Akhmed Umyarov received his PhD from New York University's Stern School of Business (2010) where he was honored with the Marcus Nadler Fellowship. Umyarov holds an MSc in mathematics with highest distinction from Moscow State University. His current research focuses on exploring causal reasons for human behavior in online settings by means of experiments and tools of econometrics. Prior to that he worked with predictive modeling algorithms in the context of recommendation systems. His industry experience includes serving as a quantitative researcher for Moody's Corp. on Wall Street, as a research and software engineer for Samsung Electronics in South Korea, and as a research engineer for Neurocom in Moscow.
I am fascinated with the emerging era of exploration of human behavior uncovered by the immense scale of current technologies. This scale of social technology is something qualitatively different from everything that humanity has ever experienced before. As complex as human behavior is on individual scale, on such aggregate scales, it is frequently observed to abide to certain fundamental laws that can be replicated by researchers again and again. In this sense, I am utilizing current technologies as a giant lab that lets me tease out these fundamental laws of human behavior online using tools of statistics and econometrics.
2013 Bapna R., Ramaprasad J., Shmueli G., Umyarov A. One-Way Mirrors and Weak-Signaling in Online Dating: A Randomized Field Experiment. To be submitted to Science. Working Paper.
2013 Bapna R., Ramaprasad J., Umyarov A. Completing the Virtuous Cycle between Paying for Music and Social Engagement in an Online Community: Evidence from a Randomized Trial. To be submitted to MIS Quarterly. Working Paper.
2011 Umyarov A., Tuzhilin A. Using External Aggregate Ratings for Improving Individual Recommendations. ACM Transactions on the Web. Volume 5, Number 1, February 2011, Section 3. Pages 1 – 40.
2012 Bapna R., Umyarov A. Do your friends make you pay? A randomized field experiment in online social networks. Management Science. (Under 3rd revision).