Stanislav Sobolevsky is an Associate Professor of Practice And Director Of Urban Complexity Lab at the Center for Urban Science and Progress at New York University and a Research Affiliate at the MIT Senseable City Lab. Holds PhD (1999) and Doctor of Science habilitation degree (2009) in Mathematics. Dr. Sobolevsky teaches applied aspects of data science, machine learning and networks analysis. Research of his group studies human behavior in urban context through its digital traces: spatio-temporal big data created by various aspects of human activity, such as 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, Environment And Planning B, International Journal Of GIS, Applied Geography, IEEE Access, Studies In Applied Mathematics and others. His applied projects on transportation modeling, urban impact assessments, 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.