Skills

Machine Learning, Stochastic Processes, Statistical Learning, Stochastic Network, Time Series, Stochastic Calculus, Mathematical Finance

Programming Language: R, Python, SQL, MATLAB, LaTeX, Mathematica, C++

Piano:Level Ten in China (Top level in nonprofessional range)

Teaching Experience

Stochastic Integral: Graduate level course

Computational Finance Methods: Rady School, Master of Finance

Probability Theory: Graduate level course

Introduction to Real Analysis

Introduction to Stochastic Processes: Markov property and Brownian motion

Advanced Calculus
Introduction to Computational Statistics: Implement statistical methods with R

The Mathematics of Finance: Binomial model and Black-Scholes Model

Introduction to Probability

Projects

PhD Research Topic

Analyze asymptotic behavior of a subcritical/critical fluid model of bandwidth sharing policy with general document size distributions as part of the NSF-supported project Stochastic Network Dynamics: Approximation, Analysis and Control.

Machine Learning (Python)

Solved maze problem by Markov Decision Process with value iteration algorithm

Solved speech recognition problem by Hidden Markov Model(HMM) with Viterbi algorithm

Statistics

Implemented model selection through cross validation, AIC, BIC and applied EM algorithm to estimate parameters

The National Undergraduate Innovative Program

Worked on recovering the 3D configuration of protein based on its partial structure using a Self-Referential Model

Contact

  • yif051@ucsd.edu
  • Applied Physics and Mathematics Building, UCSD, California, USA