Dr. Satish V. Ukkusuri
Satish V. Ukkusuri, professor and director at the Lyles School of Civil Engineering at Purdue University, presented a seminar on “Convergence of Networks, Smarter (Autonomous) Transportation Technologies and Big Data: Recent Advances,” as part of the C2SMART Distinguished Speaker Series.
Over the last few years, we have seen a convergence of technology, data, analytics and new modeling approaches in transportation systems. This trend is expected to continue with rapid advances in technology, growth of connected and self-driving cars/communities and our ability to collect high velocity spatio-temporal data. In the transportation network modeling community, many investigations have explored the potential of these technologies, especially as they relate to smarter mobility in cities. With the rapid convergence of these technologies, there is a need to develop new modeling frameworks and advance opportunities that exist in this space. This talk will present ongoing research on how network science approaches, data driven techniques and connected/autonomous vehicles are (re) shaping the smart mobility arena. This talk will discuss the speaker’s experience with various big data sources (taxi cab, social media, cell phone, camera data, etc), new network modeling approaches and autonomous vehicle models for making cities smarter and resilient.
Dr. Satish V. Ukkusuri is a Professor in the Lyles School of Civil Engineering at Purdue University since July 2014 where he teaches courses in transportation systems and freight and logistics planning. Previously, he was an Associate Professor at Purdue University from 2009-2014 and on the faculty of the Department of Civil and Environmental Engineering at the Rensselaer Polytechnic Institute from August 2005 – August 2009. Dr. Ukkusuri is a member of the Transportation and Infrastructure group at Purdue. Dr. Ukkusuri is a co-lead of the Building Sustainable Communities cluster hire at Purdue University with a goal of hiring seven faculty in this interdisciplinary area.