Student Seminar Series – Fall 018

Schedule for Fall 2018


Seminars are on Wednesdays
Time: 12:00pm – 1:00pm
Location: Room 1025, 1255 Amsterdam Avenue
Contacts: Yuling Yao, Owen Ward

Information for speakers: For information about schedule, direction, equipment, reimbursement and hotel, please click here.


Prof. Richard Davis, Prof. Bodhi Sen and Andrew Davison (Columbia)

“New Students Welcome and Introductions”


Wenda Zhou, Florian Stebegg, Shuaiwen Wang, Chengliang Tang, and others (Columbia)

“Students Summer internship”


Two Sigma “Two Sigma Info Session”



Susanna Makela (Google)

10/3/18 Ari Brill (Columbia, Physics) “Deep Learning for Gamma Ray Astronomy”
10/10/18 SIG Quant Info Session
10/17/18 Victor Veitch (Columbia)



Promit Ghosal (Columbia University)


Title: Monge-Kantorovich ranks and quantiles: Defi nitions and hypothesis testing.

Abstract: Ranks and quantiles are two important tools in the nonparametric statistics. There were enormous progress in one dimensional rank based inference in the past. Over the last three decades, several new notions of multidimensional ranks and quantiles are proposed. Recently, Chernozhukov et al. (2015) introduced Monge-Kantorovich (MK) ranks and quantiles whose de nitions are motivated by the optimal transportation theory. In an ongoing work with Prof. Bodhi Sen, we propose an one sample and a two sample test for testing the equality of multidimensional distributions based on the MK ranks and quantiles. This talk is the first one in a series of two talks on this joint work. The second talk will be given by Prof. Bodhi Sen next week. In this week’s talk, we will primarily focus on the de nitions of relevant objects and some previous works. If time permits, we will discuss the consistency and other properties of our tests and show an outline of the pointwise rate of convergence result of the MK quantile function. No prior knowledge of the optimal transport theory will be assumed.


Prof. Bodhi Sen (Columbia University)
“An introduction to Optimal Transport in Statistics, part 2.”


Prof. Sumit Mukherjee (Columbia University)

“Limit theory for permutations”

Permutation limit theory first originated in Combinatorics, and is very much motivated by (dense) graph limit theory.  We will first give examples of models of random permutations (which includes the famous Mallows models) for which we know the existence of a limit. As an application of this, we will compute limiting properties of various statistics on permutations, such as the number of fixed points, number of cycles of a given length, and number of inversions. As another application of this theory, we will compute asymptotics of the log normalizing constant for some exponential families on the space of permutations, which in turn will be used to show existence of consistent estimators in these models.


Elizabeth Ogburn (Johns Hopkins)

12/5/18 Prof. Victor de la Pena (Columbia University)

12/12/18 Prof. Yang Feng (Columbia University)