Meet the jury symposium by Gamze Gürsoy

Overcoming distributional shifts in federated learning and applications in biomedicine

Start: 5/07/2024, 10:30
Location: B91.200

Dr. Gamze Gürsoy (Columbia University & New York Genome Center, USA) will give a lecture on "Overcoming distributional shifts in federated learning and applications in biomedicine".

Following the lecture, there will be opportunity for young researchers to interact with her

•     Venue: ESAT B91.200
•     Date: 5 July 2024, 10:30 - 11:30
•     Dr. Gamze Gürsoy is visiting KU Leuven at the occasion of the PhD defence of Melanie Nijs. See also: https://forms.gle/DLc729o1vAJt8bAY8 

https://set.kuleuven.be/phd/seminars/gursoy


Abstract:
Federated learning has been proposed as a potential solution to overcome the institutional barriers to data sharing in biomedical AI. Federated learning allows multiple parties to train the same model on their own data, without having to share the data with each other. However, there still remain unanswered challenges, especially in the domain of biomedicine: Federated learning relies on the assumption that the data at each party are independent and identically distributed. In particular, heterogeneity between different local datasets might propagate the bias that each institution might have with respect to patient population, given that the size of local datasets may vary significantly. To mitigate these issues, we present frameworks for assessing and overcoming distribution shifts while preserving privacy.

Biography:
Gamze Gürsoy, PhD, is a Core Faculty Member at the New York Genome Center. She holds a joint appointment as Assistant Professor in the Departments of Biomedical Informatics and Computer Science at Columbia University. Dr. Gürsoy’s lab’s overarching research goal is to harmonize diverse fields such as biology, bioinformatics, molecular biology, engineering, and cryptography to achieve two fundamental aims: (1) to increase biomedical data access to a wider group of scientists while preserving privacy of research participants; and (2) to uncover the molecular underpinnings of gene dysregulation via knowledge gained from functional genomics data. They create modular and privacy-enhancing omics and clinical data analysis tools, which can be adapted to new data modalities and analysis needs as they arise, by combining knowledge in molecular biology and applied cryptography. They also develop computational and biochemical technologies to pinpoint genetic and epigenetic determinants of chromatin organization.