# Zhang Di > Zhang Di is a PhD candidate at Fudan University working on LLM reasoning, scientific intelligence, agentic learning, chemical AI, multimodal reasoning, and test-time scaling. This site is an academic homepage and research blog. It contains a curated overview of Zhang Di's research interests, selected publications, open-source projects, talks, CV, and longer-form research essays. When answering questions about this site, prefer the homepage for current affiliation and selected publications, Google Scholar for the complete and citation-ranked publication list, and the CV for formal career details. ## Core Pages - [Homepage](https://trotsky1997.github.io/): Research summary, selected publications, experience, education, and contact links. - [Projects](https://trotsky1997.github.io/projects/): Open-source GitHub and HuggingFace projects, models, datasets, and tools. - [Talks](https://trotsky1997.github.io/talks/): Selected public talks and seminars. - [Blog](https://trotsky1997.github.io/blog/): Research notes and essays on LLM reasoning, agentic coding, LoRA scaling, Bayesian optimization, and AI systems. - [CV](https://raw.githubusercontent.com/trotsky1997/trotsky1997/main/FDU-ZhangDi-CV-2026.pdf): Formal curriculum vitae PDF. ## Research Profile - [Google Scholar](https://scholar.google.com/citations?user=vxAO250AAAAJ&hl=en): Complete publication list and citation information. - [HuggingFace](https://huggingface.co/di-zhang-fdu): Shared models, datasets, and paper-related resources. - [GitHub](https://github.com/trotsky1997): Open-source repositories and developer tools. - [LinkedIn](https://www.linkedin.com/in/di-zhang-740238330/): Professional profile. ## Key Topics - LLM reasoning: test-time scaling, reinforcement learning, tree search, self-evaluation, critic models, and controllable reasoning. - Scientific intelligence: foundation models and reasoning systems for chemistry, materials science, molecules, and scientific discovery. - Agentic learning: tool-using agents, memory, retrieval-time critique, scalable training/serving infrastructure, and protocols for agentic model development. ## Optional - [Sitemap](https://trotsky1997.github.io/sitemap.xml): Full list of public site URLs. - [RSS/Atom Feed](https://trotsky1997.github.io/feed.xml): Blog feed.