CV

Education

• B.S. Candidate in Computer Science, Fudan University, Shanghai, China, Sep. 2023 - Jul. 2027 (Expected)
• Exchange Student in Computer Science, University of Texas at Austin, Austin, Texas, Aug. 2025 - Dec. 2025

Research Experience

• Sep. 2024 - Jun. 2025: Research Assistant
  • Fudan University Natural Language Processing Group
  • Project: Research on ChatGPT-o1 model reproduction and reflection ability improvement
  • Supervisor: Professor Xuanjing Huang
  • Duties: Constructing, evaluating, and optimizing reflection datasets; synthesizing and training self-critic data based on Llama3.1-8b-instruct; generating diverse reflection process data using tree search reasoning and reverse reasoning strategies
• Oct. 2024 - May 2025: Research Focus
  • MagicLab, Fudan University
  • Project: Learning Risk Map for Autonomous Driving in Partially Observable Environments
  • Supervisor: Wenchao Ding
  • Duties: Engineering risk field representations using spatiotemporal modeling; developing traffic scene generation with diffusion models; designing lightweight neural networks for risk prediction
  • Status: Research submitted to IEEE Robotics and Automation Letters (RAL)

Skills

• Machine Learning
  • Completed all lectures and labs of ML2022 by Hung-yi Lee
  • Proficient in various ML algorithms and techniques
• Deep Learning
  • CNN, RNN, LSTM, Transformer, GAN, Diffusion Models
  • Strong command of PyTorch framework
• Programming Languages
  • C, C++, Python, Java, LaTeX
• Specialized Areas
  • AI-Driven Autonomous Driving: planning, prediction, and decision making
  • Computer Vision: Multi-view Geometry, 3D Reconstruction (SfM/Stereo), Camera Calibration, Object Detection & Segmentation, Optical Flow
  • Data Structures & Algorithms: Completed Data Structure (Honor) course by Weiwei Sun
• Languages
  • Chinese (Native), English (Fluent)

Projects

• LCDP-Sim: Language-Conditioned Diffusion Policy (Dec. 2025 - Present)
  • Independent Developer, Austin, Texas
  • Developed an end-to-end Vision-Language-Action (VLA) system utilizing Diffusion Policy
  • Integrated CLIP text encoder and U-Net-based DDPM/DDIM architecture for high-fidelity action generation
  • Implemented Action Chunking (16-step prediction) to mitigate error accumulation
  • Built complete pipeline for data collection, distributed training, and closed-loop evaluation in ManiSkill2
• MapNavigation (Dec. 2024 - Present)
  • Independent Developer
  • Long-term maintained project combining OpenStreetMap data with Gaode Maps API
  • Features: hybrid point selection, detailed route information, support for different road types
  • Repository: https://github.com/16yunH/MapNavigation
• NeuralStyle (Jun. 2025 - Present)
  • Independent Developer
  • Modular neural style transfer toolkit with batch processing capabilities
  • Interactive web interface and configurable pipeline for experimentation
  • Repository: https://github.com/16yunH/NeuralStyle

Extracurricular Activities

• Core Member, China Undergraduate Mathematical Contest in Modeling (CUMCM), Sep. 2024
• Core Member, Fudan University’s team of aid education in Yudu, Jiangxi, Jan. 2024 - Feb. 2024
• Member, Fudan Piano Association, Oct. 2023 - Present
• Keyboard Player, Fudan Musicians Alliance, Sep. 2024 - Present

Honors & Awards

• 2024: Finalist, Water, sanitation, and hygiene for the prevention and care of neglected tropical diseases (Geneva, Switzerland)
• 2025.05: Excellent Work Award, The 5th Meituan Business Analytics Elite Competition
• 2024.12: 3rd Prize, China Undergraduate Mathematical Contest in Modeling (CUMCM)
• 2023: Finalist, Full-stack AI development engineer skills training by NVIDIA

Publications

Learning Risk Map for Autonomous Driving in Partially Observable Environments

Hong, Y., Ding, W. et al. (2025). "Learning Risk Map for Autonomous Driving in Partially Observable Environments." IEEE Robotics and Automation Letters (RAL). (Under Review)