Hane Lee

Abhishek Kantilal Tilva

Collin Andrew Cademartori

Jiajin Sun

Arnab Auddy

Alessandro Grande

Alejandra Quintos Lima

Yuling Yao

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

Before Flatiron, I earned my PhD 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."

Promit Ghosal

Yixin Wang

Morgane Austern

“I am a mathematician focused on probability and statistics problems 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

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.

Leo Neufcourt

Phyllis Wan

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!

Haolei Weng

Rohit Kumar Patra

"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 research’s main motivation is to develop 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."

Radka Hakl Picková

Research focus: Stochastic Analysis and Mathematical Finance

Tony Sit

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

Johannes Ruf

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 the 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
• PhD at Columbia Statistics = Learning insights in Statistics and Probability from an excellent, very motivated faculty and from fellow students, making friends for life and experiencing NYC.