Seminars

Federated Learning (FL) has emerged as a key paradigm for enabling collaborative and privacy-preserving machine learning across distributed data sources.

Dashboards are a critical part of your observability stack. Looking at your dashboards—are they actually helping you understand the system? When well-designed, they surface intuitive information and help quickly diagnose outages.

For more details about the talk, and if you would like to attend, please visit: https://www.eventbrite.co.uk/e/talk-by-professor-bjarne-stroustrup-concept-based-generic-programming-tickets-1742215837469?aff=oddtdtcreator

As governments move to regulate AI, there is growing interest in using Large Language Models (LLMs) to assess whether or not an AI system complies with a given AI Regulation (AIR). However, there is presently no way to benchmark the performance of LLMs at this task.

Companies need reliable emission data for their products and services to take effective climate action, yet obtaining it is challenging. In today's interconnected economy, product and service carbon footprints (PCF) cannot be determined in isolation but require emission data exchange throughout supply chains.

Abstract not available

By 2050, older adults will make up about 22% of the global population, driving an urgent need for accessible and reliable health technologies. In this talk, I will present our work on intelligent mobile systems designed for older adults.

Federated Learning (FL) is a paradigm where models are collaboratively trained by sharing only local parameters with a central aggregation server and faces limitations in heterogeneous environments.

We are delighted to announce that Professor Moshe Vardi will be delivering the 2025 Wheeler Lecture on Wednesday 22nd October hosted by Professor Anuj Dawar.

Guest Speaker: Professor Moshe Vardi https://profiles.rice.edu/faculty/moshe-y-vardi

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