Lab Director, PhD, DrSc
Associate Professor Of Practice at NYU
Research Affiliate at the MIT Senseable City Lab.
Dr. Sobolevsky holds PhD (1999) and Doctor of Science habilitation degree (2009) in Mathematics. Dr. Sobolevsky teaches data science, machine learning and networks analysis and studies human behavior in urban context through its digital traces: spatio-temporal big data created by various aspects of human activity – social media, cell phone records, vehicle/vessel GPS traces, public service requests, credit card transactions and other. Authored over a 100 of research publications in top-tier journals and conferences, including Nature’s Scientific Reports, PNAS, Physical Review E, PLOS ONE and others. His applied projects on transportation modeling, trajectory mining, anomaly, pattern and vulnerability detection in temporal urban networks are supported by industrial partners and foundations including US Department Of Energy, US Department Of Transportation, National Geospatial Intelligence Agency, Lockheed Martin, Future Cities Catapult, Arcadis. His prior research at MIT was supported by Ericsson, BBVA, Orange, British Telecom, Liberty Mutual and other industrial partners.