Dang Khoa Nguyen, MA

 

Faculty of Mathematics
University of Vienna
Room 04.132
Oskar-Morgenstern-Platz 1
1090 Wien, Austria

 

mail: dang-khoa.nguyen@univie.ac.at
phone: +43 1 4277 50762

Teaching: course directory

 

Supervisor
Radu Ioan Bot

 

 

MA (Applied Mathematics)

Research area in the program
Convex Optimization, Nonsmooth Optimization

Keywords

  • convex optimization
  • nonsmooth optimization
  • monotone operator theory
  • numerical algorithms
  • convergence analysis
  • applications to real-life problems

Research Interests

The research interests of Dang-Khoa Nguyen include both theoretical and numerical aspects of convex and nonsmooth optimization. In particular, he is investigating splitting algorithms for monotone inclusions and their application to optimization problems. The produced numerical schemes find applicability in the solving of real-life problems in fields like image and signal processing, machine learning, and network communication. Other interests lie in the field of numerical analysis, for instance, in developing numerical schemes for conservation laws, and in numerical linear algebra.

Scientific CV

Education
Since 10/2016: PhD student, Vienna Graduate School On Computational Optimization, University of Vienna, Austria.
07/2015 – 07/2016: M.Sc., Applied Mathematics, University of Tours - Université François-Rabelais, France.
09/2011 – 06/2015: B.Sc., Mathematics and Computer Science, University of Sciences, Vietnam National University - Ho Chi Minh city, Vietnam.

 

Academic Positions
04/2016 – 07/2016: Internship, Centre de mathématiques, Institut National des Sciences Appliquées de Rennes, France.
09/2015 – 12/2015: Teaching assistant, Faculty of Mathematics and Computer Science, University of Science, Ho Chi Minh city, Vietnam.

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Publications

Work in Progress

Bot, R. & Nguyen, D.-K. (2019). A Proximal-based algorithm for general difference of convex programming.

Bot, R., Vuong, P. & Nguyen, D.-K. (2019). Convergence analysis of Proximal Alternating Direction Method of Multipliers for nonlinear composition optimization.

Nguyen, D.-K., Petrot, N., Promsinchai, P. (2019). Random Block-Coordinate Forward-Backward Penalty Schemes for Monotone Inclusion and Minimization Problems.

Submitted

 Bot, R. & Nguyen, D.-K. (2018). The proximal alternating direction method of multipliers in the nonconvex setting: convergence analysis and rates. arXiv.

Accepted/published

Bot, R. & Nguyen, D.-K. (2018). A forward-backward penalty scheme with inertial effects for monotone inclusion. Applications to convex bilevel programming. Optimization.

Bot, R., Csetnek, E. & Nguyen D.-K. (2018). A proximal minimization algorithm for structured nonconvex and nonsmooth problems. SIAM Journal on Optimization.