Open to internships, graduate roles, and collaborations
Hello, I'm SHI HONGYUE
Backend & Data Analytics Developer
Python-focused backend and data analytics developer with experience in financial time-series research, statistical modeling, and reproducible machine learning experiments.
My strengths are structured problem solving and the ability to investigate unfamiliar challenges. I can take a research problem from topic definition and literature review through method selection, implementation, experiment reproduction, and validation. Reading technical material across languages, translating theory into code, and extracting reliable insight from data are central to how I work.
Master's Research — Conditional Diffusion & Covariance Forecasting
Tokyo University of Science
Designed Conditional Diffusion Score Matching (CDSM) and applied it to forecasting covariance structures in financial returns.
Conducted literature review, model design, Python implementation, experiment reproduction, and validation
Evaluated FX29, Industry49, and iShares14 against established covariance forecasting baselines
Demonstrated improved predictive accuracy and stability across empirical experiments
2024 — 2026 · Japan
Teaching Assistant
University Course Support
Supported course delivery and student learning by adapting explanations to individual levels of understanding.
Answered student questions and provided supplementary explanations during class
Prepared model solutions, assisted with grading, and coordinated with instructors and other teaching assistants
Sep 2015 — Jun 2019 · China
Quantitative Finance Research
Undergraduate Academic Project
Studied portfolio construction for index investing and implemented multiple approaches in Excel for empirical comparison.
Evaluated portfolio construction methods from risk and return perspectives
Built foundations in data structures, linear algebra, probability, statistics, economics, investment, C, and SQL
Education
Apr 2024 — Apr 2026
Tokyo University of Science
Master's Student in Management · Graduate School of Management
Researched AI-based time-series analysis, focusing on diffusion models for denoising, forecasting, and sliding-window covariance estimation.
Mar 2023 — Apr 2024
Tokyo University of Science
School of Management · Research Student in Management
Prepared for graduate-level research in management, data analysis, and quantitative methods.
Jan 2021 — Mar 2023
Kyoshin Language Academy Shinjuku
Japanese Language Program
Completed advanced Japanese-language study and prepared for graduate education in Japan.
Sep 2015 — Jun 2019
Soochow University
School of Mathematical Sciences · Financial Mathematics
Studied financial mathematics, mathematical theory, and machine learning, developing rigorous reasoning, independent learning, and structured problem-solving skills.
04 / Projects
Selected work
PROJECT / 01
Conditional Denoising Score Matching (CDSM)
A Python research codebase for sliding-window covariance estimation using conditional diffusion in time and Fourier domains, evaluated against classical statistical baselines on financial time-series datasets.
Provides reproducible data preparation, training, baseline, metric, and visualization workflows for thesis and paper experiments
PROJECT / 02
Equipment Inspection Management System (EIMS)
A role-based Flask web application where field engineers register equipment inspection results and administrators monitor equipment, assignments, and records in real time.
Built modular Blueprints, authentication and authorization, equipment/account/inspection CRUD, transactional services, MySQL and TiDB Cloud connectivity, Alembic migrations, Docker deployment, and HTTP integration tests
05 / Contact
Have an opportunity or an interesting project? Let's talk.
If you have an opportunity, a project idea, or simply want to talk technology, feel free to reach out by email or GitHub.
