Resume
Education
2014 - 2018
Hong Kong University of Science and Technology
Bachelor of Science in Mathematics; GPA: 3.80/4.30
Awards:
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University Scholarship (HKUST)
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Dean's List (School of Science, HKUST)
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University's Scholarship Scheme for Continuing UG Students (HKUST)
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Chern Class Talent Scholarship (Department of Mathematics, HKUST)
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HKSAR Government Scholarship Fund - Reaching Out Award 2016/17
Programs:
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HKUST Summer Mainland Program - Peking University Summer School
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National University of Singapore (Exchange program; GPA: 4.63/5.00)
2018 - 2023
The University of Texas at Austin
Doctor of Philosophy in Mathematics
Work
Experience
2023 - present
Postdoctral Associate
University of Minnesota - Twin Cities
2020 - 2023
Graduate Research Assistant
The University of Texas at Austin
2018 - 2020
Graduate Teaching Assistant
The University of Texas at Austin
2020
Mentor, Directed Reading Program
A study on barycentric coordinates
2016
Student Helper
Math Support Center, Hong Kong University of Science and Technology
Research
Projects
2023 - present
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Applied numerical PDE methods to simulate the highly non-linear Poisson-Schrödinger system with singular dopants in semiconductors (SDDS subgroup), developing computationally efficient predictive models with enhanced algorithmic stability and improved accuracy.
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Researching nonlinear and sigmoid-based landscape law estimators for spectral prediction.
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Implemented Finite Element Methods (FEM) in Python, utilizing preconditioners and adaptive mesh refinement pipelines to simulate and visualize theoretical flux patterns across complex fractal Robin boundaries.
2024
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Engineered a robust data pipeline utilizing Python (Pandas) and SQL to process ~150,000 trial-cell responses from the Allen Institute visual behavior 2P dataset. Constructed relational tables and engineered predictive features, including stimulus identity, exposure level, and response latency.
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Designed interactive Tableau dashboards to visualize complex neural dynamics across 223 cells and 13 mice. Utilized heatmaps and scatter plots to compare change versus omission events and uncover behavioral modulation patterns linked to running speed.
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Conducted exploratory machine learning and dimensionality reduction using Scikit-learn (Random Forest, PCA) to classify high versus low neural responses and investigate latent structures in neural activity patterns.
GitHub Repository: neural-activity-analysis
Construction of Supplemental Functions for Direct Serendipity and Mixed Finite Elements on Polygons
We are substituting the rational shape functions of direct serendipity spaces with piecewise polynomials in order to improve the performance regarding numerical results.
2022 - 2023
Construction of Direct Serendipity Finite Elements on Cuboidal Hexahedra
We generalized the construction of direct serendipity finite element spaces to convex hexahedra.
2020 - 2022
We generalized the construction of direct serendipity and direct mixed finite element spaces to convex polygons, achieving optimal approximation properties and having minimal local dimension.
Demonstration Code: directpoly
2018 - 2022
We developed families of direct serendipity and direct mixed finite element spaces on convex quadrilaterals, achieving optimal approximation properties and having minimal local dimension.
2017
International Research Internship; University of California, Los Angeles
Focused on developing new algorithms for an image processing
problem, specifcally, GISC spectral camera. The image processing problem was turned into a convex optimization problem to solve.
2016
2022 - 2023
Final Year Project; Hong Kong University of Science and Technology
Applied statistical learning methods to studying the impact of
combinations of four kinds of anticancer drugs (Vincristine, Mitoxantrone, Etoposide and Daunorubicin) against leukemia.
Skills
& Expertise
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C++
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Python
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SQL
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Tableau
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MATLAB
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R
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LaTeX
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Linux
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Parallel Computing