Milad Bakhshizadeh, Ph.D. in Statistics 2021 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. |
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Rishabh Dudeja, Ph.D. in Statistics 2021 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. You can find more information about me in my CV.
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Yuling Yao, Ph.D. in Statistics 2021 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. |
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Adji Bousso Dieng, Ph.D. in Statistics 2020 Career Highlights:
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Yixin Wang, Ph.D. in Statistics 2020 “My research centers around developing practical and trustworthy machine learning algorithms for large datasets that can enhance scientific understandings and inform daily decision-making.” |
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Morgane Austern, Ph.D. in Statistics 2019 “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.” |
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DAVID A. HIRSHBERG |
David A. Hirshberg, Ph.D. in Statistics 2018 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 “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.” |
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Swupnil Sahai, Ph.D. in Statistics 2018 “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.”
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Phyllis Wan, Ph.D. in Statistics 2018 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!
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Benjamin Bloem-Reddy, Ph.D. in Statistics 2017 I work on problems in statistics and machine learning, with an emphasis on probabilistic approaches. Some recent examples:
I also collaborate with researchers in the sciences on statistical problems arising in their research.
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Rohit Kumar Patra, Ph.D. in Statistics 2016 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.
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Michael Agne, Ph.D. in Statistics 2015 Analytics in the Life Sciences practice -Predictive modeling in big data sets: patient finding, key driver analysis, forecasting
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Vincent Dorie, Ph.D. in Statistics 2014 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.
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Kristen L. Gore, Ph.D. in Statistics 2014 Statistician and certified six sigma black belt with teaching experience in industry and academia. Passionate advocate for STEM outreach & diversity and inclusion.
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Radka Hakl Picková, Ph.D. in Statistics 2013 Research focus: Stochastic Analysis and Mathematical Finance |
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GONGJUN XU |
Gongjun Xu, Ph.D. in Statistics 2013 Research Interests:
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Tony Sit , Ph.D. in Statistics 2012 Research Interests: Survival analysis; Quantile regression; Network modelling; Risk management
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![]() Amal Moussa |
Amal Moussa, Ph.D. in Statistics 2011 “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 Career Highlights
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Tyler H. McCormick, Ph.D. in Statistics 2011
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Georgios Fellouris, Ph.D. in Statistics 2010 Research Interests: Sequential hypothesis testing; Quickest change detection; Sequential parameter estimation; Sequential design. |
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Rachel Schutt, Ph.D. in Statistics 2009 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). |
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Kobi Abayomi, Ph.D. in Statistics 2008 Career Highlights:
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FANESCA YOUNG |
Fanesca Young, Ph.D. in Statistics 2005 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. |
Placements of Recent Alumni
Name | Placement | Year |
Rohit Patra | University of Florida | 2016 |
Benjamin Reddy | University of British Columbia | 2017 |
Haolei Weng | Michigan State University | 2017 |
Christopher Dolan | Touchpoint Software | 2018 |
Feihan Lu | Upstart | 2018 |
Gonzalo Esteban Mena | University of Oxford | 2018 |
Leo Neufcourt | UC Santa Barbara | 2018 |
Lisha Qiu | Virtu Financial | 2018 |
Phyllis Wan | Erasmus School of Economics | 2018 |
Susanna Makela | 2018 | |
Swupnil Sahai | SwingVision,Mangolytics | 2018 |
Timothy Jones | Bank of America | 2018 |
Yang Kang | D.E. Shaw | 2018 |
Adji Bousso Dieng | Princeton University | 2019 |
Florian Stebegg | Two Sigma | 2019 |
Gabriel Loazia -Ganem | Layer 6 AI | 2019 |
Jin Hyung (Peter) Lee | CTRL-LABS/Facebook | 2019 |
Jing Wu | Point72 | 2019 |
Jonathan Auerbach | George Mason University | 2019 |
Kashif Yousuf | 2019 | |
Morgane Austern | Harvard University | 2019 |
Shuaiwen Wang | 2019 | |
Yayun (Lydia) Hsu | NBC Universal | 2019 |
Yixin Wang | University of Michigan | 2019 |
Guanhua Fang | Baidu Research | 2020 |
Hok Kan (Brian) Ling | Queens University | 2020 |
Milad Bakhshizadeh | Stanford University | 2020 |
Promit Ghosal | MIT | 2020 |
Rishabh Dudeja | Harvard University | 2020 |
Sihan Huang | Squarepoint Capital | 2020 |
Wenda Zhou | New York University | 2020 |
Zhi Wang | Citadel Securities | 2021 |
Miguel Angel Garrido Garcia | Princeton University | 2021 |
Chaoyu Yuan | Upstart | 2021 |
Ding Zhou | Two Sigma | 2021 |
For more information on MA Statistics Alumni, see here.