From Queens, NY. Ph.D. research in probability theory.

E-mail me at ssk@stevensoojin.kim.


bio

2020-2021:  Research, Replica, New York, NY

2017-2020:  Modeling, Two Sigma, New York, NY

2012-2017:  Ph.D., Applied Mathematics, Brown University
  (Sigma Xi Award)

2013-2016:  Fellow, NDSEG, US Dept. of Defense

Summer’16:  Data Science, Twitter, Cambridge, MA

2008-2012:  B.S.E., ORFE + PACM + CS, Princeton University
  (J. Rich Steers Award, PACM Prize)

2008-2012:  Pell Grant, Federal Student Aid, US Dept. of Education

Summer’11:  Strategies, Goldman Sachs, New York, NY


research

During my Ph.D., I did research on applied probability, rare events, and connections to statistics and optimization. I was very fortunate to be advised by Kavita Ramanan.

  1. Large deviation principles induced by the Stiefel manifold, and random multidimensional projections
    (w/ K. Ramanan)
    Electronic Journal of Probability, 2023.
    arXiv:2105.04685, doi:10.1214/23-EJP1023

  2. An asymptotic thin shell condition and large deviations for random multidimensional projections
    (w/ Y.T. Liao and K. Ramanan)
    Advances in Applied Mathematics, 2022.
    arXiv:1912.13447, doi:10.1016/j.aam.2021.102306

  3. A conditional limit theorem for high-dimensional ℓp spheres
    (w/ K. Ramanan)
    Journal of Applied Probability, 2018.
    arXiv:1509.05442, doi:10.1017/jpr.2018.71

  4. Large deviations for random projections of ℓp balls
    (w/ N. Gantert and K. Ramanan)
    Annals of Probability, 2018.
    arXiv:1512.04988, doi:10.1214/16-AOP1169

  5. Cramér’s theorem is atypical
    (w/ N. Gantert and K. Ramanan)
    Advances in the Mathematical Sciences, AWM Research Symposium 2015.
    arXiv:1508.04402, doi:10.1007/978-3-319-34139-2_11

  6. Problems at the Interface of Probability and Convex Geometry: Random Projections and Constrained Processes Ph.D. Thesis, May 2017.


teaching+


perspective

I am broadly interested in applicable mathematics — i.e., theory that can reveal new aspects of the world around us.

“I regard as quite useless the reading of large treatises of pure analysis: too large a number of methods pass at once before the eyes. It is in the works of applications that one must study them; one judges their ability there and one apprises the manner of making use of them.”

— J.-L. Lagrange