CV

Basics

• Boyang YU
• Peking University, Beijing, China, 100871

• Email: maverickyouknowwho@gmail.com

  Tel: +86-18519644705

Education

• 09/2020 – 08/2022: Peking University, Beijing, China
  • Bachelor of Science in Physics, School of Physics
  • Completed coursework for a Bachelor of Science in Physics for the first two years.
  • Made a decision to transition to Computer Science and switched majors in 09/2022.
• Since 09/2022: Peking University, Beijing, China (Graduated in fall 2025)
  • Bachelor of Science in Computer Science, School of Electronics Engineering and Computer Science.
  • GPA: 3.60/4.00

Research Experiences

• 05/2023 - Present: Prof. Libin Liu’s group, PKU, China
  • Projects:
    • Proficient in commonly used kinematic algorithms including FK/IK, motion interpolation, and character physics control.
    • Generating stylized and biologically plausible motion within a physics-driven environment:
      • Implemented a new fatigue state action generation under 3-CC control using GAN-based reinforcement learning methods on Isaacgym.
      • Currently engaged in refining AdaptNet for motion style transfer using GANs, integrating data generated from videos.
    • Collaborated on muscle-driven motion generation and volumetric muscle simulation.
• 07/2023 – 09/2023: VCL (Visual Computing and Learning) Lab Summer School, PKU, China
  • Projects:
    • Successfully reproduced DeepMimic physics control deep reinforcement learning algorithm.

Selected Course Projects

• Achieve Real-time Motion Control in Kinematics/Physics Simulation:
  • Utilized motion matching and interpolation smoothing in a Physics Simulator with PD control, achieving top score.
• Fine-Tuning the Segment-Anything Model and Integrating a Downstream Classifier:
  • Fine-tuned the segment-anything model on medical CT dataset, achieving high accuracy in organ type identification.

Language Skills

• 06/2023: TOEFL R: 30 L: 27 S: 22 W: 21 Total: 100

Selected Awards

• Excellent Study Award from Peking University
• Wanglaoji Enterprise Scholarship
• Second-class scholarship for freshmen

Technical Skills

• Coding: C++, Python (including Pytorch)
• Machine learning: reinforcement learning, machine learning theory
• Graphics: character animation, physics simulation, rendering, NeRF
• Robotics: proficient in robot kinematics and dynamics, motion planning and control policy, simulation
• Generative models: Variational Autoencoders (VAE), Generative Adversarial Networks (GAN)

Download the PDF version of my CV here.