February 25, 2016
Please join us for NYU CUSP’s for a webinar in our educational research series. Learn more about a specific research topics that our faculty is leading with current students and with the City of New York. This session will be led by CUSP faculty member, Dr. Stanislav Sobolevsky. In addition, you will have the opportunity to learn more about CUSP’s MS program in Applied Urban Science & Informatics, research and career opportunities, the application process and financial aid.
A technological revolution of the past few decades resulted in the broad penetration of digital technologies into everyday life. Digital media facilitating various aspects of human activity makes them leave digital traces behind, thus increasing production of big data related to human dynamics, social interactions, shopping and other types of behavior. Numerous big datasets are now available for research purposes, creating tremendous opportunities for making cities smarter, more adaptive, livable and resilient. This comes through development of new data-powered solutions to well-known research and operational problems in different fields (including but not limited to human geography, urban planning, economics and other social sciences) based on direct digital sensing of human activity in the urban context. The relevant sources of data include cell phone call records, geo-localized social media, credit card transactions, vehicle GPS traces, public transportation as well as carpooling and bike-sharing usage data, various data from utility companies and service providers, data from personal apps and many other datasets, all opening new horizons for understanding human behavior, its laws and patterns. The presentation will give examples of research findings in that area, together with their urban applications.
Stanislav Sobolevsky is an Associate Professor of Practice at the Center for Urban Science and Progress at New York University and a Research Affiliate at the MIT Senseable City Lab. He holds a Ph.D (1999) from Grodno State University and a Doctor of Science (2009) in Mathematics from the National Science Academy of Belarus.
Dr. Sobolevsky teaches various data science courses and applies his fundamental quantitative background to studying human behavior in urban context through its digital traces: spatio-temporal big data created by various aspects of human activity. His research interests cover network science, big data analytics, modeling of complex systems and the theory of differential equations. He is the author of one monograph, two textbooks and over 50 peer-reviewed papers in mathematics, network science and mathematical modeling.
His former professional experience includes research at MIT as well as research, teaching and administrative positions at Belarusian State University and the National Academy of Sciences of Belarus. Dr. Sobolevsky received a Silver Medal winner in the 1993 and 1994 International Math Olympiads, the best research amongst young scientist award in 2000 (Belarus), President’s Foundation Fellowship awards for both Ph.D (2001) and Doctor of Science (2010) researchers, and the 2015 award for the LinkedIn Economic Graph Challenge. He also received the Best Paper award at the Academy of Science & Engineering International Conference of Data Science in 2015.