Keynote Speakers
In order to deepen the communication in all the participants, ICBBB 2026 have invited
professors from all over the world to have speeches about
Computational Biology and Bioinformatics and related fields.
Keynote Speaker
Associ. Prof. Martin Steinegger
Seoul National University, South Korea
Dr. Steinegger is an Associate Professor in the Biology Department at Seoul National University, with a joint appointment to the Interdisciplinary Program in Bioinformatics. He conducted his doctoral studies at the Max Planck Institute for Biophysical Chemistry and was awarded a Ph.D. in computer science with summa cum laude honors from the Technical University of Munich in 2018, followed by a postdoctoral fellowship at Johns Hopkins University. Dr. Steinegger has published more than 50 papers covering a wide range of topics in bioinformatics, from detecting genomic assembly contamination to organizing the protein structure space. In 2024 he was awarded the Overton Prize for outstanding contributions to computational biology by the International Society for Computational Biology. He started his research group in 2020, focusing on the development of methods to analyze massive genomics and proteomic datasets. The group’s contributions to bioinformatics include widely used tools for predicting structures (ColabFold/AlphaFold2), clustering (Linclust), assembling (Plass), and searching sequences (MMseqs2) and protein structures (Foldseek). His group’s software and web services have been installed and used millions of times. Dr. Steinegger is an advocate for international collaboration at his home institution, as well as for open science and open-source software.
Prof. Michiaki Hamada
Waseda University, Japan
Michiaki Hamada is a Professor in the Faculty of Science and Engineering at Waseda University, Tokyo, and President of the Japanese Society for Bioinformatics (JSBi). He is concurrently a Fellow of the Center for Research and Development Strategy at the Japan Science and Technology Agency (JST-CRDS), an Invited Researcher at the Cellular and Molecular Biotechnology Research Institute, AIST, and a Visiting Professor at the Graduate School of Medicine, Nippon Medical School. He received B.Sc. and M.Sc. degrees in Mathematics from Tohoku University and a Ph.D. from Tokyo Institute of Technology in 2009, with a thesis on RNA secondary structure prediction. After eight years as a researcher in industry, he moved to the University of Tokyo in 2010 and to Waseda University in 2014, becoming a full Professor in 2018. His research spans computational biology, RNA informatics, and AI-assisted drug discovery, with a focus on RNA structure prediction, RNA-protein interaction analysis, and integrative multi-omics approaches. He has authored over 100 peer-reviewed publications and received the MEXT Young Scientists' Award (2017), the Waseda Research Award (2021), and the Okuma Memorial Academic Prize (Encouragement Award, 2024). He also serves as a Program Advisor for the FOREST program of JST and on the Program Evaluation Committee of AMED.
Speech Title: "Information Technologies Accelerating RNA Therapeutics"
Abstract: RNA-based therapeutics are emerging as a transformative class of medicines, yet their development faces long timelines, high costs, and low success rates. This keynote will introduce two complementary RNA-focused strategies that integrate artificial intelligence and computational biology to address these challenges. The first is RNA aptamer drug discovery, offering an alternative to small molecules. Our AI platform, RaptGen, combines HT-SELEX data, probabilistic modeling, and deep learning to design optimized aptamers, enabling in silico design, activity-guided mutagenesis, and rational truncation. Applications include generating high-affinity aptamers against Dengue virus and SARS-CoV-2. The second is RNA-targeted drug discovery, which treats RNAs themselves as therapeutic targets. We are developing a comprehensive database that integrates structural, interaction, and functional annotations for thousands of disease-associated non-coding RNAs, supporting the identification of druggable RNA motifs. Future directions include applying quantum computing-AI hybrid approaches to explore vast molecular sequence spaces and accelerate drug candidate optimization, bridging fundamental RNA biology and clinical innovation.
Invited Speakers
Assoc. Prof. Mustafa MISIR
Duke Kunshan University, China
Mustafa Misir is an Associate Professor of Data and Computational Science at Duke Kunshan University in China. He completed his Ph.D. in Computer Science at KU Leuven (Belgium) in 2012. After graduation, he worked as a postdoctoral researcher at INRIA Saclay - Universite Paris Sud XI (France), Singapore Management University (SMU) and University of Freiburg (Germany) respectively. He was also a visiting researcher shortly at University of Zurich (Switzerland) and Universitat Poltecnica de Catalunya (UPC) / BarcelonaTech (Spain). Afterwards, he moved to Nanjing University of Aeronautics and Astronautics (China) as a faculty member at the College of Computer Science and Technology. Prior to joining Duke Kunshan University, he was a faculty member in Computer Engineering at Istinye University (Turkey). His main research interests include Automated Algorithm Design (Machine Learning + Algorithm Design) / Automated Algorithm Design, Data Science and Operations Research. He is the recipient of several prestigious academic awards and published over 60 papers in various international conferences/journals.
Speech Title: "Automated Algorithm Design in Drug Discovery: Data-Driven Algorithm Selection for Molecular Docking"
Abstract: Automated Algorithm Design (AAD) seeks to eliminate manual, expertise-intensive design by building intelligent systems that automate algorithm selection, configuration and generation. While AAD spans multiple paradigms, this talk focuses specifically on Algorithm Selection for Molecular Docking in structure-based drug discovery. Guided by the No Free Lunch (NFL) theorem, no single docking solver universally dominates. We trace the evolution of data-driven selection strategies, from early collaborative filtering recommenders configuring search parameters, to advanced Graph Neural Networks (GNNs) and lightweight pretrained molecular embeddings that map complex protein-ligand structures to optimal cross-engine docking pipelines. We will examine how these multi-criteria selectors balance geometric accuracy, physical pose validity, and computational efficiency. Furthermore, we address the practical boundaries of data-driven selection, discussing how workflow-induced protocol shifts and unstable oracle landscapes challenge cross-benchmark generalization. By bridging AAD with computational chemistry, this presentation demonstrates how shifting from manual algorithm design to AAD drastically reduces human effort and accelerates therapeutic discovery.
Assoc. Prof. Zhuoli Huang
BGI Research, China
Dr. Zhuoli Huang is an Associate Researcher in Bioinformatics at BGI Research, Shenzhen, China. His research focuses on the application of single-cell multi-omics and population genetics to understand human immune regulation and disease mechanisms. He has been involved in large-scale population multi-omics studies integrating single-cell RNA sequencing, single-cell chromatin accessibility profiling, whole-genome sequencing, and quantitative trait locus analyses. One of his representative works is the Chinese Immune Multi-Omics Atlas (CIMA), recently published in Science, which characterized the genetic and molecular regulation of circulating immune cells at population scale. His research interests include population-scale single-cell genomics, immune quantitative trait loci, regulatory genomics, and the integration of multi-omics data with human genetics to identify cell type-specific regulatory mechanisms underlying complex traits and diseases.
Speech Title: "Integrating Single-Cell Multi-omics and Genetics to Understand Human Immune Regulation"
Abstract: The Chinese Immune Multi-Omics Atlas (CIMA) provides a population-scale framework for understanding how genetic variation shapes human immune regulation at single-cell resolution. By integrating single-cell RNA sequencing, single-cell chromatin accessibility profiling, and whole-genome sequencing from a large Chinese population cohort, CIMA systematically maps cell type-specific molecular variation across circulating immune cells. The atlas enables the identification of genetic variants associated with gene expression and chromatin accessibility and provides insights into the regulatory mechanisms linking genetic variation to immune phenotypes and disease susceptibility. In this talk, I will introduce the design and analytical framework of CIMA, highlight key findings from the integration of single-cell multi-omics and genetics, and discuss how population-scale cellular atlases can facilitate the interpretation of disease-associated genetic variants. I will also discuss the potential of such resources for studying immune-related diseases and advancing precision medicine in diverse populations.
Assoc. Prof. Leonardo N. Pasquito
University of Makati, Philippines
Dr. Leonardo N. Pasquito is Professorial Chair in Science, currently the Head of the Department of Natural Sciences of the College of Science, and Associate Professor of Biology, Biochemistry, and Mathematics, Science, and Technology at University of Makati, Metro Manila, Philippines. He holds a Master in Innovative Science Education from the University of Makati and completed the academics for Master of Science in Biochemistry at the University of the Philippines Manila. He earned his Bachelors degree in Biology, his Juris Doctor from University of Sto. Tomas Legaspi and Doctor of Public Administration from the College of Continuing, Advanced and Professional Studies, University of Makati. His research interest is on risk assessment and biosafety of Genetically Modified Organisms (GMOs) integrating computational biology, bioinformatics, and in silico tools with genomic data and policy analysis to advance food security, and evidence-based governance. His research papers have been presented in international conferences in the Philippines, Taiwan, Indonesia, Vietnam, and Japan. Dr. Pasquito has published textbooks in Chemistry, Biology, Biochemistry, Mathematics, Science and Technology and is an active member of the Philippine Association of Chemistry Teachers, Biology Teachers Association of the Philippines, and Philippine Association of Physics and Science Instructors.
