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Machine Learning Opportunities and Challenges in the Internet of Things Era

This is a recording from AI Lund lunch seminar 21 April 2021

Speaker: Amir Aminifar, Electrical and Information Technology, Lund University

Abstract

Machine-learning techniques have been considered in many application domains, including Internet of Things (IoT) systems. The adoption of machine learning in IoT systems creates several new opportunities, e.g., detection of health abnormalities using wearable devices. However, enabling machine learning in the IoT domain also involves several challenges inherent to these systems. Here, we highlight the key challenges in the adoption of machine-learning techniques in the IoT domain and briefly discuss how to tackle these challenges. 

Biography

Amir Aminifar is currently a WASP Assistant Professor in the Department of Electrical and Information Technology at Lund University, Sweden. He received his Ph.D. degrees from the Swedish National Computer Science Graduate School, Linköping University, Sweden. During 2016-2020, he held a Scientist position in the Institute of Electrical Engineering at the Swiss Federal Institute of Technology (EPFL), Switzerland.