CV

Education

• B.S. in Github, Github University, 2012
• M.S. in Jekyll, Github University, 2014
• Ph.D in Version Control Theory, Github University, 2018 (expected)

Work experience

• Summer 2015: Research Assistant
  • Github University
  • Duties included: Tagging issues
  • Supervisor: Professor Git
• Fall 2015: Research Assistant
  • Github University
  • Duties included: Merging pull requests
  • Supervisor: Professor Hub

Skills

• Skill 1
• Skill 2
  • Sub-skill 2.1
  • Sub-skill 2.2
  • Sub-skill 2.3
• Skill 3

Publications

Paper Title Number 1

Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1).

Paper Title Number 2

Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2).

Paper Title Number 3

Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3).

Talks

Talk 1 on Relevant Topic in Your Field

March 01, 2012

Talk at UC San Francisco, Department of Testing, San Francisco, California

Tutorial 1 on Relevant Topic in Your Field

March 01, 2013

Tutorial at UC-Berkeley Institute for Testing Science, Berkeley CA, USA

Talk 2 on Relevant Topic in Your Field

February 01, 2014

Talk at London School of Testing, London, UK

Conference Proceeding talk 3 on Relevant Topic in Your Field

March 01, 2014

Conference proceedings talk at Testing Institute of America 2014 Annual Conference, Los Angeles, CA

Teaching

Teaching experience 1

Teaching experience 2

Service and leadership

• Currently signed in to 43 different slack teams

Education

• Ph.D. in Electrical Engineering & Computer Science, Massachusetts Institute of Technology.
  Ph.D. minor in Mathematics & Statistics.
  Computer Science and Artificial Intelligence Laboratory
  • _{PhD-level Subjects in areas spanning Statistical Learning, Machine Intelligence, Computer Systems and Algorithms; as well as Advanced Real Analysis, Geometry and Manifolds, Mathematical Physics, Theoretical Statistics.}
• B.Eng. in Automation: Informatics & Cybernetics, Tsinghua University.
  • _{Electrical Engineering & Computer Science, Mathematics & Physics, Information, System & Control Sciences, Robotics & Machine Intelligence.}
  • _{Multiple Scholarships.}
• Non-degree Undergraduate Student and M.S., University of Pennsylvania.
  • _{Physics-based Simulation, Machine Learning Theory, Computer System and Architecture, Mathematical Optimization.}
  • _{Full Scholarships in Research and Teaching.}

Work Experience

• Research Intern, Creative Intelligence Laboratory, Adobe Research.
• Research Intern, Visual Computing Group, Microsoft Research.
• Visiting Research Fellow, Institute for Pure and Applied Mathematics, Los Angeles.
• Research Assistant, Tsinghua National Laboratory for Information Science and Technology (TNList).

Honors & Awards

• Siebel Scholar.
• MIT Presidential Fellow.

Coursework

(Math, Comp, Opt, Stat, Prob, CS, EE, Phys, Eng)

• Math
  • Advanced Calculus I,II,III
  • Advanced Algebra I,II
  • Real and Complex Analysis
  • Ordinary Differential Equations
  • Partial Differential Equations
  • Differential Geometry
  • Measure Theory and Integration
  • Functional Analysis
  • Differential Analysis
• Comp
  • Numerical Analysis and Algorithm
  • Numerical Methods for PDE
  • Computational Optimal Transport
• Opt
  • Optimization Algorithms
  • Modern Convex Optimization
  • Nonlinear Optimization
  • Operations Research
• Stat & Prob
  • Probability Theory
  • Stochastic Process Analysis
  • Mathematical Statistics
  • Statistical Inference
  • Theoretical Statistics
  • Computational Statistics
• SML
  • Machine Learning
  • Pattern Recognition
  • Computational Learning Theory
  • Statistical Learning Theory
  • Algorithmic Learning Theory
  • Information and Inference
• AI
  • Artificial Intelligence
  • Integrated Robotics Intelligence
  • Advances in Computer Vision
  • Science of Deep Learning
• CS
  • Programming Methodology
  • Programming Language
  • Discrete Mathematics
  • Automata and Languages
  • Data Structure and Algorithm
  • Algorithm Design and Analysis
  • Theory of Computation
  • Advanced Algorithms
  • Computer Principles
  • Operating System
  • Computer Networks
  • Computer Architecture
  • Software System
  • Distributed System
  • Advanced Computer Graphics
  • Physically Based Animation
  • Digital Image Processing
• EE
  • Modern Control Theory
  • Optimal and Nonlinear Control
  • Dynamic Programming
  • Signals and System Analysis
  • Statistical Signal Processing
• EE
  • Theory and Analysis of Circuits
  • Digital and Analog Electronics
  • Programmable Logic Systems
  • Microelectronics and Device
  • Projects in Circuit Design
• Phys
  • Theoretical Foundations of Physics
  • Quantum and Statistical Physics
  • Electromagnetic Theory
  • Theory of Optics
  • Mathematical Physics
  • Computational Physics
  • Experimental Physics
• Other
  • Principles of Physical Science
  • Principles of Chemical Science
  • Principles of Biological Science
  • Introduction to Architecture
  • International Politics
  • Introduction to Modern History
• • Abstract Algebra
  • Differential Manifold and Topology
  • Mathematics of Modern Physics
  • Advanced Stochastic Process
  • High-dimensional Statistics
  • Information Theory
  • Probabilistic Graphical Models
  • Advanced Natural Language Processing
  • Deep Reinforcement Learning

Coursework

	### Tsinghua University

	Optimization Algorithms

	Partial Differential Equation

	Numerical Analysis & Algorithm

	Advanced and Complex Analysis

	Probability & Statistics

	Stochastic Process Analysis

	Artificial Intelligence

	Pattern Recognition

	Robotics & Machine Vision

	Data Structure & Algorithms

	Programming Methodology

	Computer Principles

	Operating System

	Computer Networks

	Computer Graphics & Animation

	Digital Image Processing

	Advanced Computer Graphics

	Classical and Modern Physics

	Mathematical Physics

	Signals & System Analysis

	Control & System Theory

	Circuits & Electronics

	Operations Research


	### University of Pennsylvania

	Machine Learning

	Computer Architecture

	Theory of Computation

	Software System

	Computational Learning Theory

	Algorithms for Big Data

	Special Topics in Computer Graphics

	Modern Convex Optimization

	Applications of Scientific Computation (Instructor)

	Physically Based Animation (TA)

	(Advanced Topics in Algorithms)

	(Seminars on Robotics and Perception)


	### Massachusetts Institute of Technology

	Advanced Algorithms

	Information & Inference

	Advances in Computer Vision

	Distributed System

	(Numerical Methods for PDE)

	(Differential Geometry & Manifolds)

	(Graphical Models)

	(Topics in Theoretical Computer Science)