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Convex Optimization Continuous Hidden Markov Model


June 2018 – June 2019

UC Berkeley & Stanford

Concurrent Enrollment

Courses Taken (courses taken and audited at Stanford are mentioned to differentiate courses taken at Berkeley and at Stanford) from summer of 2018 to June of 2019

  • STAT 325 Multivariate and Random Matrix Theory (Graduate level; Audited at Stanford)
  • STAT 318 Modern Markov Chains (Graduate level; Audited at Stanford)
  • STAT 300B Theory of Statistics (Graduate level; Audited at Stanford)
  • CS 228 Probabilistic Graphical Model (Graduate level; Stanford)
  • STAT 210B Theoretical Statistics (Graduate level)
  • STAT 210A Theoretical Statistics (Graduate level)
  • STAT 153 Time Series (Audited)
  • EECS 227C Optimization for Large Scare Data Analysis (Graduate level)
  • EECS 227B Convex Optimization and Approximation (Graduate level)
  • EE 290S Machine Learning for Sequential Decision Making Under Uncertainty (Graduate level)
  • CS 189 Machine Learning (Summer 2018)
  • MATH 228A Numerical Solution of Differential Equations (Graduate Level)
August 2015 – May 2017

UC Berkeley

Concurrent Enrollment

Courses Taken for Graduate School Preparation

  • MATH 118 Fourier Analysis, Wavelets and Signal Processing
  • MATH 126 Introduction to Partial Differential Equation
  • MATH 202A Introduction to Topology and Analysis (Graduate Level)
  • MATH 202B Introduction to Topology and Analysis (Graduate Level)
  • MATH 204 Ordinary Differential Equation (Graduate Level)
  • MATH 228B Numerical Solution of Differential Equation (Graduate Level)
June 2015 – Present


Summer School

Courses Taken (EE364A was taken during the summer of 2018)

  • EE 364A Convex Optimization (Graduate level)
  • STAT 200 Introduction to Statistical Inference (Master Level)
  • STAT 217 Introduction to Stochastic Process (Master Level)
September 2008 – June 2012

UC Irvine

Undergraduate Institution

Courses Taken

  • MATH 240A Graduate Real Analysis (Graduate level)
  • MATH 121AB Linear Algebra
  • MATH 112ABC Introduction to Partial Differential Equation


September 2018 – April 2019

Research Student under the supervision of Doctor John Wu

Lawrence Berkeley National Lab

Research areas are:

  • Conducted research on high frequency trading via reinforcement learning


  • Lawrence Berkeley National Lab, One Cyclotron Road, MS50B Berkeley, CA 94720, USA