I am the Millard E. Gladfelter Professor of Statistics and Data Science, and a Professor of Finance (by courtesy), in the Fox School of Business, at Temple University. I also serve as Co-Director of the Temple Data Science Institute.

My research focuses on statistical methodology and theory for designing and analyzing randomized experiments and observational studies in complex settings, and on modeling and inferential issues that arise in analyses that leverage network data. In the past, have developed methodology to generate insights from genomics and proteomics data, and to generate signals from unstructred text data. I enjoy working on applications in the social sciences and healthcare, in the Tech industry, and in Finance.

Current research interests include:

  1. Design and analysis of experiments and observational studies in complex settings
  2. Methodology for the analysis of network data
  3. Geometry of inference in ill-posed inverse problems, including network tomography and contingency tables
  4. Approximate inference strategies for data analysis at scale
  5. Applied research in the social sciences, Tech, Finance, and golf analysics

Areas of technical interest include modeling, approximation theorems, inequalities, stochastic optimization, and geometry.

Current projects include methodology for designing and analyzing experiments, and identification strategies for causal analyses, with applications to: (1) to social healthcare in rural Honduras with the Human Nature Lab at Yale University; (2) search and display ad auctions in the tech industry with the Market Optimization Algorithms group at Google in New York City; (3) aspects of systematic trading with the Global Equities Division at Wells Fargo Securities; and (4) golf analytics. If you are interested in contributing to any of these efforts, please reach out via email and include your CV.

During normal times, you could find me at JSM, AISTATS, NIPS, ICLM, and at Atlantic Causal Inference conference.

Our work is or has been graciously supported by NSF, NIH, ONR, ARO, Microsoft, Google, Facebook, LinkedIn, Yahoo, AT&T, and other industry partners, and by Harvard and Temple Universities.