Milad Bakhshizadeh, Ph.D. in Statistics 2021
Current title: Postdoctoral Researcher, Stanford University

I am a postdoctoral researcher at Stanford University. I received my Ph.D. in Statistics from Columbia University (2021). I received my B.S.(2012) and M.S.(2014) in pure Mathematics from Sharif University of Technology. Please take a look at Bio page for more information.

Rishabh Dudeja, Ph.D. in Statistics 2021
Current title: Postdoctoral Researcher, Harvard University

I am a postdoctoral researcher in the Department of Statistics at Harvard University. I am fortunate to work with Prof. Subhabrata Sen and Prof. Yue Lu.

I am interested in understanding information-theoretic and computational phenomena that arise in high-dimensional statistical inference problems using tools from information theory, applied probability, and statistical physics.

Previously, I was a Ph.D. student at the Statistics Department at Columbia University, where I was fortunate to be advised by Professor Arian Maleki and Professor Daniel Hsu.

Yuling Yao, Ph.D. in Statistics 2021
Current title: Flatiron Research Fellow, at Flatiron Institute, Center for Computational Mathematics

My general research interest lies in Bayesian computation, Bayesian modeling, machine learning, and causal inference.

Before Flatiron, I earned my Ph.D. in Statistics from Columbia University in 2021 under the supervision of Andrew Gelman. Before that, I obtained my undergraduate education from Tsinghua University in Mathematics and in Economics.

My ultimate goal is to develop a scalable Bayesian workflow for open-ended real data problems. For example, some recent applications included lead fallout in Paris, arsenic diffusion in groundwater, and Covid-19 mortality in Bangladesh.

Adji Bousso Dieng, Ph.D. in Statistics 2020
Current title: Assistant Professor, School of Engineering and Applied Science, Princeton University

Career Highlights:

• Generative modeling branch of machine learning expert
• First Black female faculty member in the history of SEAS and the first Black faculty member ever in the Department of Computer Science (COS) at Princeton University
• AI Researcher at Google Brain
  

Yixin Wang, Ph.D. in Statistics 2020
Current title: LSA Collegiate Fellow, University of Michigan

“My research centers around developing practical and trustworthy machine learning algorithms for large datasets that can enhance scientific understandings and inform daily decision-making.”

Morgane Austern, Ph.D. in Statistics 2019
Current title: Assistant Professor in the Department of Statistics, Harvard University

“I am a mathematician focused on problems in probability and statistics that are motivated by machine learning. Currently, I am a postdoctoral researcher at Microsoft Research New England. I graduated with a PhD in statistics from Columbia University in 2019 where I worked in collaboration with Peter Orbanz and Arian Maleki on limit theorems for dependent and structured data.”

        DAVID A. HIRSHBERG

David A. Hirshberg, Ph.D. in Statistics 2018
Current title: Assistant Professor in Quantitative Theory & Methods Department, Emory University

I am an Assistant Professor in Emory’s Quantitative Theory & Methods Department. I work on methods for estimating causal effects from observational studies and experiments and sometimes on the R packages synthdid and grf.

Before coming to Emory, I did a PhD at Columbia with Arian Maleki and José Zubizarreta and a postdoc at Stanford with Susan Athey, Guido Imbens, and Stefan Wager. Years ago, I was a computer vision researcher in Michael Black’s group at Brown and MPI Tübingen.

Gonzalo Esteban Mena, Ph.D. in Statistics 2018
Current title: Florence Nightingale Bicentennial Fellow and Tutor in Computational Statistics and Machine Learning, University of Oxford

“I develop robust, efficient and theoretically sound statistical methodology for tackling problems in life sciences that involve data. My experience is mostly in neuroscience and digital epidemiology, but I am open to other problems as well. I am also very interested in computational statistics and machine learning per se, regardless of possible applications. In that sense, I have some experience in the computational and statistical aspects of optimal transport, and I am actively doing research in this area.”

Swupnil Sahai, Ph.D. in Statistics 2018
Current title: Co-Founder and CEO of SwingVision

“I’m Swupnil, the Co-Founder and CEO of SwingVision, a professional-grade mobile AI platform for amateur athletes, angel backed by Andy Roddick.

I’m also a Co-Instructor for Data 8: Foundations of Data Science, the fastest growing class at UC Berkeley, with 1,300+ students from across 40+ majors.

Previously, I built patent-pending AI for 3D object tracking at Tesla Autopilot.”

Phyllis Wan, Ph.D. in Statistics 2018
Current title: Assistant Professor in Statistics at the Erasmus School of Economics, Erasmus University Rotterdam.

My research interest lies in the study of complex data structures, such as networks and time series. I am especially interested in scenarios where heavy-tailed observations are present and where novel statistical tools are called for!

Benjamin Bloem-Reddy, Ph.D. in Statistics 2017
Current title: Assistant Professor of Statistics, University of British Columbia

I work on problems in statistics and machine learning, with an emphasis on probabilistic approaches. Some recent examples:

• Meaningful calibration of uncertainty in neural network models of conditional distributions and stochastic processes.
• Uses and benefits of symmetry in statistics, computation, and machine learning.
• Models and inference methods (SMC, MCMC) for evolving processes (e.g., networks) whose history is unobserved.

I also collaborate with researchers in the sciences on statistical problems arising in their research.

Rohit Kumar Patra, Ph.D. in Statistics 2016
Current title: Assistant Professor in the Department of Statistics, University of Florida.

My research centers around semiparametric/nonparametric methodology and large sample theory – efficient estimation in semiparametric models, nonparametric function estimation (with special emphasis on shape constrained estimation), likelihood and bootstrap based inference in (non-standard) parametric and nonparametric models. The main motivation of the research is in developing nonparametric procedures that are automated (free from tuning parameters) but still flexible enough to incorporate data-driven features.

My research has applications in broad areas such as genetics (multiple testing problems), economics (utility and production function estimation and binary response models), causal inference (conditional independence) and astronomy (analysis of accretion of galaxies), among other fields.

Michael Agne, Ph.D. in Statistics 2015
Current title: Associate Principal, Data Science & Analytics at Charles River Associates

Analytics in the Life Sciences practice

-Predictive modeling in big data sets: patient finding, key driver analysis, forecasting
-Sales force analysis: segmentation, projection, promotional response modeling
-Pricing and Market Access: discrete choice modeling
-Analysis at payer, physician, patient levels: hierarchical modeling
-On-site training of clients in statistical software and models

Vincent Dorie, Ph.D. in Statistics 2014
Current title: Staff Data Scientist at Code for America

Developer of statistics software with an emphasis on Bayesian nonparametrics, causal inference, and mixed models.

Focused on not-for-profit work and using data for the public good.

Kristen L. Gore, Ph.D. in Statistics 2014
Current title: Statistician, Six Sigma Black Belt at HP Inc.

Statistician and certified six sigma black belt with teaching experience in industry and academia. Passionate advocate for STEM outreach & diversity and inclusion.

Radka Hakl Picková, Ph.D. in Statistics 2013
Current title: Lecturer and Researcher, Škoda Auto University

Research focus: Stochastic Analysis and Mathematical Finance

           GONGJUN XU

Gongjun Xu, Ph.D. in Statistics 2013
Current title: Assistant Professor of Statistics, University of Michigan

Research Interests:

• Latent variable models, psychometrics

• Statistical learning and inference, high-dimensional statistics

• Semiparametric models, survival analysis

Tony Sit , Ph.D. in Statistics 2012
Current title: Associate Professor, Director, M.Sc. in Risk Management Science Programme, The Chinese University of Hong Kong

Research Interests: Survival analysis; Quantile regression; Network modelling; Risk management

Amal Moussa, Ph.D. in Statistics 2011
Current Title: Head of US Single Stocks Exotic Derivatives Trading at Goldman Sachs

“During my Ph.D. I studied contagion and systemic risk in financial networks to highlight the importance of the network structure in identifying systemic financial institutions and formulating regulatory policies.

“The Ph.D. program offered me the possibility to work with experts in the fields of Statistics and Financial Mathematics through a diverse range of classes and research projects, and most importantly gave me the opportunity to meet and collaborate with amazing classmates and faculty.”

Johannes Ruf, Ph.D. in Statistics 2011
Current title: Professor at the Department of Mathematics, London School of Economics

Career Highlights

• First Annual Morgan Stanley Prize for Excellence in Financial Markets (dissertation prize)
• Bruti-Liberati Fellowship: For visiting the Economics and Finance Department of University of Technology, Sydney and for giving the Bruti-Liberati Lecture at the QMF Conference (December 2013).
• Senior Research Fellow, Oxford-Man Institute, University of Oxford, 2011-2014
• Ph.D. at Columbia Statistics = Learning insights in Statistics and Probability from an excellent, very motivated faculty and from fellow students, making friends for life, experiencing NYC.

Tyler H. McCormick, Ph.D. in Statistics 2011
Current title: Associate Professor of Statistics & Sociology, Senior Data Science Fellow, University of Washington
 
 Career Highlights:

• 2019 recipient of the NIH Director’s New Innovator Award
• NIH K01 Career Development Award
• US Army Young Investigator Program Award
• Google Faculty Award

Georgios Fellouris, Ph.D. in Statistics 2010
Current title: Associate Professor, Department of Statistics, University of Illinois at Urbana-Champaign

Research Interests:

Sequential hypothesis testing; Quickest change detection; Sequential parameter estimation; Sequential design.
Decision making under communication constraints.
Educational measurement and cognitive assessment.

Rachel Schutt, Ph.D. in Statistics 2009
Current title: Managing Director at BlackRock

Rachel Schutt was the Chief Data Scientist of News Corp where she oversaw the company-wide data strategy as an executive on the senior technology leadership team. There she established the company’s first data science team for Dow Jones, the Wall Street Journal, and other brands. Schutt was named a World Economic Forum Young Global Leader in 2015 and is on the 2014 Crain’s New York Business 40 under 40 list.

While at Google Research, Schutt was part of the machine learning group in New York and holds patents based on her work in social networks, large data sets, experimental design, and machine learning.

Schutt is on the advisory board for Harvard’s Institute for Applied Computational Science (IACS).

Kobi Abayomi, Ph.D. in Statistics 2008
Current title: Senior Vice President of Analytics at Warner Music Group

Career Highlights:

• Completed and published innovative work for clients such as the World Bank, United Nations, the Government of Ecuador, and the Innocence Project.

FANESCA YOUNG

Fanesca Young, Ph.D. in Statistics 2005
Current title: Head, Global Systematic Equities, GIC

Fanesca leads the Global Systematic Equities team at GIC and she is responsible for the management of long-only, active extension and market neutral systematic equity investments.  Prior to joining GIC, Fanesca was a Principal at Los Angeles Capital Management and served as Managing Director and Director of Quantitative Research, where she oversaw the firm’s proprietary stock selection model and supervised execution of technical methodologies.  Fanesca serves on the editorial board of the Financial Analyst Journal and the Journal of Systematic Investing.  She received her doctorate in Statistics from Columbia University and is a CFA charterholder.