Lecture Notes

  1. Graduate Probability I (Math 733): Lyu_prob_notes
  2. Machine Learning: lecturenote_156
  3. Intro to Probability Theory : lecturenote_170AB
  4. Stochastic Processes: stochastic_notes
  5. Mathematical Finance: lecturenote_174E
  6. Introduction to Probability and Statistics II: lecturenote_170S

UW-Madison

  • Fall 2023: 734 Probability Theory II
  • Spring 2023: 535 Mathematical Methods in Data Sciences
  • Fall 2022: 733 Probability Theory I [syllabus]
  • Spring 2021: 431 Introduction to Probability Theory [syllabus]
  • Fall 2021: 632 Stochastic Processes [syllabus]

UCLA

  • Winter 2020: 156 Machine Learning [GitHub, syllabus]
  • Spring 2020: 170S Statistics II [syllabus1, syllabus2]
  • Fall 2020: 170S Statistics II (Course coordinator)
  • Summer 2020: 170S Statistics II, 174E Mathematical Finance [syllabus]
  • Spring 2020: 170S Statistics II
  • Winter 2020: 170S Statistics II
  • Fall 2019: 170S Statistics II
  • Summer 2019: 170A Probability Theory, 170B Probability Theory, 174E Mathematical Finance
  • Spring 2019: 170B Probability Theory
  • Winter 2018: 170A Probability Theory, 171 Stochastic Processes [syllabus]
  • Fall 2018: 170B Probability Theory [syllabus]

OSU

  • Spring 2018: on TRIPODS grant support
  • Spring 2017 – Fall 2017: On Presidential fellowship
  • Fall 2016: On departmental (SGA) fellowship
  • Spring 2016: On departmental (SGA) fellowship
  • Fall 2015: Math 2153 (Calculus 3) Math2153notes
  • Spring 2014: Math 1131 (Calculus for business)
  • Fall 2014: Math 1131 (Calculus for business)
  • Summer 2013: Math 1152 (Calculus 2)
  • Spring 2013: Math 1151 (Calculus 1)
  • Fall 2013: Math 1151 (Calculus 1)

Probability, combinatorics, and complex systems

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