
🏅 Honored to be selected for the Shanghai Oriental Talent Program (Young Talent Project). Grateful for the recognition and support from the Shanghai government.
Experience
Academic & Professional Activities →-
Apr. 2024 - Present
Principal Research Scientist
SAIS -
Apr. 2016 - Apr. 2024
Senior R&D Engineer
Ant & Alibaba Group -
Sep. 2012 - Nov. 2015
MSc in Communication Systems
EPFL -
Sep. 2008 - Jun. 2012
BEng with Honors
Zhejiang University -
Contact
I welcome collaborations in AI for life sciences, multimodal scientific foundation models, scientific agentic AI, and automated labs for closed-loop discovery, including multi-omics, spatial biology, RNA design, and tool-using AI systems.