UCLA Department of Mathematics

7324 Mathematical Sciences,

Los Angeles, CA 90095

Introduction to Programming,

Lecture 1 (8:00–8:50am).

Computing (COMPTNG) 20A,

Principles of Java Language with Applications,

Lecture 1 (9:00–9:50am).

Stochastic Optimization

Convex Analysis

Numerical Analysis

Scientific Computing

Proximal-Proximal-Gradient Method. Ernest K. Ryu and Wotao Yin, Manuscript. Code, Slides.

Unbalanced and Partial L1 Monge-Kontorovich Problem: A Scalable Parallel First-Order Method. Ernest K. Ryu, Wuchen Li, Penghang Yin, and Stanley Osher, Manuscript.

Cosmic Divergence, Weak Cosmic Convergence, and Fixed Points at Infinity. Ernest K. Ryu, Manuscript.

A Parallel Method for Earth Mover's Distance.
Wuchen Li, Ernest K. Ryu, Stanley Osher, Wotao Yin, and Wilfrid Gangbo,
To appear on *Journal of Scientific Computing*, 2017.

A New Use of Douglas-Rachford Splitting and ADMM for Identifying Infeasible, Unbounded, and Pathological Conic Programs. Y. Liu, E. Ryu, and W. Yin, Manuscript.

Convex Optimization for Monte Carlo: Stochastic Optimization for Importance Sampling. E. Ryu, Stanford University PhD thesis, 2016.

Adaptive Importance Sampling via Stochastic Convex Programming. E. Ryu and S. Boyd, Manuscript.

Stochastic Proximal Iteration: A Non-Asymptotic Improvement Upon Stochastic Gradient Descent. E. Ryu and S. Boyd, working draft.

A Primer on Monotone Operator Methods.
E. Ryu and S. Boyd,
*
Applied and Computational Mathematics an International Journal*,
15(1), 2016.

Risk-Constrained Kelly Gambling. E. Busseti, E. Ryu, and S. Boyd, Manuscript.

Extensions of Gauss Quadrature via Linear Programming.
E. Ryu and S. Boyd,
*Foundations of Computational Mathematics*, 15(4):953–971, 2015.

Computing
Reaction Rates in Bio-molecular Systems Using Discrete
Macro-states. E. Darve and E. Ryu.
In T. Schlick, editor, *Innovations in Biomolecular Modeling and
Simulations.* Royal Society of Chemistry, 2012.

Structural Characterization of Unsaturated Phosphatidylcholines Using
Traveling Wave Ion Mobility Spectrometry.
H. Kim, H. Kim, E. Pang, E. Ryu, L. Beegle, J. Loo,
W. Goddard, and I. Kanik.
*Analytical Chemistry*, 2009.

Courses taught:

- Convex Optimization I (EE364a), Summer 2014 (sole instructor).
- ICME Refresher Course, Sept. 17–20 2012.

Teaching assistant at Stanford University for:

- Convex Optimization II (EE364b), Spring 2014.
- Numerical Linear Algebra (CME 302), Fall 2013.
- Convex Optimization I (EE364a), Winter 2013.
- Computer Programming in C++ for Scientists and Engineers (CME211), Fall 2011.

Teaching assistant at California Institute of Technology for:

- Introductory Methods of Applied Mathematics (ACM95abc), 2009–2010.
- Physics Laboratory (Ph7), Spring 2009.

Other teaching assistant experience:

- Convex Optimization (MOOC) (CVX101), Winter 2014.

PhD, Computational and Mathematical Engineering, Stanford, 2010–2016.

BS with Honor, Electrical Engineering, Caltech, 2010.

BS with Honor, Physics, Caltech, 2010.

MIT,
Imaging and Computing Group,
visiting student, Summer 2011.

Caltech,
Biophotonics Laboratory, research assistant, Summer 2010.

JPL NASA, internship, Summer
2007, 2008, and 2009.

Simons Math+X Graduate Fellowship, 2012–13 and 2014–15.

DOE Office of Science Graduate Fellowship (SCGF), 2010–13.

NASA Tech Brief Award, 2011.

Caltech Upper Class Merit Award, 2008.

Some classical papers that are hard to find on the web.