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Big Data for Urban Innovations

​Speaker: Stanislav Sobolevsky, Associate Professor of Practice at the Center for Urban Science and Progress, New York University, and Research Affiliate at the MIT Senseable City Lab.

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 on those patterns, together with their applications to three important areas – support of planning decisions, optimization of urban operations (specifically transportation) and creating new data-driven business models and solutions.

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.

More about the BigData@Chalmers initiative >>

The Centre of Excellence for Global Systems Science – CoeGSS
a European consortium of supercomputing centres, scientific institutions, businesses and NGOs
Category Seminar
Location: Catella, floor 3, Student Union Building (Kårhuset), Chalmersplatsen 1, Johanneberg
Starts: 25 October, 2016, 10:30
Ends: 25 October, 2016, 12:00

Published: Wed 21 Sep 2016. Modified: Wed 12 Oct 2016