Tauhid Zaman


Tauhid Zaman


Tauhid is an Associate Professor of Operations Management at the MIT Sloan School of Management. He received his BS, MEng, and PhD degrees in electrical engineering and computer science from MIT.  

His research focuses on solving operational problems involving social network data using probabilistic models, network algorithms, and modern statistical methods.  Some of the topics he studies in the social networks space include predicting the popularity of content, finding online extremists, and geo-locating users.

His broader interests cover data driven approaches to investing in startup companies, non-traditional choice modeling, algorithmic sports betting, and biometric data.

His work has been featured in the Wall Street Journal, Wired, Mashable, the LA Times, and Time Magazine.



"Finding Extremists in Online Social Networks."

Klausen, Jytte, Christopher Marks, and Tauhid Zaman. Operations Research. Forthcoming.

"Opinion Dynamics with Stubborn Agents."

Hunter, D. Scott, and Tauhid Zaman, MIT Sloan Working Paper 5508-18. Cambridge, MA: MIT Sloan School of Management, July 2018.

"Detecting Influence Campaigns in Social Networks Using the Ising Model."

des Mesnards, Nicolas Guenon, and Tauhid Zaman, MIT Sloan Working Paper 5509-18. Cambridge, MA: MIT Sloan School of Management, May 2018.

"Penetrating a Social Network: The Follow-back Problem."

Que, Fanyu, Krishnan Rajagopalan, and Tauhid Zaman, Working Paper. 2018.

"Finding Online Extremists in Social Networks."

Zaman, Tauhid. Presentation, Yale Institute for Network Science Distinguished Lecturer Series, New Haven, Connecticut. October 2017.

"Data-Driven Portfolios Power ‘Home-Run’ Exits in MIT Study."

Alexander Davis. The Wallstreet Journal, August 2017.

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