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Workshop
International Workshop on Scalability, Privacy, and Security in Federated Learning (SpicyFL 2020)
Xiaolin Andy Li · Dejing Dou · Ameet Talwalkar · Hongyu Li · Jianzong Wang · Yanzhi Wang

Sat Dec 12 08:20 AM -- 07:10 PM (PST) @
in Workshops Sat »
Event URL: http://icfl.cc/SpicyFL/2020 »

In the recent decade, we have witnessed rapid progress in machine learning in general and deep learning in particular, mostly driven by tremendous data. As these intelligent algorithms, systems, and applications are deployed in real-world scenarios, we are now facing new challenges, such as scalability, security, privacy, trust, cost, regulation, and environmental and societal impacts. In the meantime, data privacy and ownership has become more and more critical in many domains, such as finance, health, government, and social networks. Federated learning (FL) has emerged to address data privacy issues. To make FL practically scalable, useful, efficient, and effective on security and privacy mechanisms and policies, it calls for joint efforts from the community, academia, and industry. More challenges, interplays, and tradeoffs in scalability, privacy, and security need to be investigated in a more holistic and comprehensive manner by the community. We are expecting broader, deeper, and greater evolution of these concepts and technologies, and confluence towards holistic trustworthy AI ecosystems.

This workshop provides an open forum for researchers, practitioners, and system builders to exchange ideas, discuss, and shape roadmaps towards scalable and privacy-preserving federated learning in particular, and scalable and trustworthy AI ecosystems in general.

Author Information

Xiaolin Andy Li (Cognization Lab)

Dr. Xiaolin Andy Li is the Chief Scientist at Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences (CAS), heading the Center for AI and Intelligent Medicine (AIM). He is also the founder of ElasticMind.AI. He was a Partner of Tongdun Technology, heading the AI Institute and Cognization Lab at Palo Alto Square, near Stanford University. He was a tenured Full Professor and University Term Professor in Computer Engineering at the University of Florida. As the founding center director, he founded NSF Center for Big Learning (CBL) with UF, CMU, UMKC and UO and three dozens of leading companies as industry members, the first national center on deep learning in USA. He was also the director of Large-scale Intelligent Systems Laboratory (Li Lab). His research interests include machine learning/deep learning, intelligent platform, cloud computing, Internet-of-Things, security & privacy, precision medicine, and logistics. He led the design and deployment of one of the first software-defined 100G campus research networks and campus clouds GatorCloud, the best campus research network in the nation. His team designed and developed many platforms and tools, such as DeepCloud, CognitiveEngine, DeepEyes, OneTask, DeepSLAM, CloudBay, SMART, GemsCloud, Guoguo, FindingNemo, ToGathor, DeepDDoS, DeepMalware, S3PAS, DeepFolding, FoldingZero, PrimateAI, MySurgeryRisk and DeepDrug. He received the NSF CAREER Award, the Internet2 Innovative Application Award, NSF I-Corps Top Team Award, Top Team Award (DeepBipolar) in the CAGI Challenge, and Best Paper Awards (IEEE ICMLA 2016, IEEE SECON 2016, ACM CAC 2013, and IEEE UbiSafe 2007). He has published over 150 peer-reviewed papers and dozens of patent applications. He received PhD in Computer Engineering from Rutgers University.

Dejing Dou (" University of Oregon, USA")
Ameet Talwalkar (CMU)
Hongyu Li (tongdun)
Jianzong Wang (Ping An Technology (Shenzhen) Co., Ltd)
Yanzhi Wang (Northeastern University)

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