Research Assistant
Resume:
Minh P. Nguyen
Austin, TX, *****
B adkcho@r.postjobfree.com
mpnguyen2
minhpnguyen
Education
2018–2023 PhD in Mathematics, The University of Texas at Austin, GPA – 3.89/4.0. 2014–2018 Bachelor of Science, Stony Brook University, GPA – 3.77/4.0. Major in Mathematics. Minor in Computer Science.
Projects and experiences
Oct 20–Present Deep reinforcement learning and shape optimization. Develop a shape gradient-based deep reinforcement learning method for solving 2D isoperimetric problem on simply-connected domains. Implemented in Python. Use OpenAI Gym to develop the environments. Dec 19–Present Stochastic control theory.
Define weak probabilistic viscosity solution for stochastic control problem. Prove the Alexandrov theorem for convex function by stochastic calculus and positive additive continuous functional. Aug 19–Dec 19 Milestoning and domain decomposition methods. Develop a domain decomposition algorithm that is equivalent to milestoning method to solve the first hitting time problem on slow Ito processes. Implemented in MATLAB. Nov 17–May 18 Balzan project in topological fluid dynamics. Implement and optimize the topological-theoretic algorithms to calculate fluid motion on discrete models associated with 2-torus and 3-torus.
Jun 17- Sep 17 SPUR Program at Cornell University. Study fundamental properties of linear algebra in group-theoretic setting [3]. Mar 16–Apr 17 Project in geometry and topology.
Develop a program in JavaScript to compute the Goldman bracket and cobracket and other statistics of two curves on 2D surface [1]. Discover two classes of ideals in the Goldman algebra [2]. Honors and Awards
2019 Prelim Excellence Award.
2018-2023 Provost’s Graduate Excellence Fellowship for 5 years from August 2018 to May 2023. 2016 Stony Brook Foundation Award, given to one student for excellence in mathematics. 2014-2016 Top 50 scorers in Putnam Competitions in 3 years 2014, 2015, and 2016. 2012 International Mathematical Olympiad Silver Medal. Skills
Languages Python, C++, JavaScript, Java.
Software MATLAB, Mathematica.
Libraries NumPy, SciPy, TensorFlow, OpenAI Gym.
Relevant coursework
Graduate Numerical Analysis, Fast methods in scientific computing, Stochastic Processes, Predictive Machine Learning, Deep Learning, Combinatorial Optimization, Statistical Machine Learning, Algorithms.
Undergraduate Data Structure, Computer Networks, Computational Geometry.
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