Summary

B.Eng. in Automation student at Tianjin University, School of Future Technology, an elite undergraduate college. Trained through the Intelligent Machine Platform honors track, with two years of shared mathematics, physics, and engineering foundations before selecting Automation. Research interests center on computational neuroscience, cognitive neuroscience, and Neuro-AI, grounded in robotics, control, and reproducible scientific computing.

Education

• B.Eng. in Automation, Intelligent Machine Platform Honors Track

  Present
  Tianjin University, School of Future Technology

  GPA: Overall 3.85/4.0; Junior specialization 3.98/4.0

  Courses: Overall standing: rank 8/100, weighted score 91.54, GPA 3.85/4.0, Junior specialization standing: rank 1/8, weighted score 96.55, GPA 3.98/4.0, Elite first-two-year training in mathematics, physics, and engineering fundamentals, Brain and Cognition, Intelligent Medical Signal Processing, Optimization-based Machine Learning, Deep Learning, Pattern Recognition and Brain-like Intelligence, Equations of Mathematical Physics, Theory of Motor, Numerical Computational Method, Circuit Principles, Analog Circuits, Digital Circuits, Principles of Programming, Selected grades: Numerical Computational Method 99, Fundamental Physics 99, Equations of Mathematical Physics 98, Mathematical Analysis 95, Principles of Programming 95, Probability and Mathematical Statistics 94, Circuit Principles 94, Advanced Linear Algebra 93, Analog Circuits 93, Automatic Control 92, Discrete Mathematics 92

Work Experience

• Visiting Undergraduate Research Assistant

  2026-07 - 2026-09
  Shanshan Qin Lab, Shanghai Jiao Tong University

  Upcoming summer research visit as an undergraduate research assistant.

  • Summer research visit at Shanghai Jiao Tong University.

Skills

Publications

• Nonholonomic Narrow Dead-End Escape with Deep Reinforcement Learning

  2025
  Proceedings of the 2025 9th International Conference on Computer Science and Artificial Intelligence, ACM

  Conference paper on deep reinforcement learning for nonholonomic robots escaping narrow dead-end environments.

  View Publication

Portfolio

• EEG Feature Enhancement and Single-Trial Classification
  View Project
• EEG Time-Frequency Analysis with OpenBMI
  View Project
• Deep Learning Exp2: MNIST Noise Robustness
  View Project
• Q-RIS-UAV Secure Energy Optimization
  View Project
• SAGIN ML: Satellite Link Optimization
  View Project
• MNIST MLP Experiment Diagnosis
  View Project

Languages

• Chinese

  Native
• English

  Proficient

Interests

• Research

  Computational neuroscience, Cognitive neuroscience, Neuro-AI, Predictive processing, World models, Embodied cognition