Title: Scalable Cluster Assessment and Clustering for Big Data and their Smart city Application
Speaker: Dr. Punit Rathore, Postdoctoral Researcher in Senseable City Lab at Massachusetts Institute of Technology (MIT), Cambridge, USA.
Day, Date and Time: Thursday, 18th March 2021, 9.30 AM to 10.30 AM
Abstract of the talk: Everyday an abundant amount of data is generated from various sources such as Internet of Things (IoT) networks, smartphones, and social network activities. Making sense of such an unprecedented amount of data is essential for many businesses, services and almost every smart city domain such as health care, transportation, finance, and energy sectors. The data generated from these domains are mostly unlabeled, anomalous, spatio-temporal, streaming, and/or high-dimensional, which makes their interpretation challenging to create useful knowledge. Therefore, scalable and efficient machine learning algorithms are required to manage and extract useful information from big data.
In this talk, Dr. Punit Rathore will discuss his research work on "scalable cluster assessment and clustering, and their smart city applications" for knowledge discovery from large volumes of high-dimensional data. Specifically, he will discuss his novel cluster assessment and clustering algorithm for time-efficient tracking of evolving cluster structures in high-velocity data streams. In this talk, he will also discuss some of the applications of his algorithms for smart city context, particularly for transportation and IoT domain.
About the Speaker: Dr. Punit Rathore is currently a Postdoctoral Researcher in Senseable City Lab at Massachusetts Institute of Technology (MIT), Cambridge, USA, where he is working on urban intelligence and spatio-temporal data mining. Previously, he was a Postdoctoral Researcher at Grab-NUS AI Lab at National University of Singapore, Singapore. Dr. Rathore completed his Masters (M. Tech) from Indian Institute of Technology Kharagpur in 2011 and Doctor of Philosophy (PhD) from the Department of Electrical and Electronics Engineering, the University of Melbourne in Jan-2019. Prior to his Ph.D., Dr. Rathore has also worked as a Researcher in Automation Division at Tata Steel Ltd. Jamshedpur for around three and half years where he designed and developed several automation systems for manufacturing industries based on machine vision and machine learning techniques. Dr Punit Rathore has published more than 13 first-author papers in top IEEE/ACM journals and conferences in his field of research. His research work has also been internationally recognized with multiple best-paper awards at world-recognized IEEE conferences and best Ph.D. thesis prizes by IEEE System, Man, and Cybernetics Society (SMC) and Melbourne School of Engineering, the University of Melbourne.
Meeting number (access code): 184 327 1243
Meeting password: mDwp3kajt47