Research Interests
Stochastic Games Stochastic Differential Equations Groundwater Management Financial Mathematics Deep Learning
Skills
Programming Languages
Python R LaTeX Markdown Git
Libraries & Frameworks
NumPy Pandas Matplotlib Scikit-learn PyTorch Statsmodels SciPy
Tools
Quarto Jupyter GitHub VS Code
Education
Committee: Prof. M. Ludkovski (supervisor), Prof. J.P. Fouque, Prof. R. Hu.
Thesis: Stochastic game models for groundwater markets in California.
Coursework: Probability Theory · Statistical Theory · Machine Learning · Energy Finance · Financial Models · Advanced Time Series · Bayesian Analysis · High-Frequency Trading
Supervisors: Dr George Wang (Lancaster), Prof. Ian D’Souza (NYU Stern).
Dissertation: Measuring and Forecasting Mutual Fund Survival Capacity using Machine Learning Algorithms.
Coursework: Derivatives Pricing · Financial Econometrics · Market Risk Forecasting · Stochastic Calculus · Extreme Value Methods · Forecasting
Coursework: Real Analysis · Complex Analysis · Linear Algebra · Probability · Statistical Modelling · Bayesian Inference · Time Series Analysis · Differential Equations · Combinatorics
Employment
- Conducting doctoral research on stochastic game models for groundwater markets under the supervision of Prof. Michael Ludkovski.
- Developing deep learning methods for solving high-dimensional stochastic control and mean-field game problems.
- Supported by the Amazon Fellowship in Responsible AI.
- Led discussion sections, held office hours, and graded assessments across courses in data science, probability, statistics, and survival analysis with combined enrolment of 200+ students per quarter.
- Served as instructor of record (Teaching Associate), independently managing all course administration, lectures, and assessments.
- Assisted with research on machine learning methods for mutual fund performance and survival forecasting.
- Contributed to data collection, model implementation, and preparation of working paper submitted for publication.
Fellowships & Grants
- Amazon Fellowship in Responsible AI (2024 — Present) Awarded by Amazon Science to support doctoral research on responsible AI at the University of California Santa Barbara.
Working Papers
- Measuring and Forecasting Mutual Fund Survival Capacity using Machine Learning Algorithms, with Dr George Wang (Lancaster University Management School) and Ian D’Souza (NYU Stern).
Teaching
| Course | Title | Role |
|---|---|---|
| PSTAT 5A | Understanding Data | Teaching Assistant |
| PSTAT 5LS | Life Science Statistics | Teaching Assistant |
| PSTAT 8 | Introduction to Mathematical Proof | Teaching Assistant |
| PSTAT 10 | Introduction to Data Science | Instructor |
| PSTAT 120C | Probability and Statistics | Teaching Assistant |
| PSTAT 175 | Survival Analysis | Teaching Assistant |
| PSTAT 274 | Time Series Analysis | Teaching Assistant |
| PSTAT 100 | Data Science Concepts and Analysis | Instructor |
| PSTAT 160A | Stochastic Processes | Teaching Assistant |
Awards
Award for Best Academic Performance 2020/21 Highest GPA on the MSc Quantitative Finance programme at Lancaster University in the 2020/21 academic year.
Award for Best Dissertation Results 2020/21 Highest dissertation mark on the MSc Quantitative Finance programme at Lancaster University in the 2020/21 academic year.
Lancaster Gold Award Awarded for skills developed outside academia, including digital skills, charity work, work experience, and serving as a Student Academic Representative.