Publications & Preprints
1
A Markovian Traffic Equilibrium Model for Ride-Hailing
2
Optimizing Urban Electric Vehicle Charging and Battery Swapping Infrastructure: A Location-Inventory-Grid Model
3
Dynamic Carbon Intensity Indicator (CII) Management in Stochastic Tramp Shipping Market
4
Adding Runs of Modular Autonomous Vehicles with Skip-Stop Strategy Using Deep Reinforcement Learning
5
Charting the Uncharted: A Multi-Attribute Ship Clustering Model for Identifying Dark Shipping of Sanctioned Oil Using AIS Data
Research Experience
Optimal Control in Battery Swapping Stations
March 2026 – Present
Prof. David Yao · Columbia University
- Constructed a continuous-time MDP model for optimal control in battery swapping stations
- Proved the optimality of the threshold-based policy
Markovian Traffic Equilibrium for Ride-Hailing
Jun 2025 – Present
Prof. Chiwei Yan · University of California, Berkeley
- Proved equilibrium existence via fixed-point theory; established uniqueness and MSA convergence for directed cycle networks
- Conducted all numerical experiments on Sioux Falls and Chicago sketch networks (up to 933 nodes, 300K vehicles)
- Designed ablation studies on myopic vs. forward-looking drivers and congestion-aware pricing
Modular-Vehicle Transit with DRL
Jan 2025 – Jul 2025
Prof. David Z.W. Wang · Nanyang Technological University
- Designed an MDP-based optimization model integrating modular and regular transit
- Developed a reinforcement learning framework reducing costs by 11.40% vs. rolling-horizon baseline
EV Charging Infrastructure
Oct 2024 – Present
Prof. Wei Qi · Tsinghua University
- Integrated grid regulation with location and inventory management of battery swap stations
- Approximated the system via continuous models; under minor revision at TR Part E
Carbon Intensity Indicator (CII) Management
Apr 2024 – Present
Prof. Xiwen Bai · Tsinghua University
- Built stochastic optimization model for tramp fleet deployment under IMO CII constraints
- Proved policy paradox; derived VSS and EVPI bounds; under minor revision at TR Part A
Dark Shipping Detection via AIS Data
May 2024 – Oct 2024
Prof. Xiwen Bai · Tsinghua University
- Developed multi-level K-means algorithm to detect illegal voyages, correctly classifying 80%+ dark ships
- Improved classification accuracy by 28% over baseline using AIS trajectory features
Education
B.Eng. Industrial Engineering
3.9
/ 4.0
GPA
Statistics & Probability: Probability Theory (A) · Linear Regression (A) · Multivariate Analysis (A-) · Nonparametric Statistics (A)
Optimization & Computing: Deterministic Models (A) · Applied Stochastic Models (A) · Convex Optimization (P) · Dynamic Programming & Reinforcement Learning (A+) · Machine Learning (A)
Economics & Finance: Microeconomics (A) · Macroeconomics (B+) · Political Economy (A+) · Engineering Economy (A-) · Corporate Finance (B+)
Optimization & Computing: Deterministic Models (A) · Applied Stochastic Models (A) · Convex Optimization (P) · Dynamic Programming & Reinforcement Learning (A+) · Machine Learning (A)
Economics & Finance: Microeconomics (A) · Macroeconomics (B+) · Political Economy (A+) · Engineering Economy (A-) · Corporate Finance (B+)
Honors & Awards
Scholarship for Scientific and Technological Innovation Excellence
Fall 2024–2025
Tsinghua University
Scholarship for Comprehensive Excellence
Fall 2022–2023
Tsinghua University
Outstanding Student Leader
Fall 2022
Tsinghua University
Skills & Languages
Programming
Python · MATLAB · C++ · R · SQL
English
TOEFL 108
GRE V158 / Q170 / AW4.0
GRE V158 / Q170 / AW4.0