CV
Education
- Ph.D. Texas A&M University, 2020
- M.S. Rice University, 2015
- B.S. Tongji University, 2012
Work experience
- 2024-present: Project Lead Environment (GHG/energy systems modeller)
- Modelling Toronto’s 2040 net-zero GHG emissions pathways to drive policy and test actions for citywide emissions reductions
- 2022-2024: Rising Stars in Clean Energy Postdoctoral Fellow
- Modeling life cycle fleet electrification pathways for light-duty vehicles, to meet climate targets
- 2021-2023: Postdoctoral Fellow
- Developing Carbon Monitor Cities: A near-real-time daily global CO2 emission dataset at city level
- Developing OpenPit-AI
- Studying low-carbon transitions of cities in China
- Investigating city-level carbon neutrality pathways in collaboration with Alibaba Group
- 2019-2020: Teaching Assistant
- Texas A&M University
- Taught and designed lab sections for GIS and remote sensing courses.
- 2016-2019: Research Assistant
- Texas A&M University
- Developed image processing and feature detection software for an agricultural radar system.
- Quantified carbon sequestration capabilities of genetically modified plants.
- Funded by the Department of Energy of United States.
- 2015-2016: Shaanxi Geology and Mining Group
- Developed geophysical data processing workflows and drafted project proposals.
- 2014-2014: Halliburton Landmark Graphics Corp
- Developed software workflows for DecisionSpace Geosciences and Well Seismic Fusion
- 2012-2013: Research Assistant
- Tongji University
- Collected and processed data for an ocean bottom seismometer array
- Studied the characteristics of microseism
Skills
- Scientific Programming and Modeling
- Python Matlab R SQL C++
- Data Science
- Geodatabase
- Machine Learning
- Big Spatio-temporal Datasets
- Geographic Information Systems
- Remote Sensing (Satellite, Radar)
Certificates
- Machine learning (Stanford University online, 2015)
- Deep learning for computer vision (Nvidia, 2020)
Publications
Talks
Understanding Climate-Glacier Dynamics in the Karakoram Himalaya using Debris-Flux and Ablation Modeling
Poster at American Geophysical Union Fall Meeting, San Francisco, California
Greenhouse Gas Emission Reduction for Mining Fleets via Smart Dispatching Based on Deep Reinforcement Learning
Presentation at Annual Convention of the Canadian Institute of Mining, Metallurgy and Petroleum (CIM), Vancouver, BC, Canada
Near-Real-Time Estimates of Daily Fossil-Fuel CO2 Emissions from Cities Worldwide
Online Presentation and Poster at Metrology for Climate Action Workshop 2022, Online
Carbon Monitor Cities, Near-Real-Time Monitoring of Daily Fossil-Fuel CO2 Emissions from Cities Worldwide
Oral Presentation at International Conference on Industrial Ecology (ISIE 2023), Leiden, Netherlands
Smart Mining Fleet Dispatching System to Reduce Greenhouse Gas Emissions Using Deep Reinforcement Learning
Poster Presentation at International Conference on Industrial Ecology (ISIE 2023), Leiden, Netherlands
Modelling Toronto’s Net Zero Strategy Using LENZ Modelling Suite
Oral Presentation at EMH (Energy Modelling Hub) 2024 Annual Forum, Ottawa, Canada