For our next talk, in the Digital Phenotyping seminar series, we are delighted to host Ben Busby, Senior Alliance Manager for Genomics at NVIDIA on 17 July 2025, 1:00 pm, BDI seminar room 1.

Title: Ideas for accelerated and integrated compute in imaging, genomics, and devices, in Biobank and other datasets
Date: 17 July 2025
Time: 13:00 – 14:00
Venue – BDI/OxPop seminar room 1

Abstract
As we enter the age of AI, agents will play a larger role in analysis and knowledge management and contextualization will become critical. The scientific (and practical) implementation interfaces will not be limited to AI and chatbots. Accelerated scientific computing is extremely likely to play an expanding role in traditional analysis, particularly when using biobank scale data. Some vignettes on specific topics in acceleration will be offered:

- Sequence alignment and annotation

- Synthetic image generation

- Knowledge graphs as memory

- Single cell analysis

- On-device computing

- Estimation of cis- and trans- effects on variant penetrance by background haploblocks

We’ll end with a discussion of contextualization, validation, and garbage collection of model generated datasets with a focus on improvement of healthcare systems.

Bio: Ben Busby is the Senior Alliance Manager for Genomics at NVIDIA, where he focuses on areas such as prototyping, disease subtyping, deep learning, and knowledge graphs. He also holds an adjunct faculty position in the Computational Biology Department at Carnegie Mellon University and serves as an advisor to both Johns Hopkins University and Research to the People at Stanford. Ben earned his PhD in Biochemistry from the University of Maryland, Baltimore, and did a postdoc in evolutionary genomics at NCBI.

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Hybrid Option:
Please note that these meetings are closed meetings and only open to members of the University of Oxford. Please respect our speakers and do not share the link with anyone outside of the University. The purpose of these seminars is to foster more communication among employees throughout the University, so we strongly advise in-person attendance whenever feasible.

Microsoft Teams meeting
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Meeting ID: 377 252 440 130 6
Passcode: PB3pp2pZ

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