Multi-device Intelligence with a Data-Centric Approach to Federated Learning
Join us for an in-person talk by Mohammad Malekzadeh, a Senior Research Scientist and Tech Lead at Nokia Bell Labs.
Multi-device Intelligence with a Data-Centric Approach to Federated Learning
14 Mar 2025, 12:00 – 13:00
Attend an external talk with Dr Mohammad Malekzadeh, Senior Research Scientist and Tech Lead at Nokia Bell Labs, as we explore cutting-edge developments in multi-device intelligence and federated learning.
In an era where personal devices continuously capture and process data, how can we train neural networks efficiently while addressing challenges such as data scarcity, model partitioning, and missing modalities? Dr Malekzadeh will share his expertise on optimizing deep learning models for real-world applications, ensuring both efficiency and privacy in multi-device environments.
This session is ideal for academics, researchers, industry professionals, and students interested in machine learning, edge computing, and privacy-preserving AI. Don't miss this opportunity to gain valuable insights and participate in an interactive discussion.
Dr Mohammad Malekzadeh is a Senior Research Scientist and Tech Lead at Nokia Bell Labs in Cambridge, UK. He leads the Device Intelligence team, focusing on Machine Learning solutions for personal devices, with an emphasis on efficiency, collaboration, adaptability, and privacy. Before joining Bell Labs, Mohammad worked as a Postdoctoral Research Associate at Imperial College London's Information Processing and Communications Lab, closely collaborating with Prof. Deniz Gunduz on Privacy-Preserving and Trustworthy Machine Learning. Mohammad pursued his PhD in Computer Science at Queen Mary University of London as a member of the Centre for Intelligent Sensing, concurrently holding a Research Assistant position at Imperial College London contributing to the Databox Project in the Systems and Algorithms Laboratory. In his PhD, Mohammad collaborated with esteemed advisors such as Prof. Hamed Haddadi, Dr. Richard G. Clegg, and Prof. Andrea Cavallaro for developing Machine Learning Algorithms for Privacy-Preserving Personal Data Analytics, particularly for data captured by mobile and wearable devices. During his PhD journey, Mohammad interned at Brave Software Research, where he explored privacy-preserving techniques to improve content personalisation in web browsers.
Further information
Ticketing
Ticketed
Cost
Free
Open to
All
Availability
Yes
