Scalable Clustering for Big Data and Efficient Algorithms for IoT and Smart City Applications

Seminar talk titled "Scalable Clustering for Big Data and Efficient Algorithms for IoT and Smart City Applications"

Title Of the Talk: Scalable Clustering for Big Data and Efficient Algorithms for IoT and Smart City Applications
Speaker: Dr Punit Rathore
Host Faculty: Dr. Vineeth N Balasubramanian
Date & Time: Thursday, 22nd July 10:00 – 11:00am
Seminar link:


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 healthcare, transportation, environment, 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. In this talk, Dr. Punit Rathore will discuss his efficient machine learning algorithms to manage and extract actionable information from big data from various domains. Specifically, he will present his novel cluster assessment and clustering algorithm for time-efficient tracking of cluster structures in static big data and high-velocity data streams, with a brief overview of his novel algorithms for the smart city context, particularly for the transportation and IoT domain.

Speaker Profile:

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 for Smart City applications. Previously, he was a Postdoctoral Researcher at the GRAB-NUS AI Lab at National University of Singapore, Singapore. Dr. Rathore completed his Masters (M. Tech) in Instrumentation Specialization from the Department of Electrical Engineering at IIT Kharagpur in 2011 and Doctor of Philosophy (PhD) from the Department of Electrical and Electronics Engineering at the University of Melbourne, Australia in Jan-2019. Prior to his PhD, Dr. Rathore 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 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 PhD thesis prizes by IEEE System, Man, and Cybernetics Society (SMC) and Melbourne School of Engineering, the University of Melbourne, Australia.

Thursday, 22nd July 10:00 – 11:00am