Kelvin Shuangjian Zhang
I am a Postdoctoral Fellow at the
Department of Mathematics and Applications,
ENS Paris,
working with Professor
Gabriel Peyré.
I received my Ph.D. degree from the
Department of Mathematics,
University of Toronto
in 2018, under the supervision of Professor
Robert J. McCann.
During summer 2018, I visited Professor
Guillaume Carlier
at
MOKAPLAN,
INRIA. Then I worked with Professor
Marco Cuturi as a Postdoctoral Fellow at
CREST

ENSAE ParisTech, before I moved to ENS Paris.
Research Interests:
Optimal Transport, and its applications in
  Economics (Screening, Auction)
  Machine Learning (GANs)
  Statistics (MCMC)
Interested Topics Include:
 Prescribed Jacobian equation, Monge–Ampère equation
 Langevin Monte Carlo, Fokker–Planck equation
 The principalagent framework, Duopoly models
 Wasserstein GANs
Publications:
[1] Circular cone: a novel approach for protein ligand shape matching using modified PCA [pdf]. Kelvin Shuangjian Zhang, Jun Du, Liang Zhang, Cheng Zeng, Qiao Liu, Tao Zhang and Gang Hu. Computer Methods and Programs in Biomedicine 108(1) (2012) 168175.
[2] Implicit manifold learning on generative adversarial networks [pdf]. Kry Yik Chau Lui, Yanshuai Cao, Maxime Gazeau, Kelvin Shuangjian Zhang. ICML2017 Workshop on Implicit Generative Models, Sydney, 2017.
[3] On concavity of the monopolist's problem facing consumers with nonlinear price preferences [pdf], with Robert J. McCann.
Comm. Pure Appl. Math. 72(7) (2019) 13861423.
[4] Existence in multidimensional screening with general nonlinear preferences [pdf]. Econ. Theory 67(2) (2019) 463485.
[5] Existence, Uniqueness, Concavity and Geometry of the Monopolist’s Problem Facing Consumers with Nonlinear Price Preferences
[pdf]. PhD Thesis, University of Toronto, 2018.
[6]
Existence of solutions to principalagent problems with adverse selection under minimal assumptions
[pdf], with Guillaume Carlier. J. Math. Econ. 88 (2020) 6471.
[7] Wasserstein Control of Mirror Langevin Monte Carlo
[pdf].
Kelvin Shuangjian Zhang, Gabriel Peyré, Jalal Fadili, Marcelo Pereyra. In Proc. COLT'20, 2020.
[Slides]
Invited Talks
Useful Links:
arXiv  MathSciNet  AMS  CMS  CREST  ENSAE  BIRS  MSRI  Fields  PIMS  CRM  CIM  INRIA  MOKAPLAN  Vector  BorealisAI  Layer6AI  fast.ai  GitHub  Coursera  UofT library  ScienceDirect  JSTOR  LibGen  Google Scholar  UofT Economics seminars  UofT Math seminars  CREST Economics seminars  CREST Statistics seminars  Statistical Machine Learning in Paris  Séminaire Parisien d'Optimisation
Dr. Kelvin Shuangjian Zhang
Département de Mathématiques et Applications
École Normale Supérieure (ENS)
45 Rue d’Ulm
75005 Paris, FRANCE
Office: Room T21
Email: szhang [at(@)] ens.fr