Yi He

Undergraduate Student · Mathematics and Applied Mathematics

Cuiying Honors College, Lanzhou University
National Program for Top Talents in Basic Sciences

Member of Gansu Association of Artificial Intelligence

Yi He

About Me

I am currently a third-year undergraduate student pursuing Mathematics and Applied Mathematics at Cuiying Honors College, Lanzhou University. My research focuses on the intersection of mathematics and artificial intelligence.

My primary research interests lie in AI × Science, Deep BSDE Method, Bioinformatics, and Computational Algebra.

I have led or participated in multiple interdisciplinary research projects, including the development of spherical BSDE algorithms, the construction of the DNA methylation prediction model and interpretability framework Bio-Prism, and the application of point cloud equivariant networks in part representation recognition.

Email: heyi2023@lzu.edu.cn

Education

University of California, Berkeley

Jan. 2026 - May. 2026
Visiting International Student (Semester Study Abroad)
  • Selected Courses: CS 61B (Data Structures), Introduction to Neurotechnology
  • Focus: Computer Science & Applied Mathematics
  • Affiliation: Member of Open Computing Facility (OCF)

Lanzhou University

Sept. 2023 - Present
B.S. in Mathematics and Applied Mathematics, Cuiying Honors College
  • GPA: 4.02 / 5.0
  • Rank: Top 5%
  • Awards: 2025 MCM/ICM Finalist (Top 2%)
  • Extracurricular: Captain of the Swimming Team (School of Mathematics and Statistics); Captain of the Track and Field Team (Cuiying Honors College)

Skills

Programming Languages

Python (PyTorch)

C & C++

MATLAB

Development Tools

VS Code & SSH

Linux & Conda

Algorithm Foundations

Numerical Computation

Monte Carlo Methods

FFT & IFFT

Authoring Tools

LaTeX

Markdown

HTML & CSS

Other Skills

AutoDL Cloud Computing

Web Deployment

Leading Research Experience

Deep BSDEs: Solving Spherical Fokker-Planck and Feynman-Kac Equations

Lanzhou University · Prof. Weihua Deng's Group (Distinguished Young Scholar); Collaborative Advisor: Dr. Heng Wang

Developed a numerical solution method for high-dimensional partial differential equations under spherical geometric constraints, combining deep learning with backward stochastic differential equations (BSDEs) to address the curse of dimensionality in traditional methods.

Lead Researcher AI for PDE Deep BSDE Spherical Geometry
BSDE Research Cover

MEDNA-DFM Model and XAI method: CAD & CWGA

City University of Hong Kong · Dr. Tianchi Lu's Group

Developed a DNA methylation prediction framework based on Dual-View FiLM-MoE architectures, and proposed the CAD & CWGA interpretability method, emphasizing internal mechanism analysis as a necessary condition for interpretability.

📄 Paper: arXiv:2602.22850 ✨ Web: MEDNA-DFM-Web 📌 Status: Under Review at Advanced Science
Lead Researcher (1st Author) Bioinformatics MEDNA-DFM CAG & CWGA Explainable AI
Bio Research Cover

Collaborative Research Experience

Fixed points of orientation-preserving full transformation

Lanzhou University · Prof. Wenting Zhang's Group; Collaborative Advisor: Yang An, M.S.

Implemented computations for various semigroup mappings and fixed point calculations, with statistical analysis to propose novel patterns.

📌 Status: Under Review at Discrete Applied Mathematics
Code Member Computational Group Theory Combinatorics
Computational Algebra Cover

PathMoG : A Pathway-Centric Modular Graph Network for Multi-Omics Cancer Survival Prediction

City University of Hong Kong · Dr. Tianchi Lu's Group

Contributed to the core model design by introducing Feature-wise Linear Modulation (FiLM) as a key architectural innovation.

📌 Status: Under Review at IEEE Journal of Biomedical and Health Informatics
Model Design Member Survival Prediction Multi-Omics Fusion
PathMoG

HBGSA: Hydrogen Bond Graph with Self-Attention for Drug-Target Binding Affinity Prediction

City University of Hong Kong · Dr. Tianchi Lu's Group

📌 Status: Under Review at Knowledge-Based Systems
Core Member GNN Hydrogen Bonds Drug-Target Affinity
HBGSA

Industrial Part Representation and Assembly

Beijing Normal University-Hong Kong Baptist University United International College · Prof. Tieyong Zeng's UIC Path Group; Provincial Key Project

Adopted point cloud-level contrastive learning and equivariant neural network approaches to transfer PointNet for part representation learning.

Core Member PointNet Contrastive Learning REQNN
3D Research Cover

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Ask "Ver" (My AI Assistant)

I developed a personalized AI assistant Ver based on Dify, which has been trained on all my research notes and project codes.