I am a computational social scientist with an interest in large-scale data intensive methods for improving and scaling marketing research. Majority of my current research applies combined methods from marketing, network and data science for mining user perception of brands using publicly available social media data. I am also working with influencer datasets on Twitter and Instagram to understand social activism and build network-based recommender systems. My academic training includes a range of research methods, including data analytics, network analyses, econometrics, survey-based methods, machine learning, text analytics, deep learning, and causal inference.
Graduate students – I am currently supervising Miss Nina Dao (MBA Candidate at Gene Rainbolt Graduate School of Business ) on her graduate research assignment at The University of Oklahoma.
Contact – pmal @ ou dot edu
Education and Employment
- Assistant Professor, Michael F. Price College of Business, University of Oklahoma, 2021 – Present
- Postdoctoral Scholar in Quantitative Marketing, Northwestern University, 2021
- PhD in Information Systems, University of Illinois at Chicago – 2020
- Msc in Business Analytics, University of Manchester – 2015
- Bsc Physics Honors, Miranda House – 2013