Michael H. Lim
(Hyun Jae Lim)
UC Berkeley - PhD in Statistics & Robotics
Harvard University Class of 2018
"ML does ML"
I am a PhD student in Statistics with a focus on robotics at UC Berkeley. I love physics, mathematics, natural sciences, and computational sciences, with a strong background in computational research in quantitative fields. I am interested in research opportunities spanning control theory, sequential decision making, and machine learning, with applications in robotics. During my time at Harvard University, I received 4th year combined master's degree in Statistics, and Magna Cum Laude with Highest Honors for bachelor's degree in Physics and Mathematics. I am grateful to be supported by the NSF Graduate Research Fellowship.
Outside of school work and research, I love photographing, choreographing, break dancing, snowboarding, and playing electric guitar.
Education and Honors
University of California, Berkeley
- 2018-Present: Ph.D. Candidate in Statistics
- 2017-2018: A.M. in Statistics
- 2014-2018: A.B. in Physics and Mathematics, Magna Cum Laude with Highest Honors
Stuyvesant High School
- 2010-2014: NYS Advanced Regents Diploma
- 2019: NSF Graduate Research Fellow
- 2019: Hertz Foundation Fellowship - Semifinalist
- 2017: Harvard College Research Program - Summer Researcher
- 2016: Harvard College Teaching Assistant - Derek Bok Award for Teaching Excellence
- 2015: Georgetown Physics REU - Participant and Recipient of NSF Grant
- 2014: Intel Science Talent Search - Semifinalist (National Top 200)
- 2014: National Merit Scholarship - Finalist and Recipient
- 2014: U.S. Physics Team - Gold Medalist and 2-time Semifinalist (National Top 60)
- 2013: Siemens Competition - Regional Finalist for Individual Research (National Top 30)
- Graduate Coursework: Advanced Robotics, Linear Systems Theory, Optimization Models, Probabilistic Modeling in Genomics, Theoretical Statistics II, Statistical Models: Theory and Applications I, II, Teaching of Probability and Statistics
- Graduate Coursework: Probability Theory I, II, Statistical Inference I, Multivariate Statistical Analysis, Philosophical Foundation of Statistics, Electromagnetic Interactions with Matter, Market Design
- Advanced Coursework: Machine Learning, Generalized Linear Models, Stochastic Processes, Game Theory, Probability, Quantum Mechanics I, II, Solid State Physics, Abstract Algebra, Differential Geometry, Linear Algebra and Real Analysis I, II, Vector Space Methods for Differential Equations
- Lim, M. H., Yoshimura, B. T., & Freericks, J. K. (2016). Creating analogs of thermal distributions from diabatic excitations in ion-trap-based quantum simulation. New J. Phys. 18 043026. [pdf]
- Exoo, G., Ismailescu, D., & Lim, M. (2014). On the Chromatic Number of R4. Discrete Comput. Geom. 52(2): 416. [pdf]
- 2019: Stat 135 - Concepts of Statistics, in Spring 2019 with Dr. Adam Lucas.
- 2017: Stat S-106 - Probability, Statistics and Calculus, in Summer 2017 with Prof. Joseph Blitzstein, Prof. Nina Zipser, Prof. Xiao-Li Meng.
- 2017: Physics 15b - Introduction to Electromagnetism and Statistical Physics, in Spring 2017 with Dr. David Morin (Grader).
- 2016: Stat 110 - Introduction to Probability, in Fall 2016 with Prof. Joseph Blitzstein.
- 2015: Math 23a - Linear Algebra and Real Analysis I, in Fall 2015 with Prof. Paul Bamberg.
- 2019-Present: Online Robotic Motion Planning - Graduate Student Researcher, Advisor: Prof. Claire Tomlin, UC Berkeley
- 2016-2018: Stochastic MCMC Simulation - Statistics Research Assistant, Advisor: Prof. Samuel Kou, Harvard University
- 2015: Computational Condensed Matter - Physics REU Participant, Advisor: Prof. James Freericks, Georgetown University
- 2015: Condensed Matter Physics - Physics Research Assistant, Advisor: Amir Yacoby, Harvard University
- 2012-2014: Geometric Graph Theory - Mathematics Research Assistant, Advisor: Geoffrey Exoo (Indiana University), Dan Ismailescu (Hofstra University)
- 2016: Quantitative Finance Research - Trading Intern, IMC Financial Markets