Prof. Adil Mardinoğlu is Professor of Systems Biology at the Centre for Host–Microbiome Interactions, King's College London, and a group leader at the Science for Life Laboratory (SciLifeLab), KTH Royal Institute of Technology, Stockholm. His team combines multi-omics data, genome-scale metabolic modelling, systems biology and artificial intelligence with experimental biology and drug development to design novel treatment strategies for metabolic and neurodegenerative diseases as well as certain cancers. A key contributor to the Human Protein Atlas and the international Human Cell Atlas initiatives, he has authored more than 290 research and review articles in journals including Science, Nature, Nature Biotechnology, Cell Metabolism and Nature Communications, and is a co-founder of several biotech companies, including ScandiBio Therapeutics.

Dr. Öznur Taştan is an Associate Professor of Computer Science and Engineering at Sabancı University, Istanbul, where she is also affiliated with the Molecular Biology, Genetics and Bioengineering program. She received her PhD (2011) and MSc (2007) from the School of Computer Science at Carnegie Mellon University, worked as a postdoctoral researcher at Microsoft Research New England, and was a faculty member at Bilkent University before joining Sabancı University. Her research lies at the intersection of machine learning and computational biology, developing machine learning and deep learning methods that leverage large-scale molecular profiling data to uncover the molecular basis of cellular processes and diseases. She serves as co-president of the ISCB Machine Learning in Computational and Systems Biology (MLCSB) community and as an associate editor of IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Dr. Özge Şensoy is an Associate Professor at the School of Engineering and Natural Sciences, İstanbul Medipol University, where she leads the Computational Biophysics Laboratory. Her research aims to reveal the molecular mechanisms of biologically relevant processes and to design targeted and safe therapeutic molecules using molecular dynamics simulations, enhanced sampling techniques, molecular docking, virtual screening and free-energy calculations, with particular interests in allostery, G protein-coupled receptors, RAS proteins and antibiotic resistance. Working in close collaboration with experimental groups in biochemistry, molecular biology and medicinal chemistry, she received the TÜBA-GEBİP Outstanding Young Scientist Award (2023) for her work on computational physics and structural biology.

Prof. Dr. Ivet Bahar is the Director of the Laufer Center for Physical and Quantitative Biology and a Professor of Biochemistry and Cell Biology at Stony Brook University. Prior to this, she was Distinguished Professor and Founding Chair of the Department of Computational and Systems Biology at the University of Pittsburgh School of Medicine. She received her BS and MS degrees in Chemical Engineering from Boğaziçi University and earned her PhD in Physical Chemistry from Istanbul Technical University. An internationally recognized pioneer in structural biology and computational biophysics, Prof. Bahar developed elastic network models (such as the Gaussian Network Model and Anisotropic Network Model) for understanding biomolecular dynamics, allosteric regulation, and drug discovery. She is an elected member of the US National Academy of Sciences (NAS), a member of the European Molecular Biology Organization (EMBO), and a fellow of the Biophysical Society.

Ege Ülgen, MD, PhD, is a bioinformatics professional with a background spanning medicine, bioinformatics, and cancer genomics. He received his medical degree from Acıbadem University, followed by a PhD in Biostatistics and Bioinformatics. He also conducted postdoctoral research at Yale School of Medicine, focusing on neurogenetics and brain tumours. Ege has worked extensively on genomic data analysis and genomics sequencing, particularly in cancer and specifically glioma research. He currently works as a Bioinformatics Engineer at Genomics England, where he designs and develops software solutions supporting the Cancer Genomic Medicine Service, with a focus on robust, scalable, and reliable analysis of genomic and clinical data.