headshot

Amin Rahimian

Assistant Professor
RAHIMIAN@pitt.edu
aminrahimian.github.io @aminrahimian Google Scholar Industrial Engineering

overview

Dr. Rahimian joined Pitt IE in the fall of 2020. Prior to that, he was a postdoc with joint appointments at MIT Institute for Data, Systems, and Society (IDSS) and MIT Sloan School of Management. He received his PhD in Electrical and Systems Engineering from the University of Pennsylvania, and Master’s in Statistics from Wharton School. Broadly speaking his works are at the intersection of networks, data, and decision sciences. He borrows tools from applied probability, statistics, algorithms, as well as decision and game theory. Some of his current focus is on the challenges of inference and intervention design in complex, large-scale sociotechnical systems, with applications ranging from online social networks, e-commerce and collective decision/action platforms to modern civilian cyberinfrastructure and future battlefields. He is especially interested in the critical role that information plays in the operation of sociotechnical institutions and its societal implications, including on diversity, fairness, and privacy. He has served on the program committee of the 2021 ACM Economics and Computation conference and is currently serving on the advisory council of the vaccine confidence fund (a new industry alliance) as well as the program committee of the 2022 IISE annual conference (as the operations research track co-chair). He has published in the Proceedings of the National Academy of Sciences, the Operations Research journal, the Automatica journal, and several IEEE Transactions. At Pitt he teaches Stochastic Processes (IE 2084) and Design of Experiments (IE 1072).

about

(2021) Most Inspiring Research Paper Award at the ACM Collective Intelligence Conference.

Hązła, J., Jadbabaie, A., Mossel, E., & Rahimian, M.A. (2021). Bayesian Decision Making in Groups is Hard. Operations Research, 69(2), 632-654.Institute for Operations Research and the Management Sciences (INFORMS). doi: 10.1287/opre.2020.2000.

Moehring, A., Collis, A., Garimella, K., Rahimian, M.A., Aral, S., & Eckles, D. (2021). Surfacing norms to increase vaccine acceptance. Available at SSRN 3782082.Center for Open Science. doi: 10.31234/osf.io/srv6t.

Almaatouq, A., Rahimian, M.A., Burton, J., & Alhajri, A. (2020). When social influence promotes the wisdom of crowds. Center for Open Science. doi: 10.31234/osf.io/f5ky3.

Holtz, D., Zhao, M., Benzell, S.G., Cao, C.Y., Rahimian, M.A., Yang, J., Allen, J., Collis, A., Moehring, A., Sowrirajan, T., Ghosh, D., Zhang, Y., Dhillon, P.S., Nicolaides, C., Eckles, D., & Aral, S. (2020). Interdependence and the cost of uncoordinated responses to COVID-19. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 117(33), 19837-19843.Proceedings of the National Academy of Sciences. doi: 10.1073/pnas.2009522117.

Eckles, D., Esfandiari, H., Mossel, E., & Rahimian, M.A. (2019). Seeding with Costly Network Information. SSRN Electronic Journal.Elsevier BV. doi: 10.2139/ssrn.3386417.

Eckles, D., Mossel, E., Rahimian, M.A., & Sen, S. (2019). Long ties accelerate noisy threshold-based contagions. SSRN Electronic Journal.Elsevier BV. doi: 10.2139/ssrn.3262749.

Banerjee, S., Mukherjee, N., & Rahimian, A. (2021). Deep Learning for Simulation-based Bayesian Inference of Hidden Parameters in Online Reputation Systems. In Machine Learning for Consumers and Markets.

Burton, J., Almaatouq, A., Rahimian, A., & Hahn, U. (2021). Rewiring the Wisdom of the Crowd. In Proceedings of the Annual Meeting of the Cognitive Science Society, 43.

Burton, J., Hahn, U., Almaatouq, A., & Rahimian, A. (2021). Algorithmically Mediating Communication to Enhance Collective Decision-Making in Online Social Networks. In ACM Collective Intelligence Conference.

Eckles, D., Esfandiari, H., Mossel, E., & Rahimian, A. (2021). Seeding with Costly Network Information. In Summer Institute in Competitive Strategy (SICS).Haas School of Business, UC Berkeley.

Moehring, A., Collis, A., Garimella, K., Rahimian, A., Aral, S., & Eckles, D. (2021). Surfacing Norms to Increase Vaccine Acceptance: Evidence From an International Experiment. In INFORMS Marketing Science.

Eckles, D., Esfandiari, H., Mossel, E., & Rahimian, M.A. (2019). Seeding with Costly Network Information. In Proceedings of the 2019 ACM Conference on Economics and Computation, (pp. 421-422).ACM. doi: 10.1145/3328526.3329651.

Rahimian, M.A., Jadbabaie, A., & Mossel, E. (2017). Complexity of Bayesian belief exchange over a network. In 2017 IEEE 56th Annual Conference on Decision and Control (CDC), 2018-January, (pp. 2611-2616).IEEE. doi: 10.1109/cdc.2017.8264038.

Preciado, V.M., & Rahimian, M.A. (2016). Controllability Gramian Spectra of Random Networks. In 2016 American Control Conference (ACC), 2016-July, (pp. 3874-3879).IEEE. doi: 10.1109/acc.2016.7525517.

Rahimian, M.A., & Jadbabaie, A. (2016). Distributed Estimation and Learning over Heterogeneous Networks. In 2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton), (pp. 1314-1321).IEEE. doi: 10.1109/allerton.2016.7852386.

Rahimian, M.A., & Jadbabaie, A. (2016). Learning without Recall from actions of neighbors. In 2016 American Control Conference (ACC), 2016-July, (pp. 1060-1065).IEEE. doi: 10.1109/acc.2016.7525055.

Rahimian, M.A., & Jadbabaie, A. (2016). Naive social learning in Ising networks. In 2016 American Control Conference (ACC), 2016-July, (pp. 1088-1093).IEEE. doi: 10.1109/acc.2016.7525060.

Rahimian, M.A., & Jadbabaie, A. (2016). Group decision making and social learning. In 2016 IEEE 55th Conference on Decision and Control (CDC), (pp. 6783-6794).IEEE. doi: 10.1109/cdc.2016.7799314.

Rahimian, M.A., & Jadbabaie, A. (2015). Learning without recall in directed circles and rooted trees. In 2015 American Control Conference (ACC), 2015-July, (pp. 4222-4227).IEEE. doi: 10.1109/ACC.2015.7171992.

Rahimian, M.A., & Jadbabaie, A. (2015). Learning without Recall: A Case for Log-Linear Learning. In IFAC-PapersOnLine, 28(22), (pp. 46-51). doi: 10.1016/ifacol.2015.10.305.

Rahimian, M.A., & Preciado, V.M. (2015). Failure detection and isolation in integrator networks. In 2015 American Control Conference (ACC), 2015-July, (pp. 677-682).IEEE. doi: 10.1109/acc.2015.7170813.

Rahimian, M.A., Shahrampour, S., & Jadbabaie, A. (2015). Learning without Recall by Random Walks on Directed Graphs. In 2015 54th IEEE Conference on Decision and Control (CDC), 54rd IEEE Conference on Decision and Control,CDC 2015, (pp. 5538-5543).IEEE. doi: 10.1109/cdc.2015.7403087.

Shahrampour, S., Rahimian, M.A., & Jadbabaie, A. (2015). Switching to learn. In 2015 American Control Conference (ACC), 2015-July, (pp. 2918-2923).IEEE. doi: 10.1109/acc.2015.7171178.

Tzoumas, V., Rahimian, M.A., Pappas, G.J., & Jadbabaie, A. (2015). Minimal actuator placement with optimal control constraints. In 2015 American Control Conference (ACC), 2015-July, (pp. 2081-2086).IEEE. doi: 10.1109/acc.2015.7171040.

Enyioha, C., Rahimian, M.A., Pappas, G.J., & Jadbabaie, A. (2014). Controllability and fraction of leaders in infinite networks. In 53rd IEEE Conference on Decision and Control, 2015-February(February), (pp. 1359-1364).IEEE. doi: 10.1109/cdc.2014.7039571.

Rahimian, M.A., Molavi, P., & Jadbabaie, A. (2014). (Non-)Bayesian learning without recall. In 53rd IEEE Conference on Decision and Control, 2015-February(February), (pp. 5730-5735).IEEE. doi: 10.1109/cdc.2014.7040286.

Rahimian, M.A., & Aghdam, A.G. (2013). Structural controllability of multi-agent networks: Importance of individual links. In 2013 American Control Conference, (pp. 6871-6876).IEEE. doi: 10.1109/acc.2013.6580918.

Rahimian, M.A., & Preciado, V.M. (2013). Detection and isolation of link failures under the agreement protocol. In 52nd IEEE Conference on Decision and Control, (pp. 7364-7369).IEEE. doi: 10.1109/cdc.2013.6761058.

Rahimian, M.A., Ajorlou, A., Tutunov, R., & Aghdam, A.G. (2013). Identifiability of links and nodes in multi-agent systems under the agreement protocol. In 2013 American Control Conference, (pp. 6853-6858).IEEE. doi: 10.1109/acc.2013.6580915.

Rahimian, M.A., & Aghdam, A.G. (2012). Structural controllability of multi-agent networks. In Proceedings of the 2012 ACM Research in Applied Computation Symposium on - RACS '12, (pp. 221-226).ACM Press. doi: 10.1145/2401603.2401652.

Rahimian, M.A., Ajorlou, A., & Aghdam, A.G. (2012). Characterization of link failures in multi-agent systems under the agreement protocol. In 2012 American Control Conference (ACC), (pp. 5258-5263).IEEE. doi: 10.1109/acc.2012.6314875.

Rahimian, M.A., Ajorlou, A., & Aghdam, A.G. (2012). Detectability of multiple link failures in multi-agent systems under the agreement protocol. In 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), (pp. 118-123).IEEE. doi: 10.1109/cdc.2012.6426051.

Rahimian, M.A., Asadi, M.M., & Aghdam, A.G. (2012). Characterization of structured and unstructured decentralized fixed modes using transfer matrices. In 2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE).IEEE. doi: 10.1109/ccece.2012.6335000.

Rahimian, M.A., & Aghdam, A.G. (2011). Structural controllability of multi-agent systems subject to simultaneous failure of links and agents. In IEEE Conference on Decision and Control and European Control Conference, (pp. 1443-1448).IEEE. doi: 10.1109/cdc.2011.6160852.

ParandehGheibi, A., Rahimian, M.A., Akhaee, M.A., Ayremlou, A., & Marvasti, F. (2010). Compensating for distortions in interpolation of two-dimensional signals using improved iterative techniques. In 2010 17th International Conference on Telecommunications, (pp. 929-934).IEEE. doi: 10.1109/ictel.2010.5478860.

Rahimian, M.A., & Tavazoei, M.S. (2010). Comparing the stability regions for fractional-order PI controllers and their integer-order approximations. In 49th IEEE Conference on Decision and Control (CDC), (pp. 720-725).IEEE. doi: 10.1109/cdc.2010.5717715.

Rahimian, M.A., & Ohyama, S. (2009). Compensating for the latency of data acquisition for localization in mobile wireless sensor networks. In 2009 International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), (pp. 7-12).IEEE. doi: 10.1109/issnip.2009.5416829.