I work with large market datasets to understand how prices, promotions, market structure, and mobility relate to demand and market outcomes, then translate that evidence into forecasts, scenarios, and decision-support tools. My work spans 6.6M retail scanner records, 8.68M historical market records, mobility traces, input-output tables, customs micro-data, and geospatial rasters.
Retail pricing decisions
I estimate demand response, simulate price and promotion scenarios, and optimize profit under cost, inventory, and margin constraints. Core asset: Pricing and Promotion Decision Engine.
Commodity prices and market integration
I use high-frequency wholesale prices and smartphone-based mobility data to study how passenger connectivity, rather than freight costs, shapes spatial price dispersion across Chinese cities. Core asset: HSR and Market Integration paper.
Trade-cost shocks and local multipliers
I build quantitative spatial models to measure how trade-cost shocks propagate through domestic production networks, local absorption, and non-tradable demand. Core asset: Trade shock paper.
Research and Tools
Built on 6.6M rows of Dominick's scanner data: log-log fixed-effects demand estimation, price and promotion counterfactuals, constrained profit optimization under cost and margin inputs, and A/B power calculations, deployed as a live Streamlit app.
Built an auditable historical price system from 8.68M market records: rolling forecasts, a validation-frozen price-risk signal, and explicit fallbacks or no-go decisions when out-of-sample evidence did not support a stronger product claim.
Constructed a panel with 3.99 million city-pair-month observations from daily wholesale prices and mobility indices. Estimates indicate HSR connectivity lowers intercity price dispersion by about 2% on average and up to 5% in short-haul markets.
Built a multi-sector quantitative spatial model for 31 Chinese provinces calibrated to MRIO, ICIO, and Customs micro-data. Identifies the own-trade share as the structural organizing statistic for multiplier heterogeneity, with inland inward-oriented economies amplifying external shocks through non-tradable service demand.
Experience
2025 - Present
Live demand-estimation and constrained-optimization tool on 6.6M rows of scanner data, deployed as a Streamlit app.
2026 - Present
Historical market-data system for rolling forecasts, price-risk signals, and transparent model-governance decisions across 117 cities and 30 vegetables.
2024 - Present
Quantitative spatial modeling and shift-share IV estimation on Chinese trade and production data; model-implied provincial GDP multipliers from 0.30 to 1.02.
2022 - 2025
Linked large-scale price and mobility data to evaluate transport infrastructure effects on market integration.
2023 - 2024
Silver Medal on Home Credit Credit Risk Model Stability (LightGBM/CatBoost, Polars ETL); Bronze on ICR Identifying Age-Related Conditions (XGBoost/TabPFN ensemble).
2022 - Present
Processed 19 years of 5 km population rasters into a harmonized panel; deployed an interactive Streamlit map in 2025.
2020 - 2025
Supported graduate finance and undergraduate economics courses and coached students in quantitative methods.
Education and Honors
Clark University, Ph.D. in Economics (August 2026)
SUNY Buffalo, M.A. in Economics
Valparaiso University, M.S. in International Economics and Finance
Chongqing University, B.Mgmt. in Accounting
Sheftel Award for Research Excellence, Clark University (2025, two-time recipient)
Veendorp Best Field Paper Award (2022)
Doctoral Fellowship, Clark University (2019-2026)
Distinguished Student Award (Graduate School), Valparaiso University Alumni Association (2018)
Kaggle Silver Medal (2024) and Bronze Medal (2023)
Southern Economic Association (2025)
Midwest Economic Conference (2025)
Clark Ph.D. seminars (2022-2025)
Contact
I am happy to discuss Applied Economist roles where rigorous empirical evidence, experimentation, and economic modeling need to become clear business decisions. Email is the fastest way to reach me.