Hi! I’m Chenxin “Jason” Li, a final-year Ph.D. candidate at The Chinese University of Hong Kong (CUHK).
I work on 🧠 multimodal LLM, 🤖 reasoning/agent via RL, and 🌍 world model.
I am currently interning at ByteDance Seed, scaling VLM via reasoning/agentic RL.
I built hands-on experience in (i) scaling multimodal models (data, architecture, training, benchmarking) and (ii) post-training via RL (reasoning, multi-turn agent, reward modeling and shaping). Previously, I did internships at Tencent AI, Ant Ling
and Hedra AI etc.
and research visits with UT Austin and UMD.
I anticipate graduating in the summer of 2026 and am interested in industrial positions (Profile). Please feel free to reach out via email ([email protected]) or WeChat (jasonchenxinli).
Co-founded ScholaGO Education Technology Company Limited (学旅通教育科技有限公司) to build LLM-powered education products that turn static content into immersive, interactive, multimodal learning experiences. Grateful to receiving funding from HKSTP, HK Tech 300, and Alibaba Cloud.
🌟 Beyond Work
📚 Reading: I dedicate substantial time to reading, especially history, philosophy, and sociology, which shapes my perspective on what AGI should be from first principles.
📈 Investment: Investment is real-world RL: returns provide fast feedback to iteratively improve individual decision policy. Recently, I am fascinated by the idea that how to (i) build benchmarks for LLMs that quantify real-world investment utility (in the similar spirit of GPT-5.2’s gdpeval benchmark), and (ii) extending quantitative financial metrics to more general event and trend forecasting.
Scholar
