Real-time IoT Data Collection and Online Learning for e-Health Applications
You are all invited to attend the seminar:
“Real-time IoT Data Collection and Online Learning for e-Health Applications”
given by Marco Levorato, University of California, Irvine.
Abstract: In this talk, I will emphasize the challenges we faced and solutions we developed to build effective IoT systems for the real-time collection of biophysical signals from resource constrained sensors. First, I will discuss a use-case focused on the detection of stress in everyday settings based on signals, and emphasize the need for real- time personalized analysis. In this context, I will present a context-aware active learning algorithm based on deep reinforcement learning for the optimization of the interaction between a layered wearable-edge-cloud system and the user. Then, I will present and discuss the techniques we developed to support the complex neural analysis of biosignals on computing/communication limited systems, and in particular recent frameworks based on split deep neural networks and iterative sample-specific representations.
Bio: Marco Levorato is an Associate Professor in the Computer Science department at UC Irvine. He completed the PhD in Electrical Engineering at the University of Padova, Italy, in 2009. Between 2010 and 2012, he was a postdoctoral researcher with a joint affiliation at Stanford and the University of Southern California. His research interests are focused on distributed computing over unreliable wireless systems, especially for autonomous vehicles and healthcare systems. His work received the best paper award at IEEE GLOBECOM (2012). In 2016 and 2019, he received the UC Hellman Foundation Award and the Dean mid-career research award, respectively. His research is funded by the National Science Foundation, the Department of Defense, Intel and Cisco. In 2020-2021, he was the vice chair of the IEEE Technical Committee on Smart Grid Communications. He serves in the TPC of IEEE Infocom and IEEE Secon, and was part of the organizing committee of several IEEE and ACM conferences, including IEEE Secon 2022 and 2017, ACM MobiSys 2015 and ACM MobiCom 2015 and 2014. In 2022, he gave the keynote speech at IEEE Healthcom.