Digital Health Seminar Series

Stimulating interdisciplinary connections in health care with innovative technologies

The Digital Health Seminar Series aims to develop international interdisciplinary connections between academics, industry, and healthcare professionals interested in advancing healthcare with innovative technologies.

It is organised by the EPSRC Centre for Doctoral Training in Digital Health and Care, and the EPSRC LEAP Digital Health Hub, at the University of Bristol.

These seminars are open to all. For any queries please contact dh-seminars@bristol.ac.uk. Sign up to our mailing list to keep up to date regarding upcoming seminars, and see our blog for more information.
 

Autumn 2025 Seminar Series

We are pleased to announce the first speakers for the Autumn term Digital Health and Care Seminar Series, which take place every two weeks starting Tuesday 30th September 2025 at 2pm.


Next Event

Topic: AI for Life Sciences: Challenges and Opportunities
Location: In Person 1.5 Wills Memorial Building (University of Bristol only) & Online (Register at Ticket Tailor)
Date: November 25th, 2025 14:00-15:00 GMT

Abstract:
There is a growing effort to apply artificial intelligence to solve challenging problems in the life sciences, offering new ways to understand biology and accelerate discovery. In this talk, I will give an overview of how AI is being applied across key areas such as drug discovery and protein design. I will discuss how AI models are used to learn the language of proteins and DNA sequences, highlight the limitations of current approaches, and share perspectives on emerging directions and opportunities at the intersection of AI and the life sciences.

Bio:
Mahmoud Hossam is an AI Scientist at CureCraft, where he works on building AI models for protein and enzyme design. Previously, he was an R&D AI Engineer at GSK, focusing on improving variant effect prediction using protein language models. Mahmoud completed his PhD at Monash University in generative sequence models. His broader interests lie in applying foundational and generative AI models, alongside reinforcement learning, to address challenges across the life and natural sciences, including drug and materials discovery and design, as well as healthcare.

Past Seminars

Pre-2025 past seminars