About me
I am an assistant professor of Statistics at Rutgers University. I received a Ph.D. in Statistics from University of Washington in 2018 under the supervision of Professor Jon A. Wellner, and a B.Sc. in mathematics from Fudan University in 2013.
I am broadly interested in mathematical statistics and high dimensional probability. My current research is concentrated on abstract empirical process theory, and its applications to nonparametric function estimation (with a special focus on shaperestricted problems), Bayes nonparametrics, and high dimensional statistics. My research is partially supported by a generous NSF grant.
Papers
 H. Deng, Q. Han and C.H. Zhang (2020) Confidence intervals for multiple isotonic regression and other monotone models. [arXiv]
 Q. Han and K. Kato (2019) BerryEsseen bounds for Chernofftype nonstandard asymptotics in isotonic regression. [arXiv]
 Q. Han (2019) Global empirical risk minimizers with “shape constraints” are rate optimal in general dimensions. [arXiv]
 Q. Han (2019) Multiplier Uprocesses: sharp bounds and applications. [pdf]
 Q. Han and J. A. Wellner (2019) Complex sampling designs: uniform limit theorems and applications. [arXiv]
 Q. Han and C.H. Zhang (2019+) Limit distribution theory for block estimators in multiple isotonic regression. Ann. Statist., to appear. [arXiv]
 Q. Han and J. A. Wellner (2018) Robustness of shaperestricted regression estimators: an envelope perspective. [arXiv]
 Q. Han*, T. Wang*, S. Chatterjee and R. J. Samworth (2019) Isotonic regression in general dimensions. Ann. Statist., 47, 24402471. [arXiv] (*=equal contribution)

Q. Han and J. A. Wellner (2019) Convergence rates of least squares regression estimators with heavytailed errors. Ann. Statist., 47, 2286–2319. [arXiv]
(Presented in the Annals of Statistics special invited session at JSM 2019)
 Q. Han (2017) Oracle posterior contraction rates under hierarchical priors. [arXiv]
 Q. Han and J. A. Wellner (2016) Multivariate convex regression: global risk bounds and adaptation. [arXiv]
 Q. Han and J. A. Wellner (2016) Approximation and estimation of sconcave densities via Rényi divergences. Ann. Statist., 44, 1332–1359. [arXiv]
 A. Jalali, Q. Han, I. Dumitriu and M. Fazel (2016) Relative density and exact recovery in general stochastic block models. NIPS 2016. [arXiv]
Upcoming travel
 Statistics seminar. Mar 5, 2020. Department of Statistics, University of Minnesota, USA.
 Statistics seminar. May 21, 2020. Department of Statistics, University of California Davis, USA.
 2020 ICSA Conference. Jun 26Jun 29, 2020. Wuhan, China.
 Mathematical and Statistical Challenges in Uncertainty Quantification. Jul 1316, 2020. Cambridge, UK.
 2020 IMS/Bernoulli World Congress of Probability and Statistics. Aug 1721, 2020, Seoul, South Korea.
 2020 Workshop New Developments in Econometrics and Time Series. Oct 12, 2020, Renne, France.
Teaching
 Instructor, STAT 652653, Rutgers, Fall 2019/Spring 2020.
 Instructor, STAT 653, Rutgers, Spring 2019.
 Instructor, STAT 593, Rutgers, Fall 2018.
 Instructor, STAT/MATH 491, UW, Fall 2017.