Seminar from 3-4 p.m.
Reception to follow in IOE 1727 from 4-5 p.m.

Title: Federated Data Analytics for the Internet of Federated Things (IoFT)

Abstract: A critical change is happening in today's Internet of Things (IoT). The computational power at the edge device is steadily increasing. AI chips are rapidly infiltrating the market. Mobile phones' processing power is becoming comparable to laptops available for everyday use. Tesla's autopilot system has 150 million times more computing power than Apollo 11, and small local computers such as Raspberry Pis have become commonplace in manufacturing systems. This change opens a new paradigm of data analytics within IoT; one that exploits edge compute resources to process more of users' data at the origin of creation. In this talk, I term this future of IoT as the "Internet of Federated Things (IoFT)" and discuss our recent efforts in federated data analytics aimed at bringing this future into reality. Specifically, I will present federated analytics approaches that aim to answer two questions: (1) How to personalize model inference so participants borrow strength from each other yet retain their own individualized models, (2) How to extract what is shared and unique across the distributed datasets? I end the talk by describing our prototyping efforts to generate real-life IoFT data.

Bio: Raed Al Kontar is an Assistant professor in the Industrial and Operations Engineering (IOE) Department at the University of Michigan and an affiliate with the Michigan Institute for Data Science (MIDAS). Raed’s research focuses on collaborative, distributed, and decentralized data science. Raed obtained an undergraduate degree in Civil and environmental engineering and mathematics from the American University of Beirut in 2014. And then a master’s degree in statistics in 2017, and a Ph.D. degree in Industrial & System Engineering in 2018, both from the University of Wisconsin-Madison.