CV
You can download my CV (last updated May 2026)
Education
- Ph.D. in Mechanical Engineering, University of Michigan, 2028 (expected)
- M.S. in Computational Materials Science and Engineering, Carnegie Mellon University, 2022
- B.E. in Materials Science and Engineering, South China University of Technology, 2021
Work experience
- Summer 2023: Machine Learning Summer Internship
- Redesign Science
- Duties included: Improving Machine-Learned Collective Variables with Energy-based Path Construction
- Supervisor: Dr. Andreas Mardt
- Summer 2022 and Spring 2023: Research Assistant
- Carnegie Mellon University
- Duties included: Developing AI for molecule property prediction
- Supervisor: Prof. Amir Barati Farimani
- Spring 2023: Global Alpha Researcher
- Trexquant Investment LP
- Duties Included: Applying Machine Learning for profitable strategies using trading signals
Publications
Talks
TransPolymer: a Transformer-based Language Model for Polymer Property Predictions
Invited Talk at Brown University, CRUNCH Group Seminar, Online
CLOUD: A Scientific Foundation Model for Crystal Property Prediction
Poster at MICDE Scientific Foundation Model Conference, Ann Arbor, Michigan
CLOUD: A Scientific Foundation Model for Crystal Property Prediction
Poster at Molecular Machine Learning Conference, Montreal, Quebec
CLOUD: A Scalable and Physics-Informed Foundation Model for Crystals
Invited Talk at AI for Chemistry & Materials Webinar Series, Online
Introduction to Scientific Foundation Models
Tutorial at U-M Knowledge-Guided Machine Learning (KGML) Workshop: Leading the New Paradigm of AI for Science, Ann Arbor, Michigan
CLOUD: A Scalable and Physics-Informed Foundation Model for Crystals
Lightning Talk at Vector workshop on Foundation Models for Science, Toronto, Ontario
CLOUD: A Scalable and Physics-Informed Foundation Model for Crystals
Poster at GRC AI for Materials, Energy, and Chemical Sciences, Galveston, Texas
Autonomous Discovery of Superconducting Materials Using ScienceClaw
Demo at ClawCon, Ann Arbor, Michigan
Blog Posts
Professional Services
- Reviewer: NeurIPS’23-25, ICLR’24-26, ICML’24-25, ICLR ML4Materials Workshop’23, ICML SPIGM Workshop’23-24, ICML AI4Science Workshop’24
Skills
- Computational Skills
- Programming Languages: Python, SQL, MATLAB, R
- Frameworks: PyTorch, Tensorflow, Keras
- Developer Tools: Google Cloud Platform, PyCharm, VS code, Visual Studio, Docker, Git
- Libraries: pandas, NumPy, Matplotlib, sklearn, Huggingface, RDKit
- Deep Learning Model: Transformer, DDPM, Score-based Generative Model, LSTM, CNN
- Agentic AI: Claude Code, Model Context Protocol, OpenClaw
- HPC & Distributed Computing: PBS / SLURM, MPI, ezpz
- Computation and Simulation Tools: Molecular Dynamics, DFT
- Experimental Skills
- Synthesis Skills: organic synthesis of small molecules and COFs, purification skills like column chromatography and Soxhlet purification
- Characterization Techniques: FTIR, UV-vis spectrophotometry, XRD, SEM, XPS
- Electrochemical Experimental Skills: CV, DPV, chronoamperometry
- Additional Skills
- Spoken Languages: English (fluent), Chinese (native)