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  Jianwei Huang

  Vice President at z6首页; Presidential Chair Professor at The Chinese University of Hong Kong, Shenzhen

  Executive Chair

  嘉宾介绍

  演讲提要
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  Bing Luo

  z6首页-Yale Joint Postdoc Researcher

  Co Chair

  嘉宾介绍

  演讲提要
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  Salman Avestimehr

  CEO and Co-founder of FedML

  Secure, Scalable, and Efficient Federated Learning

  嘉宾介绍

  Salman Avestimehr (https://www.avestimehr.com) is the CEO and co-founder of FedML. He is also a Dean’s Professor and the inaugural director of the USC-Amazon Center on Trustworthy AI at the ECE and CS Department of University of Southern California. His research interests include decentralized and federated machine learning, information theory, security, and privacy. Dr. Avestimehr has received many awards for his research, including the Presidential PECASE award from the White House (President Obama), the James L. Massey Research & Teaching Award from IEEE Information Theory Society, an Information Theory Society and Communication Society Joint Paper Award, , and several Best Paper Awards at Conferences. He is also a fellow of the IEEE.

  演讲提要

  Federated learning (FL) has emerged as a promising approach to to enable decentralized machine learning directly at the edge, in order to enhance users’ privacy, comply with regulations, and reduce development costs.  In this talk, we will provide an overview of FL and highlight several key research directions in this area. In particular, we discuss four important research directions of: (1) privacy and security guarantees of FL; (2) FL over resource-constrained edge nodes; (3) label scarcity and self-supervised FL; and (4) scalable system design for FL.

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  Chaoyang He

  CTO and Co-founder of FedML

  FedML: A Secure, Scalable, and Efficient Edge-Cloud Platform for Federated Learning

  嘉宾介绍

  Chaoyang He is Co-founder and CTO of FedML, Inc., a startup running for a community building open and collaborative AI from anywhere at any scale. His research focuses on distributed/federated machine learning algorithms, systems, and applications. He received his Ph.D. in Computer Science from the University of Southern California, Los Angeles, USA, advised by Salman Avestimehr (USC), Professor Mahdi Soltanolkotabi (USC), Professor Murali Annavaram (USC), and Professor Tong Zhang (HKUST). He also works closely with researchers/engineers at Google, Facebook, Amazon, and Tencent. Previously, He was an R&D Team Manager and Principal Software Engineer at Tencent (2014-2018), a Team Leader and Senior Software Engineer at Baidu (2012-2014), and a Software Engineer at Huawei (2011-2012). He has received a number of awards in academia and industry, including Amazon ML Fellowship (2021-2022), Qualcomm Innovation Fellowship (2021-2022), Tencent Outstanding Staff Award (2015-2016), WeChat Special Award for Innovation (2016), Baidu LBS Group Star Awards (2013), and Huawei Golden Network Award (2012). Besides pure research, he also has R&D experience for Internet products and businesses such as Tencent Cloud, Tencent WeChat Automotive / AI in Car, Tencent Games, Tencent Maps, Baidu Maps, and Huawei Smartphone. More details are available at his homepage: https://ChaoyangHe.com

  演讲提要

  In this talk, we will provide an overview of FedML (https://fedml.ai), which is a machine learning platform that enables zero-code, lightweight, cross-platform, and provably secure federated learning and analytics. In particular, we discuss four key components of FedML platform: (1) cutting-edge federated learning algorithms with an open-source community of more than 1k users; (2) a lightweight and cross-platform Edge AI SDK for deployment over GPUs, smartphones, and IoTs; (3) a user-friendly MLOps platform to simplify collaboration and real-world deployment; and (4) platform-supported vertical solutions across a broad range of industries (healthcare, finance, insurance, smart cities, IoT, etc.) and applications (computer vision, natural language processing, data mining, and time-series forecasting).

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