Minkey Chang — Data Scientist
Data scientist working on multivariate time series: representation learning, forecasting, and reinforcement learning for decisions under uncertainty. I work at the intersection of theory and practice — I have industry experience in market research and data analysis, and I like to take ideas from research and put them to work. I care about getting things right. I’m curious, I learn by doing, and I bring steady enthusiasm to the work.
Selected Publications & Projects
iVDFM in the proceedings track; poster session at KIAS, Seoul (July 2026).
FinAI @ ICLR 2026 — financial AI workshop (Rio, April 2026).
Book on building agents with LangChain and LangGraph (Wikidocs, May 2026).
Climate visualization for South Korea (GitHub Page).
Work Experience
Blog
Driving through underground rocks
A particle filter that cannot audit its own error, and what it took to estimate that error with simulation-based inference instead.
Can we really get alpha from market data?
Efficient Market Hypothesis, Micro Alphas, and why probabilistic forecasting matters for turning signals into positions.
What works for forecasting macro economic series with deep learning?
Data quirks of macro series, which model families work (and which don’t), and why it’s rarely one-size-fits-all.
Could multivariate time series have their own representations?
Identifiable innovations, diagonal dynamics, and iVDFM: factor recovery, interventions, and probabilistic forecasting.
Can we make a more risk-aware portfolio agent from utility theory?
Recursive (Epstein–Zin) utility with Monte Carlo certainty equivalents in PPO/A2C, on Korean ETF splits.
Effective Bird Sound Classification
Mel spectrograms and EfficientNet for bird sound: why the mel scale helps and how to keep the pipeline simple.
Creating and Evaluating Synthetic Tabular Data
Sequential synthesis for tabular data, plus three checks: propensity scores, CI overlap, and quasi-identifier risk.