Amin Rahimian, Biosketch

Pitt IE
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Amin I am an assistant professor of Industrial Engineering at the University of Pittsburgh, where I lead the Sociotechnical Systems Research Lab and am also affiliated with the Intelligent Systems Program (ISP) and the Institute for Cyber Law, Policy, and Security (Pitt Cyber). Before joining Pitt IE in the fall of 2020, I was a postdoc with joint appointments at MIT Institute for Data, Systems, and Society (IDSS) and MIT Sloan School of Management (co-advised by Elchanan Mossel and Dean Eckles). I did my PhD in Electrical and Systems Engineering at the University of Pennsylvania (advised by Ali Jadbabaie). Broadly speaking my works are at the intersection of networks, data, and decision sciences. I borrow tools from applied probability, statistics, algorithms, as well as decision and game theory. Some of my 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 public health, modern civilian cyber-infrastructure and future warfare. I am especially interested in the critical role that information plays in the operation of sociotechnical systems and its societal implications, particularly related to privacy, fairness and information integrity (e.g., issues of social learning and spread of misinformation and other harmful content). I have served on the program committee of the 2021 ACM Economics and Computation conference, the advisory council of the 2021 vaccine confidence fund (then a new industry alliance), as well as the program committees of EAAMO'22 (Equity and Access in Algorithms, Mechanisms, and Optimization), SocialSens2022 (Special Edition on Information Operation on Social Media), 2022 IISE annual meeting (as the operations research track co-chair), 2023 ACM Economics and Computation conference, 2024 Web Conference, 2024 Privacy-Preserving Artificial Intelligence workshop (PPAI), 2024 Theory and Practice of Differential Privacy workshop (TPDP), and 2024 Annual Modeling and Simulation Conference (as the US and Canada publicity chair). I am currently serving on the program committee of the 2025 Web Conference. I have published in the Proceedings of the National Academy of Sciences, Nature Human Behaviour, Nature Communications, the Operations Research journal, Automatica journal, and several IEEE transactions and control theory journals. I also serve as reviewer/referee for PNAS, Science and Nature journals, Operations Research, Management Science and other physics, engineering, mathematics and computer science field journals as relevant to my research interests. At Pitt, I have taught Stochastic Processes (IE 2084, PhD qualifier), Statistics and Data Analysis (IE 2007, old PhD qualifier) and Advanced Topics in Operations Research (IE 3080, my focus in Fall 2023 was on probabilistic analysis of algorithms and randomized algorithms). I currently teach Foundations of Statistics (IE 2117, a new PhD qualifier), Design of Experiments and Quality Assurance (IE 1072, a required undergraduate course), as well as an undergraduate technical elective called "Data for Social Good" (IE 1171) that was developed as a Pitt Year of Data and Society initiative.

Education:

  • PhD in Electrical and Systems Engineering, University of Pennsylvania

  • Master's in Statistics, Wharton School, University of Pennsylvania

  • Master's in Systems Engineering, University of Pennsylvania

  • Master's in Electrical and Computer Engineering, Concordia University

  • Bachelor's in Electrical Engineering-Control, Sharif University of Technology

Interests and Expertise:

  • Theory and Methods:

    • Applied probability, randomized algorithms, differential privacy

    • Applied statistics, statistical decision theory, estimation, inference, forecasting and calibration

    • Probability and random processes on graphs and networks

    • Statistical and computational learning theory, distributed estimation and online learning

    • Network science, statistical analysis of networks

    • Social learning, group decision making and collective intelligence

    • Mathematical theories in social and behavioral sciences, judgment and decision making

    • Distributed systems, dynamics, and control theory

  • Applications Areas:

    • Ethical and responsible algorithm design for sociotechnical systems

    • Problems of fairness, privacy and information integrity in social networks and other sociotechnical contexts

    • Statistical methods and algorithm design for disease surveillance, biomarker discovery and phylogeny

    • Simulation modeling and statistical analysis of public health emergencies and disease of despair

    • Risk-benefit analysis and decision support in command and control, emergency response and other mission-critical applications

    • Cost-effectiveness and value of information analyses in public health, policy, disease screening and management

    • Distributed interventions in social networks, optimal social network interventions

    • Design of algorithms for social and e-commerce platforms, online marketplaces

    • Applied privacy in healthcare and social network settings

    • Applied problems in social and economic networks

Awards and Grants: