UCLA Department of Mathematics

7324 Mathematical Sciences,

Los Angeles, CA 90095

Matrix Analysis,

8:00–9:50am.

Computing (COMPTNG) 20A,

Principles of Java Language with Applications,

9:00–9:50am (Lecture 1).

Stochastic Optimization

Convex Analysis

Numerical Analysis

Scientific Computing

Splitting with Near-Circulant Linear Systems: Applications to Total Variation CT and PET.
**E. K. Ryu**, Manuscript.
Code.
Slides.

Linear Convergence of Cyclic SAGA.
Youngsuk Park, **E. K. Ryu**, Manuscript.

Uniqueness of DRS as the 2 Operator Resolvent-Splitting and Impossibility of 3 Operator Resolvent-Splitting.
**E. K. Ryu**, Seyoon Ko, and Joong-Ho Won, Manuscript.
Code.

Douglas-Rachford Splitting and ADMM for Pathological Convex Optimization.
**E. K. Ryu**, Y. Liu, and W. Yin, Manuscript.
Code.
Slides.

Vector and Matrix Optimal Mass Transport:
Theory, Algorithm, and Applications.
**E. K. Ryu**, Y. Chen, W. Li, and S. Osher, SIAM Journal on Scientific Computing, 2018.
Code.

Proximal-Proximal-Gradient Method.
**E. K. Ryu** and W. Yin, Manuscript.
Code,
Slides.

Cosmic Divergence, Weak Cosmic Convergence, and Fixed Points at Infinity.
**E. K. Ryu**, Journal of Fixed Point Theory and Applications, 2018.

Unbalanced and Partial L1 Monge-Kantorovich Problem:
A Scalable Parallel First-Order Method.
**E. K. Ryu**, W. Li, P. Yin, and S. Osher,
To appear on *Journal of Scientific Computing*, 2017,
Slides.

A Parallel Method for Earth Mover's Distance.
W. Li, **E. K. Ryu**, S. Osher, W. Yin, and W. Gangbo,
*Journal of Scientific Computing*,
75(1),
2018.
Code.

A New Use of Douglas-Rachford Splitting for Identifying Infeasible, Unbounded, and Pathological Conic Programs.
Y. Liu, **E. K. Ryu**, and W. Yin,
Mathematical Programming Series A, 2018.

Convex Optimization for Monte Carlo:
Stochastic Optimization for Importance Sampling.
**E. K. Ryu**,
Stanford University PhD thesis, Advisor: Stephen P. Boyd, 2016.

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

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

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

Risk-Constrained Kelly Gambling.
E. Busseti, **E. K. Ryu**, and S. Boyd,
*Journal of Investing*, 25(3), 2016.

Extensions of Gauss Quadrature via Linear Programming.
**E. K. 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. K. 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. K. Ryu**, L. Beegle, J. Loo,
W. Goddard, and I. Kanik.
*Analytical Chemistry*, 2009.

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

Advisor: Stephen P. Boyd

MS, Statistics, Stanford, 2010–2016.

BS with Honor, Physics and Electrical Engineering, 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.

Gene Golub Best Thesis Award, 2016.

Simons Math+X Graduate Fellowship, 2012–13, 14–15,
and 15–16.

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

NASA Tech Brief Award, 2011.

Caltech Upper Class Merit Award, 2008.

Erdös number: 3 (Stephen Boyd → Persi Diaconis → Paul Erdös)