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I am an undergraduate student in the joint program of TU Delft and Eindhoven University of Technology, with interdisciplinary training in computer science, electrical engineering, and applied physics.
I am currently studying in a joint undergraduate program between Delft University of Technology and Eindhoven University of Technology. My academic background spans computer science, electrical engineering, and applied physics, and I am especially interested in research at the intersection of machine learning and real-world engineering systems.
My current interests include AI for Science, foundation models, analog circuit design and optimization, and the use of modern machine learning methods to model, optimize, and automate complex physical and engineering systems.
I am actively seeking research and collaboration opportunities related to AI for Science, foundation models, semiconductor design workflows, and AI-driven analog circuit optimization.
Applying machine learning and foundation models to scientific and engineering problems with strong physical structure.
Interested in large language models, multimodal models, and their use in scientific discovery, reasoning, and engineering workflows.
Exploring AI-driven methods for analog circuit modeling, optimization, and automation across design and verification stages.
Bridging intelligent algorithms with real-world hardware, semiconductor workflows, and physical systems.
Mar 2026 – Present · Shenzhen
Research on LLM for Recommendation (LLM4Rec) under the supervision of Prof. Fangyuan Zhang.
Jul 2025 – Sep 2025 · Shanghai, China
Studied semiconductor IC design workflows and EDA toolchains, including schematic design, pre-layout simulation, layout verification, DRC/LVS, and MPW-oriented tape-out preparation.
Sep 2023 – Feb 2024 · Beijing, China
Conducted an independent environmental data research project on the relationship between PM2.5 air pollution and respiratory disease incidence, using Python for exploratory data analysis, statistical inference, and visualization.
Current research work on applying large language models to recommendation systems and related intelligent retrieval settings.
Documentation and technical notes on IC design flow, DRC/LVS, PDK concepts, and tape-out preparation.
Built structured datasets and analyzed the association between PM2.5 exposure and respiratory health outcomes.
B.Sc. in Computer Science, Electrical Engineering and Applied Physics(triple degree program) · Sep 2024 – Jun 2028
B.Sc. in Computer Science, Electrical Engineering and Applied Physics(triple degree program) · Sep 2024 – Jun 2028
I am open to research collaborations, academic discussions, and internship opportunities in AI for Science, foundation models, recommendation systems, and AI-driven circuit design.
Email: vipinapple986@gmail.com
LinkedIn: Weiping Yan
GitHub: appleweiping