Xinhe Gao

EDUCATION

College / University

Shanghai Jiao Tong University

Highest Degree

Bachelor of Engineering

Major Subjects

Biomedical Engineering

Country

China (P.R.)

Lab Experience

Behavioral task design and programming in MATLAB;
Macaque behavioral training and data acquisition;
Python and PyTorch; deep learning;
EEG preprocessing and analysis; MRI image segmentation;
PCR and qPCR; DNA extraction and sequencing-library preparation; biosignal acquisition

Projects / Research

  • 2025 – 2026: Developed macaque behavioral tasks and recurrent neural network models to study the neural mechanisms of flexible cognition; Okazawa Lab, Chinese Academy of Sciences
  • 2025 – 2026: Developed a contrastive-learning and teacher-distillation model for emotion recognition using low-channel wearable EEG; Center for Brain-like Computing and Machine Intelligence, Shanghai Jiao Tong University
  • 2024 – 2025: Developed a prompt-based Mixture-of-Experts model for EEG emotion recognition; co-authored a paper accepted to IEEE ICASSP 2026; Center for Brain-like Computing and Machine Intelligence, Shanghai Jiao Tong University
  • 2023: Contributed to a personalized nucleic-acid diagnostic project for endometrial cancer through DNA extraction, amplification, and sequencing-library preparation; NABME Lab, Shanghai Jiao Tong University

Scholarships / Awards

2025: SJTU-SIP Scholarship for Overseas Study
2024: Excellent Scholarship Grade B, Shanghai Jiao Tong University
2023: Excellent Scholarship Grade C, Shanghai Jiao Tong University

SCIENTIFIC INTERESTS AND GOALS

I am interested in how neural population dynamics implement computations for flexible cognition, and whether these computations generalize across tasks and individuals. I’m drawn to this because humans adapt rapidly to changing situations, yet do so in individual-specific ways; I want to identify what is shared versus idiosyncratic in the underlying neural codes. During my graduate training, I hope to explore diverse approaches to these questions and strengthen my theoretical and methodological foundations. Ultimately, I aim to understand how the brain supports adaptive behavior while accounting for both general principles and meaningful individual differences.