CV
Education
The Ohio State University, Columbus, Ohio
PhD in Civil Engineering (Structural Engineering), expected December 2027
Minor in Computer Science and Engineering
Advisor: Prof. Abdollah Shafieezadeh
National University of Singapore, Singapore
MEng in Civil Engineering, June 2023
Thesis: Reliability Analysis of Offshore Structures
Advisor: A/Prof Ying Min Low
Southeast University, Nanjing, China
BEng in Civil Engineering, June 2022
Research & Data Science Experience
Electricity Price Forecasting — January 2025 to February 2026
- Developed a causal graph-informed temporal convolutional network for retail electricity price forecasting, achieving 3.08% MAPE.
- Built end-to-end Python pipelines combining more than ten years of daily market data, over two million retail offers, wholesale forward prices, and contract attributes.
- Produced interpretable insights into key drivers of price variation using causal feature representations and model diagnostics.
Retail Renewable Energy Premiums Analysis — August 2024 to August 2025
- Built a matching pipeline connecting renewable and non-renewable retail electricity offers, creating more than 120,000 matched contracts.
- Applied gradient boosting and SHAP to quantify drivers of renewable premiums across utilities, time periods, and contract attributes.
- Identified a 7.66% average renewable premium and a $44/MWh wholesale price threshold associated with supplier margin compression.
AI Data Centers and Grid Resilience — November 2025 to April 2026
- Built a county-level panel dataset covering 67 Florida counties from 2014 to 2025, integrating outage records, 17 hurricane events, socioeconomic data, and geocoded data center infrastructure.
- Engineered spatial-temporal features and applied difference-in-differences and event-study methods to quantify impacts on peak outage rates and recovery duration.
Causal Machine Learning for Decision Optimization — August 2024 to November 2025
- Developed uncertainty-aware causal forest models for treatment optimization under heterogeneous effects.
- Designed evaluation frameworks that improved decision performance over baseline methods.
Technical Skills
- Programming: Python, R, SQL, MATLAB
- Machine Learning: PyTorch, scikit-learn, graph neural networks, interpretable machine learning
- Statistical Modeling: causal inference, time-series forecasting, uncertainty quantification, discrete choice modeling, Bayesian modeling
- Data Engineering & Analysis: pandas, NumPy, large-scale data pipelines, panel data, NLP/text mining, geospatial-temporal integration
- Tools: Git/GitHub, Jupyter, LaTeX, Overleaf
Selected Presentations
- Understanding and Addressing Energy Affordability in the United States Workshop, National Academies, Washington, D.C., February 2026 — selected and funded by the National Academies.
- APPAM Fall Research Conference, Seattle, Washington, November 2025.
- CEGE Graduate Research Expo, Columbus, Ohio, October 2025 — Best Communication Award.
- College of Engineering Graduate Research Symposium, Columbus, Ohio, October 2025 — Best Presentation Award.
- American Causal Inference Conference, Detroit, Michigan, May 2025.
- USAEE/IAEE North American Conference, Baton Rouge, Louisiana, November 2024.
Leadership & Service
- Graduate Student Ambassador, CEGE, The Ohio State University, October 2025-present.
- Advisor, International Undergraduate Future Orientation at OSU, August 2024-present.
- Advisor, Research Experiences for Undergraduates Site, OSU, May-July 2024.
- Volunteer, Central Ohio Mini Bridge Competition, 2026.