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Data Science Conference 2020

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Temple University’s Fox School of Business and Wells Fargo Equity Finance hosted the inaugural Data Science Conference in November 2020. Faculty from leading universities participated in a series of panels exploring technical issues relevant to today’s unprecedented environment. The conference explored aspects of statistical machine learning, deep learning and AI with an emphasis on tools and ideas that are relevant to systematic investing methodologies.


Thursday, November 19, 2020 Agenda

Leveraging COVID-19 data for quantitative forecasting

11:00 am – 12:30 pm EDT

In these unprecedented times quantitative investors are asking what data are available for tracking the spread and impact of COVID-19, from different sources, issues about data curation and reliability, and issues that arise when developing meta-analysis of data from different sources for the purposes of forecasting and of identifying causal relations.

Deep-learning & AI: Has the revolution happened yet?

12:30 pm – 2:00 pm EDT

In Tech, Finance, and Big Pharma alike, techniques from machine learning, to artificial intelligence, to data science, promise to revolutionize how operations are run, forecasts are made, and vaccines discovered. Several CEOs have been warning the public about AI taking over the world. Despite all the hype, real results have been lagging. This panel will discuss a realistic role for techniques from machine learning to data science, and what we can expect they will bring in the near and distant future.

Statistical machine learning tools and systematic investing

2:00 pm – 3:30 pm EDT

A review of statistical and machine learning ideas and methodologies that promise to impact the practice of systematic investing.

Content Library

1st Panel: Leveraging COVID-19 data for quantitative forecasting



Ronald Anderson

Fox School of Business, Temple University


John Leone

Wells Fargo Equity Finance

Edoardo M. Airoldi

Fox School of Business, Temple University

Jun Liu

Harvard University

Professor of Statistics

Emmanuel Candes

Stanford University

Professor of Mathematics and Statistics, and The Barnum-Simons Chair in Mathematics and Statistics

David Madigan

Northeastern University

Provost and Professor of Statistics

Nicholas Christakis

Yale University

Sterling Professor of Social and Natural Science, Internal Medicine & Biomedical Engineering

Donald Rubin

Temple University and Harvard University

Professor of Statistics, Temple University, and Emeritus Professor of Statistics at Harvard University

David Donoho

Stanford University

Professor of Statistics, and Anne T. and Robert M. Bass Professor of Humanities and Sciences

Panos Toulis

University of Chicago Booth

Assistant Professor of Statistics

Michael Jordan

UC Berkeley

Professor of Statistics and Computer Science, and Pehong Chen Distinguished Professor

Bin Yu

UC Berkeley

Professor of Statistics and Chancellor’s Distinguished Professor

Michael Kohler

Technical University of Darmstadt

Professor at the Department of Mathematics