Tel Aviv University · Department of Industrial Engineering
Sensing, understanding, and shaping human behavior
through Artificial Intelligence and Data Science
Principal Investigator
Erez Shmueli is an Associate Professor in the Department of Industrial Engineering at Tel Aviv University, where he heads the Big Data Lab. He co-initiated and served as the founding Head of TAU's undergraduate Data Science program. He is a Research Affiliate at the MIT Media Lab (Human Dynamics Group), a member of the Blavatnik Interdisciplinary Cyber Research Center (ICRC), and a researcher at the TAU Epidemic Research Center. As of 2025, he holds a Visiting Professorship at Stanford University's Human-Centered AI Institute (HAI).
His research focuses on developing AI models that leverage real-world data from smartphones and wearable devices to sense, understand, and shape human behavior — with a growing emphasis on health and wellbeing. His work spans machine learning and fairness, privacy-preserving computation, network science, behavioral sensing, and digital health. Research from his lab has been featured in The New York Times, Harvard Business Review, and IEEE Spectrum.
Beyond academia, Prof. Shmueli co-founded Wizermed, a digital health startup using continuous smartwatch monitoring to predict migraine attacks 24 hours in advance. He holds multiple patents and has secured over $3.7 million in research funding.
What We Do
We develop computational methods that extract actionable insights from large, complex, real-world datasets — bridging AI, social science, and medicine.
Developing novel ML algorithms for prediction, fairness, and prescriptive analytics — with a focus on ensuring ethical and unbiased AI across social and organizational settings.
Leveraging smartphones and wearable devices to continuously monitor physiological and behavioral signals — enabling real-time detection of health conditions, trauma responses, and wellbeing trends at scale.
Mining structure and dynamics from large-scale networks and behavioral datasets. Designing privacy-preserving protocols and understanding collective phenomena from digital traces.
Latest
A study of 4,806 smartwatch users over three years, published in PLOS Mental Health, found physiological early-warning markers of PTSD in people indirectly exposed to the October 7, 2023 attacks — with PTSD prevalence reaching 22–36% at 7–8 weeks post-event.
Read paper →Published in Communications Medicine (Nature Portfolio), this study used smartwatches and mobile apps to monitor Israeli civilians' physiological wellbeing in real time during the May 2021 Gaza conflict — demonstrating scalable population-level health surveillance using consumer devices.
Read paper →Prof. Shmueli co-founded Wizermed, a digital health startup that uses continuous smartwatch signal monitoring to predict migraine attacks a full day ahead. The company raised $800K pre-seed funding from eHealth Ventures and is developing the first AI-powered migraine early-warning system.
Learn more →Our People
We are a diverse group of researchers united by curiosity and rigor. The lab is actively recruiting outstanding PhD students and postdocs — reach out if you are interested.
Principal Investigator
Tel Aviv University · Stanford HAI (Visiting) · MIT Media Lab (Affiliate)
PhD Researcher
Network Science · Complex Systems
Our Work
A selection of recent and highly cited work. See Google Scholar for the complete list of 80+ publications.
Edited Book
Machine Learning for Data Science Handbook: Data Mining and Knowledge Discovery Handbook (3rd ed.)
Springer, 2023
Social media impact and smartwatch monitoring: Prevalence and early markers of PTSD and anxiety following mass traumatic events
PLOS Mental Health, 2(9):e0000195
Real-time sensing of war's effects on wellbeing with smartphones and smartwatches
Communications Medicine (Nature Portfolio)
Higher sensitivity monitoring of reactions to COVID-19 vaccination using smartwatches
npj Digital Medicine, Vol. 5
Employees recruitment: A prescriptive analytics approach via machine learning and mathematical programming
Decision Support Systems
Timing Matters: Influence Maximization in Social Networks Through Scheduled Seeding
IEEE Transactions on Computational Social Systems
Secure Multi-Party Protocols for Item-Based Collaborative Filtering
ACM RecSys '17 — 11th ACM Conference on Recommender Systems
Sensing, Understanding, and Shaping Social Behavior
IEEE Transactions on Computational Social Systems, Vol. 1, No. 1
Get in Touch
Interested in collaboration, joining the lab, or learning more about our research? We'd love to hear from you.
Department of Industrial Engineering
Tel Aviv University
Tel Aviv 6997801, Israel
We are actively recruiting outstanding PhD students and postdoctoral researchers. Send your CV and a brief statement of interest.