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SUMMARY:Federated Learning at H.IAAC: On-going Research and Opportunities 
 - Allan M. de Souza &amp\; Luiz Bittencourt\, Universidade Estadual de Cam
 pinas (UNICAMP)\, Brazil
DTSTART:20251020T100000Z
DTEND:20251020T110000Z
UID:TALK238684@talks.cam.ac.uk
CONTACT:Sally Matthews
DESCRIPTION:Federated Learning (FL) has emerged as a key paradigm for enab
 ling collaborative and privacy-preserving machine learning across distribu
 ted data sources. At the Hub of Artificial Intelligence and Cognitive Arch
 itectures (H.IAAC)\, University of Campinas (UNICAMP)\, several research i
 nitiatives have been conducted to advance the development and application 
 of FL. In this talk\, we will present an overview of the main research dev
 eloped at H.IAAC. We will also discuss ongoing and future research directi
 ons and highlight collaboration opportunities.\n\nBio:\nLuiz Bittencourt i
 s an Associate Professor at Universidade Estadual de Campinas (UNICAMP)\, 
 Brazil. Luiz was awarded with the IEEE ComSoc Latin America Young Professi
 onal Award in 2013. He acts on the organization of several conferences in 
 the cloud and edge computing topics\, and in several technical program com
 mittees. He served as associate editor for the IEEE Cloud Computing Magazi
 ne\, and currently serves as AE for the Computers and Electrical Engineeri
 ng and the Internet of Things journals\, for the Journal of Network and Sy
 stems Management\, for the IEEE Networking Letters and for the IEEE Transa
 ctions on Services Computing. His main interests are in resource managemen
 t and scheduling in cloud\, edge and fog computing\, and their synergy tow
 ards an intelligent computing continuum through distributed machine learni
 ng techniques.\n\nAllan M. de Souza is an Assistant Professor at  Universi
 dade Estadual de Campinas (UNICAMP)\, Brazil\, and Researcher at the Hub o
 f Artificial Intelligence and Cognitive Architectures (H.IAAC). He earned 
 his Ph.D. in Computer Science from UNICAMP and the University of Bern\, Sw
 itzerland. His research interests include Federated Learning and Intellige
 nt Distributed Systems.
LOCATION:Computer Lab\, FW11
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