The "SICE Forum" organized by the School of Information and Communication Engineering (SICE) invites Associate Prof. Zaid Al-Ars, Delft University of Technology, to deliver an academic webinar. Below are the details for the event, and interested students and faculty members are welcome to attend.
Topic:Future Technologies to Enable Edge Device Intelligence
Speaker: Zaid Al-Ars (Delft University of Technology,Associate Professor)
Time:16:00 (Thursday), November 11, 2021
Venue: Online platform: ZOOM Meeting
Conference links:
https://tudelft.zoom.us/j/94241813721?pwd=b1gxdExjNTZjOVNwTWNlSi9UaW5VUT09
Host: Associate Professor Qiang Liu
Introduction:
The fast proliferation of edge devices in various application domains opens new opportunities to embed computer intelligence in our environment and support various aspects of our daily lives.
This promises to increase data security, improve user interactivity and reduce bandwidth pressure. However, there are a number of challenges that we need to address to enable this vision, ranging from the limited compute capabilities of edge devices to the inherent vulnerability of devices in the field. In this talk, we present a number of emerging machine learning technologies and approaches to address these challenges. Research on federated and distributed learning allows creating powerful predictive models from the vast amounts of data distributed at the edge. At the same time, new techniques like model quantization allow for deploying such complex models in embedded edge devices easily using automated model synthesis tools. We also discuss applications in healthcare and big data analytics that can benefit immensely from such advances in the capabilities of edge intelligence.
Speaker’s profile：
Zaid Al-Ars is an associate professor in the Delft University of Technology, where he leads the Accelerated Big Data Systems group (abs.ewi.tudelft.nl). His work focuses on addressing bottlenecks in big data analytics frameworks to increase scalability, performance, power efficiency, etc. These techniques are deployed on a number target of application domains such as healthcare, analytics and data science. Zaid is also co-founder of multiple big data analytics startups active at the intersection of big data analytics and high-performance computing. He also worked and collaborated with various tech industry heavyweights, such as Siemens, Infineon, Philips and IBM, and serves on the advisory board of a number of high-tech startups. Zaid received numerous awards in recognition for his research contribution, such as the IBM Faculty Award and the Xilinx Research Grant. He is regularly invited to give talks on big data technology and commercialization both in industry and academia. Zaid has a long and successful history managing and executing industrial projects at the national, European as well as the international level. He has two patents and published more than 150 peer-reviewed publications.
