Education

Ph.D in Computer Science

University of Toronto, Canada, From September 2024 (Deferred due to visa)

Working with Prof. Ashton Anderson

M.Eng. Electrical and Computer Engineering

University of Toronto, Canada, September 2021 - November 2023

Emphasis: Computer Engineering, CGPA: 3.91/4.0

B.S. Computer Science and Technology

Xi'an Jiaotong University, China, September 2017 - July 2021

Selected into Honors Science Program (Computer Science), GPA: 91.0/100

Pre-university Education of the Honors Youth Program of Xi'an Jiaotong University

Qian Xuesen Honors College, Xi'an Jiaotong University, September 2015 - July 2017

Tianjin Nankai High School, Tianjin, China

Working Experience

Summer Intern

Computational Social Science Lab, University of Toronto, June 2023 - October 2023

Chess Concepts Mastery in Maia: A Quantitative Study with Dr. Ashton Anderson

  • Analyzed the level of chess knowledge acquired by Maia using linear probing methods
  • Applied non-negative matrix factorization to discover chess concepts
  • Provided quantitative evidence about knowledge acquisition in different levels of Maia

Research Intern

Canadian Pension Plan Investment Board (CPPIB), September 2022 - April 2023

Master's Thesis: Multi-horizon Time Series Forecast for Security Forward Return under the supervision of Prof. Yuri Lawryshyn

  • Conducted large-scale data pre-processing and dimensionality reduction for stock forward return
  • Implemented Seasonal ARIMA model and adapted Seq2Seq model for multi-horizon prediction
  • Replicated Temporal Fusion Transformer model for prediction and evaluated feature contributions

Machine Learning Research Intern

Cloud & Smart Industries Group, Tencent Holdings Ltd., June 2020 - September 2020

Deep Knowledge Tracing and Educational Data Analysis

  • Assisted research on Knowledge Tracing problem for student academic performance prediction
  • Reproduced DKVMN (Dynamic Key-value Memory Networks) for Knowledge Tracing on localized data
  • Implemented Graph Neural Network for node-level classification over knowledge graph