Knowledge-based diagnosis of genetic disease
Dr. Robert Hoehndorf,
Associate Professor, Computer Science,
Knowledge-based diagnosis of genetic disease
King Abdullah University of Science and Technology, Kingdom of Saudi Arabia.
Robert is an Associate Professor in Computer Science at King Abdullah University of Science and Technology in Thuwal where he is the PI of the Bio-Ontology Research Group (BORG). Prior to joining KAUST, Robert held research positions at the Max Planck Institute for Evolutionary Anthropology, the European Bioinformatics Institute, University of Cambridge, and Aberystwyth University. He earned his PhD degree in Computer Science from the University of Leipzig. Robert's research focuses on the development and application of knowledge-based methods in biology and biomedicine. In bioinformatics, Robert focuses on bio-ontologies and data integration, protein function prediction, and developing models for investigating genotype-phenotype relations. In computer science, his interests lie in Semantic Web technologies and neuro-symbolic methods that combine formal logic and machine learning. Robert has published over 150 papers in journals and international conferences. Robert is Editor in Chief of the Journal of Biomedical Semantics.
Computational genomics at scale: Open-source frameworks for cancer omics and gene regulation
Dr. Aziz Khan,
Assistant Professor, Computational Biology
Group Leader of Computational Biology & Cancer Regulatory Genomics Lab,
Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates.
Aziz Khan is an Assistant Professor of Computational Biology at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) in Abu Dhabi, where he leads the Computational Biology and Cancer Regulatory Genomics (https://khanlab.bio/) Lab. His research focuses on deciphering gene regulation and the non-coding genome in cancer and precision medicine, using scalable computational and machine learning approaches. His lab develops open-source tools and integrative frameworks to interpret large-scale, multi-omics data. Aziz earned his PhD in Bioinformatics from Tsinghua University and completed his postdoctoral research at the NCMM, University of Oslo. Before joining MBZUAI, he was a senior research scientist at Stanford Cancer Institute, where he led core efforts in cancer genomics infrastructure and contributed to large multi-institutional initiatives, including the Human Tumor Atlas Network (HTAN) and the Metastasis Research Network (MetNet). He has developed widely used computational resources such as JASPAR, Intervene, and UniBind, and has taught and advocated for open and reproducible science as a Stanford/Carpentries Instructor and former eLife/ASAPbio Ambassador. His work bridges AI, genomics, and systems biology, with a mission to enable reproducible, collaborative, and globally impactful science.
Integrative bioinformatics for smart healthcare
Dr. Vladimir Brusic,
Vice President, Applied Research and Graduate Studies,
Applied Research & Graduate Studies Division,
University of Doha for Science and Technology, Qatar.
Dr. Vladimir Brusic is Professor and Vice President for Applied Research and Graduate Studies at the University of Doha for Science and Technology (UDST). He holds a Ph.D. from La Trobe University (Australia) and brings over two decades of global experience in bioinformatics, computing, and data science. He has worked with leading institutions around the world including La Trobe University and the University of Queensland (Australia); Harvard Medical School and Boston University (USA); the Institute for Infocomm Research (I²R), Nanyang Technological University, and the National University of Singapore (Singapore); Nazarbayev University (Kazakhstan); the University of Nottingham Ningbo China (China); and now UDST. His research spans immunoinformatics, health informatics, and computational medicine, with impactful contributions to cancer research, biomarker discovery, and systems biology. At UDST, Dr. Brusic leads initiatives to strengthen applied research and graduate programs, promote interdisciplinary collaboration, and drive innovation.
Building a Population-Specific Genomic Ecosystem for Precision Healthcare
Dr. Dinesh Velayutham,
Senior Bioinformatics Specialist,
Qatar Precision Health Institute (QPHI),
Qatar Foundation.
Dr. Dinesh Velayutham is a Senior Bioinformatics Specialist at the Qatar Precision Health Institute, Qatar Foundation, where he leads research in pharmacogenomics, HLA profiling, and population genomics within national biobank initiatives. He earned his Ph.D. from the University of Milan, Italy, supported by an international fellowship from the Italian government, followed by postdoctoral training in genomic medicine and computational biology. With over a decade of experience in next-generation sequencing (NGS) analytics, Dr. Velayutham has contributed to large-scale genomic projects spanning human, animal, and plant systems. His current work integrates genomic, transcriptomic, and clinical data to advance precision medicine in the Qatari population. He has co-authored more than 25 peer-reviewed publications and several book chapters in genomics and personalized medicine. Dr. Velayutham is also actively involved in graduate teaching at Hamad Bin Khalifa University, mentoring MSc and Ph.D. students in genomics and bioinformatics. His professional interests include population-scale pharmacogenomics, causal inference using multi-omics data, and development of population-specific genomic resources for precision health.