Graph generative AI and applications in bio/medical domain | 16/05/2025

Τίτλος:  Graph generative AI and applications in bio/medical domain

Ομιλητής: Michalis Vazirgiannis, Distinguished Professor, École Polytechnique, Paris and Affiliate Professor at MBZUAI in UAE.

Abstract: Graph generative models are recently gaining significant interest in current application domains. They are commonly used to model social networks, knowledge graphs, molecules and proteins. In this talk we will present the potential of graph generative models and our recent relevant efforts in the biomedical domain. More specifically we present a novel architecture that generates graphs with application to medical records as graphs with privacy guarantees. We capitalize and modify the graph Variational autoencoders (VAEs) architecture. We also present multimodal architectures capitalizing on graphs with applications to protein function prediction- the prot2text model.  Finally we present ongoing research directions, like how can graphs be transformed to sequences to achieve optimal generation capitalizing on LLMs.

About the speaker:Dr. Vazirgiannis is a Distinguished Professor at École Polytechnique in France and Affiliate Professor at MBZUAI in UAE. He has been intensively involved in data science and AI related research. His broad research area is in methods for data mining and machine/deep learning methods for diverse data types and applications (including graphs, text, time series). Recently he is working of i. GNNs and aspects including expressiveness, efficiency, generation ii. Pretrained models and resources for multilingual NLP and Biomedical applications. His research and industrial impact is spanning different domains such as web advertising, social networks, online gambling, insurance, legal text applications, aviation and maritime industry and the bio/medical domain. He has been teaching machine/deep learning and AI courses for academic and executive training studies in France, China, UAE, Morroco, Spain, Greece. Pr. Vazirgiannis has published more than 250 papers in international journals and proceedings of international conferences including NeurIPS, AAAI/IJCAI, AISTATS, ICLR, EMNLP/ACL, JMLR, JAIR, KDD, Nature/Digital Medicine, Scientific Reports. On the side of supervision he has supervised 32 completed PhD theses. Finally he has been able to attract significant funding for research from national and international sources, from research agencies and industrial partners (including Google, Airbus, Huawei, Deezer, BNP, LVMH). He lead(s) academic research chairs (DIGITEO 2013-15, ANR/HELAS 2020-26, Wallenberg Chair@KTH 2020-25) and an industrial one (AXA, 2015-2018). He has received several awards and distinctions including i. Marie Curie Intra European Fellowship (2006-8) ii. “Rhino-Bird International Academic Expert Award” in recognition of his academic/professional work @ Tencent (2017), iii. best paper awards in international conferences (such as IJCAI 2018, CIKM2013, LoResLM@COLING 2025). He has been invited to media interviews in France, USA and China  and published popularized articles in French and Greek magazines/newspapers on Artificial Intelligence topics. More info at: http://www.lix.polytechnique.fr/dascim/