Kun-Ying Lee (李坤應)
Undergraduate Student at Tsinghua University.
I am a first-year undergraduate student in the Department of Computer Science and Technology at Tsinghua University.
Currently, I am a research intern at the MARS Lab at the Institute for Interdisciplinary Information Sciences (IIIS), advised by Prof. Hang Zhao. My research interests lie broadly in Robotics and Embodied AI.
Additionally, I am a member of the TH-MOS (Tsinghua Master of Soccer) robot soccer team, working on Gait Control algorithms for competitive robots.
Outside of research, I am a passionate pianist and a member of the Tsinghua University Clavier Team. I also enjoy playing frisbee with the CS department team.
News
Publications
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Mathmedia, Vol. 49, No. 2, 2025 -
64th National Science Fair, Tainan City, Taiwan, Aug 2024
Projects
Human Resource Machine (Oct. 2025)
Developed a desktop reimagining of the puzzle game “Human Resource Machine” using C++17, SFML 3, and ImGui-SFML.
Logisim Based RISC CPU Implementation (Jun. 2025)
- Designed a 32-bit single-cycle RISC CPU using Logisim Evolution.
- Implemented modular components including ALU, Instruction Decoder, Program Counter, and Register File.
- Supported R-type (Arithmetic/Logical) and I-type (Immediate/Load/Control) instructions.
UAV-Based Food-Delivery Routing For Tsinghua University (Aug. 2025)
- Applied A-star algorithm to generate safe and efficient UAV routes that avoid obstacles and follow constraints
- Developed a web-based simulation interface that visualizes deliveries in real time
DualBot Explorer Project Development (Feb. 2023)
Developed a dual-agent conversational AI system employing Langchain, GPT-4o, FAISS and Streamlit. Implemented three interaction modes: Debate Mode, Paper Digest Mode and Peer-review Simulation Mode.
EcoTracker Android App Development (Apr. 2024)
Co-invented (responsible for the back-end part) a comprehensive mobile app that helps users track and analyze their carbon footprint across various aspects, from consumption patterns to transportation choices. Powered by AI, the app provides personalized, actionable recommendations to help users adopt more sustainable habits.