Keynote

We are privileged and honored to have Dr. Arpan Pal, TCS Research, India as our Keynote speaker.

Dr. Arpan Pal has more than 31 years of experience in the area of Intelligent Sensing, Signal Processing &AI, Edge Computing and Affective Computing. Currently, as Distinguished Chief Scientist and Research Area Head, Embedded Devices and Intelligent Systems, TCS Research, he is working in the areas of Connected Health, Smart Manufacturing, Smart Retail and Remote Sensing.  He is on the editorial board of notable journals like ACM Transactions on Embedded Systems, Springer Nature Journal on Computer Science and is on the TPC of notable conferences like IEEE Sensors, ICASSP and EUSIPCO. He has filed 190+ patents (out of which 100+ granted in different geographies) and has published 170+ papers and book chapters in reputed conferences and journals. He has also written three complete books on IoT, Digital twins in Manufacturing and Application AI in Cardiac screening. He is on the governing/review/advisory board of some of the Indian Government research organizations  and academic institutes. He is two times winner of Tata Group top Innovation award in Tata Innovista under Piloted technology category. Prior to joining Tata Consultancy Services (TCS), Arpan had worked for DRDO, India as Scientist for Missile Seeker Systems and in Rebeca Technologies as their Head of Real-time Systems. He is a B.Tech and M. Tech from IIT, Kharagpur, India and PhD. from Aalborg University, Denmark.  

Linked In - http://in.linkedin.com/in/arpanpal 

Google Scholar - http://scholar.google.co.in/citations?user=hkKS-xsAAAAJ&hl=en 

Orcid - https://orcid.org/0000-0001-9101-8051 

Keynote- Device Edge Computing for Intelligent Embedded Systems 

Abstract: The rise of Internet of Things (IoT) and sensor-driven analytics have brought about a significant change in the way that various machines, physical devices, and objects interact for performing Edge analytics. There is a growing focus on the Device Edge, the constrained compute-memory-power devices that are at the endpoints of the network. Such tiny devices are prime enablers of edge analytics, performing first level of data reduction, multi-sensor fusion, prediction, and inferencing. 

In this talk we introduce the device edge computing and its motivation followed by its applications in machine, material, infrastructure, people and earth sensing in the areas of manufacturing, retail, healthcare and sustainability. Then we do a deep dive on two important technologies driving this – automated model size reduction and neuromorphic computing. Finally we close with a peek into the future around nano-sensing systems.