- Visiting Professor, Sasin School of Management
- Associate Professor of Operations Management, MIT Sloan School of Management
- Yale School of Management – Associate Professor of Operations Management
- MIT Sloan School of Management – KDD Career Development Professor in Communications and Technology; Associate Professor; Assistant Professor of Operations Management
- The Wharton School – Post-doctoral Researcher
Social Media Information Operations, Generative AI, National Security, Sports Analytics
- Sigmetrics Test of Time Award: Rumors in a Network: Whos the Culprit?, (2020)
- INFORMS Conference on Service Science Best Conference Paper Award: Optimal Dispatch in Emergency Service System via Reinforcement Learning (2020)
- INFORMS Social Media Analytics Best Student Paper Award: Detecting Influence Campaigns in Social Networks Using the Ising Model (2018)
- INFORMS Social Media Analytics Best Student Paper Award Runner Up: Time Varying Opinion Dynamics with Limited Verbalisation in the Presence of Stubborn Agents (2018)
- INFORMS Social Media Analytics Best Student Paper Award: Finding Online Extremists in Social Networks (2016)
- M. Mosleh, Q. Yang, T. Zaman, G. Pennycook, and D. Rand, “Differences in misinformation sharing can lead to politically asymmetric sanctions.” to appear in Nature, 2024
- Y.S. Chen and T. Zaman. “Shaping opinions in social networks with shadow banning.” Plos One 19 (3): e0299977, 2024.
- C. Martel, M. Mosleh, Q. Yang, T. Zaman and D. Rand (2024). “Blocking of counter-partisan accounts drives political assortment on Twitter.” PNAS Nexus 3(5) (2024): 161.
- K. Qureshi and T. Zaman, “Social media engagement and cryptocurrency performance.” Plos One 18 (5): e0284501, 2023.
- M. Rossetti and T. Zaman, “Bots, disinformation, and the first impeachment of US President Donald Trump.” Plos One, 18 (5): e0283971, 2023.
- C. Marks and T. Zaman, “Building a location-based set of social media users.” Operations Research 70 (6), 3090-3107 2022.
- D. Scott Hunter and T. Zaman, “Optimizing opinions with stubborn agents.” Operations Research 70 (1), 1-22, 2022.
- Z. el Hjouji, N. Guenon des Mesnards, D. Scott Hunter and T. Zaman, “Detecting bots and assessing their impact in social networks.” Operations Research 70 (1), 1-22, 2022.
- Q. Yang, K. Qureshi, and T. Zaman, “Mitigating the Backfire Effect Using Pacing and Leading.”, Proceedings of the Tenth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2021, 10, pp. 156-165. Springer International Publishing, 2021.
- J. Klausen, C. Marks, and T. Zaman, “Finding online extremists in social networks.” Operations Research 66 (4), 957-976, 2018. (Also appeared in ORMS Editor’s Cut: Military O.R., volume 12, 2018)
- D. Shah and T. Zaman, “Finding rumor sources on random trees.” Operations Research 64 (3), 736-755, 2016.
- S. Ozturkcan, N. Kasap, M. Cevik, and T. Zaman. “Tracking social protests with Twitter: an analysis of the Gezi Park demonstrations.” Communications of the ACM, 2015.
- T. Zaman, E. B. Fox, and Eric T. Bradlow, “A Bayesian approach for predicting the popularity of tweets.” Annals of Applied Statistics, 8 (3), 1583-1611, 2014.
- S. Bhamidi, J. M. Steele, and T. Zaman, “Twitter event networks and the superstar model.” Annals of Applied Probability, 25 (5), 2462-2502, 2014.
- D. Shah and T. Zaman, “Rumors in a network: whos the culprit?” IEEE Transactions on Information Theory, 57 (8), 5163-5181, 2011. D. Shah and T. Zaman, “Detecting sources of computer viruses in networks: theory and experiment.” Proceedings of the ACM SIGMETRICS international conference on Measurement and modeling of computer systems, 203-214, 2010.
- T. Zaman, R. Herbrich, J. Van Gael, and D. Stern, “Predicting information spreading in Twitter.” NIPS Workshop on computational social science and the wisdom of crowds Vol. 104, No. 45, pp. 17599-601, 2010.
- T. Zaman, X. Guo, and R.J. Ram, “Semiconductor waveguide isolators.” Journal of Lightwave Technology (invited paper), 26 (2), 291-301, 2008.
- T. Zaman, X. Guo, and R. J. Ram, “Faraday rotation in an InP waveguide.” Applied Physics Letters, 90 (2), 023514, 2007.
- T. Zaman, X. Guo, and R. J. Ram, “Proposal for a polarization independent integrated optical circulator,” IEEE Photonics Technology Letters, 18 (12), 1359-1361, 2006.
- T. Tepper, F. Ilievski, C. A. Ross, T. Zaman, R. J. Ram, S. Y. Sung, and B. J. H. Stadler, “Magnetooptical properties of iron oxide films.” Journal of Applied Physics, 93(10), 6948-6950.
- R. Ascazubi, O. C. Akin, T. Zaman, R. Kersting, and G. Strasser, “Dephasing in modulation-doped quantum structures probed by THz time-domain spectroscopy.” Applied Physics Letters, 81(23), 4344-4346, 2002.
- ONR Grant: ACERT (Phase 1). (2017)
- DARPA SBIR Program Grant: DEEPSONG (Phase 1). (2017)
- DARPA SBIR Program Grant: Group Forecasting (Phase 2). (2014)
- FDA BAA -13-00119 Grant (Phase 1). (2013)
- DARPA SBIR Program Grant: Group Forecasting (Phase 1). (2013)
- Accenture and MIT Alliance in Business Analytics Grant. (2013)
- “Digital Bridge: State Department debrief Twitter censorship Brussels security pitch”, Politico, June 22, 2023.
- “Social Media Offers Crypto Investors Real-Time Insights”, Politico, Sep 22, 2023.
- “Experts trying to build perfect March Madness bracket offer tips for choosing your own”, CBS News, March 16,2023
- “Musk says Twitter is biased against conservatives, facts say otherwise”, The Hill, April 20, 2022
- “Data-Driven Portfolios Power Home-Run Exits in MIT Study”, The Wallstreet Journal, August 7th, 2016.
- “Does the Amount You Sweat Predict Your Job Performance?”, The Wallstreet Journal, October 27th, 2016.
- “MIT Savant Can Predict How Many Retweets You Will Get”, Wired, May 30th, 2013.
- “MIT Algorithm Can Predict How Popular a Tweet Will Be”, Los Angeles Times, May 29th, 2013.