معرفی
Dootika Vats is an Associate Professor in the Department of Mathematics & Statistics at Indian Institute of Technology Kanpur (IIT Kanpur). She earned her PhD in Statistics from the University of Minnesota, Twin-Cities, and her research focuses on advancing Monte Carlo and Bayesian computational methods, especially Markov chain Monte Carlo diagnostics.
Education:
- PhD, Statistics, University of Minnesota, Twin-Cities, Feb 2017
- MS, Statistics, University of Minnesota, Twin-Cities, Nov 2016
- MS, Statistics, Rutgers University, New Brunswick, May 2012
- BA (honors), Mathematics, University of Delhi, Lady Shri Ram College, May 2010
Research Interests:
Her work lies at the intersection of computational statistics and Bayesian inference, with core emphases on:
- Markov chain Monte Carlo (MCMC) methodology
- Monte Carlo variance estimation and output analysis
- Bayesian computation and diagnostics
- Geometric ergodicity and convergence rates of MCMC algorithms
Recent Publications Trend:
Across her recent articles and preprints, Dr. Vats has consistently tackled open problems in MCMC output analysis, introducing new diagnostics, optimal batch-size selection, and visualization tools that directly impact practical Bayesian computation. Her contributions bridge theoretical rigor—such as proving strong consistency of spectral variance estimators—with immediately applicable software and graphical methods.
Awards & Honors:
- Director’s Award, University of Minnesota School of Statistics, 2016
- Graduate Research Partnership Program Fellowship, Summer 2016
- Louise T. Dosdall Fellowship for Women in STEM, 2016–2017
- School of Statistics Alumni Fellowship, 2015–2016
- Martin–Buehler Fellowship in Statistics, Fall 2015
- Bernard W. Lindgren Graduate Student Teaching Award, Spring 2014
- Lynn Lin Fellowship in Statistics, Summer 2014
Teaching & Mentoring:
At IIT Kanpur she continues to teach and mentor within the statistics curriculum. Earlier, at the University of Minnesota, she served as Instructor for STAT 3011 and as a teaching assistant across multiple undergraduate and graduate courses; at Rutgers University she was a part-time lecturer in calculus and pre-calculus.
Labs & Collaboration:
While no specific lab is named, her research is computational and collaborative; she has worked with James M. Flegal, Galin L. Jones, and other leading MCMC methodologists, and her Google Summer of Code participation demonstrates engagement with the open-source statistics community.
