Dr. Igor Jurisica is a Senior Scientist at Schroeder Arthritis Institute and Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, UHN, and a Professor at University of Toronto, as well as an Affiliated Professor of Computational Biology at the MBZUAI School of Digital Public Health. Since 2021 he has served as Scientific director of the World Community Grid, which is a virtual supercomputer platform enabling advanced open science and open data research benefiting humanity. 
His research focuses on integrative informatics and the representation, analysis and visualization of high-dimensional data to identify prognostic and predictive signatures, determine clinically relevant combination therapies, and develop accurate models of drug mechanism of action and disease-altered signaling cascades. He has been recognized among leading experts in artificial intelligence applied to drug discovery and oncology.

Dr. Edoardo Pasolli is an Associate Professor in the Department of Agricultural Sciences at the University of Naples Federico II, Italy.
His research centers on the development and application of advanced computational and machine-learning approaches for metagenomics, with a particular focus on large-scale integrative analyses of human and food-associated microbiomes. He has contributed to improving strain-level resolution methods, enabling high-precision profiling of microbial diversity, functional potential, and transmission dynamics across hosts, environments, and ecological niches. His work supports a deeper understanding of microbiome structure, evolution, and its implications for health, nutrition, and food systems.
Previously, he held a Marie Skłodowska-Curie Individual Fellowship at the University of Trento. He also completed postdoctoral training at the University of Trento, Purdue University, and NASA Goddard Space Flight Center.

Dr. Oksana Valerianovna Galzitskaya is Head of the Bioinformatics Laboratory at the Gamaleya National Research Center for Epidemiology and Microbiology and leads the Bioinformatics and Proteomics Laboratory at the Institute of Protein Research of the Russian Academy of Sciences.
Her research integrates molecular biology, biophysics, and bioinformatics, with a focus on protein folding, amyloid formation, and intrinsically disordered proteins. She has developed theoretical and computational frameworks to identify folding nuclei, predict amyloidogenic and disordered regions, and model mechanisms of protein misfolding and aggregation. Her work has contributed to understanding amyloid fibril formation, polymorphism, and disease-related protein behavior, supporting advances in therapeutic target identification and antimicrobial peptide design.

Alexandre G. de Brevern is a Senior Researcher at INSERM and head of Dynamics of Structures and Interactions of Biological Macromolecules (DSIMB, INSERM UMR_S 1134, BIGR). 
He has two main axes of researches: (i) developing innovate methodologies useful for the scientific community and (ii) specific application to proteins implicated in diseases and pathologies. He has contributed more than 20 tools, web servers, and databases focused on protein structure analysis, comparison, and flexibility prediction. He is known for work on local protein conformations (β-turns, PPII helices, β-bulges) and for introducing Protein Blocks, a structural alphabet widely used to analyze protein structures and dynamics, disordered regions, and binding sites. He applies Bayesian and machine-learning approaches (ANNs, SVMs, deep learning) and uses modeling/MD to study disease-related proteins, notably in transfusion biology.