Prof.  Abhishek Narain Singh

INSERM/Sorbonne University, France
Schiller International University, Germany

Prof. Dr. Abhishek Narain Singh is an AI Scientist at INSERM/Sorbonne University, Paris, France, and Adjunct Faculty at Schiller International University, Germany. He is a computational biologist specializing in AI-driven genomics, with extensive international research experience across Europe and the US. He completed his PhD studies in Biochemistry as a Commonwealth Scholar at the University of Cambridge, UK, and was also an NSF EPSCoR PhD Scholar at Mississippi State University, USA, focusing on Bioinformatics and Chemical Engineering, with additional external PhD work at Leipzig University, Germany. He has held research and postdoctoral positions at institutions including the A.I. Virtanen Institute for Molecular Sciences, SickKids and the University of Toronto, the University of Eastern Finland, Bar-Ilan University, Martin Luther University, Mosaiques Diagnostics, and UMC Groningen. His expertise spans machine learning, graph theory, statistics, supercomputing, bioinformatics, genetics, cardiovascular diseases, sarcopenia, and fusion proteins. Prof. Singh holds multiple advanced degrees, including an Erasmus MS in Mathematics, Computer Science and Economics from the University of Vienna, an MS in Computer Science, Statistics and Biomedicine from the University of Eastern Finland, an MBA from HHL Leipzig, and a Master’s in Management from KEDGE Business School, France. He earned his BTech from IIT Delhi with majors in Mathematics and Computer Science, Chemical Engineering, and Biotechnology. He has taught at undergraduate and postgraduate levels, previously served on the faculty at Virginia Tech and the University of Virginia School of Medicine, and actively contributes as a peer reviewer for leading journals such as Oxford University Press’s Bioinformatics Advances. He has published extensively across journals, books, and patents and is a recipient of the BIRAC E-Yuva Post-PhD Innovation Fellowship.

Speech Title: "DMWAS: Divergence-Encoded Multimodal Omics Wide Association Study (DMWAS): Evolutionary Structural Variant Embeddings for Transformer-Based Genomic Association Analysis "

Abstract: Genome-Wide Association Studies (GWAS) and Polygenic Risk Scores (PRS) have substantially improved genomic risk prediction but remain largely dependent on single nucleotide polymorphisms (SNPs) and additive statistical models. Structural variants (SVs), including insertions and deletions (InDels), represent a major source of genomic variation yet remain poorly represented in machine learning-based association studies. Existing approaches typically encode SVs as binary presence/absence variables, gene-loss events, graph genome structures, sequence k-mers, or literature-derived semantic embeddings. These approaches fail to preserve the evolutionary relationships inherent in structural genomic variation. We present Divergence-Encoded Multimodal Omics Wide Association Study (DMWAS), a transformer-based framework that embeds structural variants using phylogenetic divergence scores derived from multiple sequence alignment and consensus evolutionary distance modeling. Unlike conventional GWAS, PRS, gene-loss association studies (GLAS), graph-genome approaches, and NLP-derived genomic embeddings, DMWAS provides a continuous, biologically grounded representation of structural variation. Benchmark analyses using GTEx pilot datasets and simulated structural variant cohorts demonstrated superior predictive performance, achieving mean ROC-AUC values up to 0.86 across tissues and traits. Divergence-based embeddings consistently outperformed GWAS-derived markers, PRS, gene-loss models, k-mer embeddings, graph genome representations, convolutional sequence models, and NLP-derived genomic embeddings. These findings establish evolutionary divergence as a biologically interpretable representation of structural variation and suggest a new paradigm for next-generation machine learning association studies.

 

Assoc. Prof. Jin-Ku Lee
Seoul National University, South Korea

Jin-Ku Lee is an associate professor at Seoul National University College of Medicine (SNUCM), Korea. He achieved both M.D. (2003) and Ph.D. (2013) at SNU. His research fields of interests were cancer genomics and pharmacogenomic analysis using patient-derived tumor models for precision oncology. In respect to these research areas, he has published many SCI(E) articles, including Nature genetics (2017, 2018), Genome Biology (2019) and Biomaterials (2023). In particular, his lab is focused on developing cutting-edge technologies in patient tumor organoid cultures and 3D-based drug screening accompanied with systemic identification of genomic biomarkers for drug sensitivity.

Speech Title: "Integrative Genomic–Ex Vivo Response Profiling in Patient-Derived 3D Tumor Mode"

Abstract: A central challenge in precision oncology is that genomic information alone often fails to predict therapeutic response, because drug sensitivity is shaped not only by tumor cell-intrinsic alterations but also by three-dimensional tissue architecture and tumor microenvironmental interactions. To address this gap, we developed patient-derived 3D tumor biofabrication strategies that integrate functional ex vivo response profiling with genomic, single-cell, and spatial analyses. As a technical foundation, we established a high-throughput organo-on-pillar platform, high-TOP, which enables automated and standardized generation of extracellular matrix–embedded tumor microdomes. This system allowed reproducible drug-response measurement in ovarian cancer cell lines and patient-derived organoids, providing a scalable experimental basis for linking ex vivo carboplatin sensitivity with clinical chemotherapy response. Building on this functional platform, we asked how patient-specific signaling environments shape therapeutic vulnerability. Systematic profiling of 128 growth factor combinations revealed heterogeneous growth dependencies in patient-derived 3D cultures and identified estradiol-responsive tumor and stromal populations. Integrated transcriptomic and spatial analyses showed that MAL.PDCD5 malignant cells and FB.TNFSF10 fibroblasts coordinate immune suppression through reduced antigen presentation, TGF-β–linked CAF programs, and spatial exclusion of T/NK cells, thereby connecting hormone-responsive microenvironmental states to immunotherapy resistance. Finally, we applied the same logic to platinum response and identified stromal APOL4 as a marker and functional regulator of chemosensitive tumor niches. APOL4 defined an immunomodulatory, matrix-remodeling CAF-1 state, and APOL4 knockdown in CAFs induced carboplatin resistance in 3D tumor–CAF co-cultures, demonstrating that ex vivo response phenotypes can reveal causal stromal mechanisms. Together, these studies establish an integrated framework in which patient-derived 3D biofabrication functions as both a drug-response assay and a discovery platform for microenvironmental biomarkers, enabling tumor microenvironment-guided precision oncology.

 

 

Prof. Emeritus Hideo Matsuda
University of Osaka

Prof. Hideo Matsuda received his B.Sc. degree in Physics from Kobe University, Japan, in 1982, and he received his M.Eng. and Ph.D. degrees in Computer Science from Kobe University, Japan, in 1984 and 1987, respectively. He served as a Professor in the Department of Bioinformatic Engineering, Graduate School of Information Science and Technology at the University of Osaka between 2002 and 2025. In the Japanese Society for Bioinformatics (JSBi), he served as the Vice President (2008-2010), the President (2010-2013), and a Board Member (2019-2025). He also served as a Committee Member at the Bioscience Database Center in the Japan Science and Technology Agency (JST) between 2011 and 2026, and a Program Officer at the Research Center for Science Systems in the Japan Society for the Promotion of Science (JSPS) between 2016 and 2019. He received the Best Paper Award in the Asia-Pacific Bioinformatics Conference (APBC) in 2012, the Outstanding Paper Awards from the Information Processing Society of Japan (IPSJ) in 2014 and 2025, and the JSBi Prize from JSBi in 2024. He has co-authored about 180 bioinformatics publications including Nature, Science, JAMA, Nature Genetics, Nature Communications, Nucleic Acids Research, Genome Research, and Bioinformatics.

 

Prof. Dr. Muhamad Syarhabil Ahmad

Universiti Malaysia Perlis, Malaysia

Graduated in 2000 as a bachelor in chemical engineering from Purdue University, West Lafayette, IN, USA. Muhammad Syarhabil then pursued his Ph.D. from University of Wisconsin, Milwaukee in the field of chiral catalysis and organic syntheses and finished in 2008. He is a full professor, a professional engineer and a profesional chemist in the Faculty of Chemical Engineering & Technology in Universiti Malaysia Perlis, Malaysia. His interest in Malaysia’s native herbal extraction lead him to work in developing a green extraction process as “Solvent-free Extraction” and patented the process in Malaysia MY-156276-A and developed an equipment for the process. He also looked into safe and slow release of imidacloprid insecticide to control Malaysia’s dengue fever epidemic by ecapsulating the insecticide with Ca-chitosan-alginate combination. He then headed the Institute of Sustainable Agritech (INSAT) of UniMAP and researched in sustainable (RAS) recirculated aquaculture system by trying to incorporate and immitate a complete natural ecosystem starting from microorganism to the top of food chain. His work targetted multiple water species that is endengered, rare and caught in wild for consumption and difficult to rear in captives such as Marble Goby and still working on how to imrove and optimize the system. His interest in natures chlorophyl-protein interaction in harvesting and storing energy lead him to work in trying to increase the organic solar cell efficiency. He Incorporated the chelation complex of chlorophyllin and ferrocene in trying to direct electron movement flow. This later lead to his understanding and proposing electron movements for nature’s lycopene in (DSSC) dye-sensitized solar cell and is still working on how to improve organic solar cell efficiency. Currently his research interest dwelves in inhibiting corrosion using nanostructures especially in ecofriendly application. He was also the Dean in the Chemical Engineering faculty of UniMAP for many years and still active as a senate member of his Malaysian University. He is an active member in society by serving as an International Invited Speaker expert for Malaysian Agricultural Research Development Institute (MARDI)- AARDO African Asian Rural Development Development Organization for online training programme (OTP) in 2024 under the “Agricultural Nanotechnology: Catalysing Food Security and Sustainability. He is highly interested in research collaboration worldwide and eager to explore new and exciting frontiers in knowledge.

Dr. Souvik Kar
Principal Investigator/Biobank Head, International Neuroscience Institute, Germany

Dr. Souvik Kar holds a Master's degree in Zoology from India and was awarded the prestigious Georg Christoph Lichtenberg International Scholarship to pursue his Ph.D. in Neuroscience at Hannover Medical School, Germany. Following the successful completion of his doctoral research, he joined the International Neuroscience Institute (INI) Hannover as a Principal Investigator, where he established his own research laboratory and founded the institute's biobank facility. Dr. Kar currently oversees the central biobank at INI Hannover, which houses one of Germany's largest collections of human cerebral cavernous malformation (CCM) patient tissue and blood samples. His research laboratory was among the first to identify and characterize critical non-coding RNAs—including microRNAs, small nucleolar RNAs (snoRNAs), and long non-coding RNAs and coding RNAs—in CCM patients, particularly those with brainstem lesions. His research focuses on the molecular mechanisms underlying cerebrovascular diseases and the identification of coding and non-coding RNA signatures as predictive biomarkers in CCM. His work has identified molecular candidates with significant potential for improving early clinical diagnosis, patient stratification, and the development of novel therapeutic strategies for CCM. Dr. Kar has received multiple national and international research grants, including the ERA-NET NEURON European research grant (2022–2027), and Be Brave for Life Foundation supporting his research into cerebrovascular diseases. He also serves as a member of the Medical Advisory Board of the German Cavernoma Patient Organization, contributing his scientific expertise to the advancement of patient-oriented research and care in CCM.

Speech Title: "ELTD1 As a Novel Potential Prognostic Biomarker for Cerebral Cavernous Malformation Disease"

Abstract: Cerebral cavernous malformations (CCM) are angiographically occult vascular anomalies of the brain characterized by dilated capillaries, increased vascular permeability, and loss of endothelial junctional protein complexes [1]. Loss-of-function mutations in one of the three genes, namely KRIT1/CCM1, CCM2, and PDCD10/CCM3, have been associated with the disease pathogenesis. Despite recent advances in understanding the molecular mechanism of the disease, current lack of therapies and its unpredictable clinical behavior pose significant challenge in the identification of diagnostic biomarkers. The ETLD1 (epidermal growth factor, latrophilin and seven transmembrane domain-containing protein 1), a G-protein coupled receptor (GPCR) protein is an angiogenic biomarker, and has been suggested as a key therapeutic target for stroke and high-grade gliomas [2]. However, the relevance of ELTD1 in CCM pathogenesis remains unexplored. To identify and validate the expression of ELTD1 mRNA and protein levels in CCM disease, we employed various molecular biology methods such as RNA-seq, qRT-PCR, immunohistochemistry, and western blot. Through different analyses in human CCM patients, and in-vivo and in-vitro studies, herein we show the association between CCM and ELTD1, a known biomarker of angiogenesis and inflammation. Whole RNA transcriptome approach demonstrated ELTD1 is differentially expressed, whereas gene expression analysis revealed ELTD1 is significantly up-regulated in surgically resected tissue and plasma samples from CCM patients. Immunoexpression of ELTD1 showed a strong ELTD1-immunoreactivity in endothelial cells lining affected lesions. Further, we confirmed up-regulation of ELTD1 in cellular and animal models of CCM pathogenesis. Taken together, our results reveal for the first time a strong involvement of ELTD1 in CCM pathogenesis. Future clinical studies in larger patient cohorts and animal models of CCM disease will identify its role as a prognostic biomarker for early clinical diagnosis and risk stratification.

 

Asst. Prof. Jyong-Huei Lee
Yushan Young Fellow
National Taiwan University, Taiwan

I am an Assistant Professor of Engineering Science and Ocean Engineering (ESOE) and Global Undergraduate Program in Semiconductors (GUPS) at National Taiwan University, with expertise in semiconductor fabrication, biosensing technologies, and microfluidic systems. I earned my Ph.D. from The Pennsylvania State University (2019–2024), where I developed molecular biosensors and single-cell platforms for rapid pathogen identification in bloodstream infections and Alzheimer’s disease models, in collaboration with Stanford University and GE Healthcare. I also worked with the Gates Foundation to develop high-throughput microfluidic platforms for drug screening. Earlier, during my master’s studies at National Taiwan University (2015–2017), I established an integrated digital microfluidic organ-on-chip platform.

Speech Title: "Transforming Clinical Diagnostics through Multimodal Biosensors, Single-Cell Profiling, and Microfluidics"

Abstract: Recent advances in clinical diagnostics have been driven by the need for rapid, quantitative, and functionally informative analysis of complex biological systems. Conventional microbiological and sequencing-based methods, while powerful, often require long turnaround times and may have limited sensitivity in low-biomass samples. They also cannot adequately resolve cellular heterogeneity or functional activity, limiting their application in real-time clinical decision-making. Multimodal biosensors offer a promising approach for high-resolution, single-cell clinical diagnostics. By integrating molecular probes targeting 16S rRNA and mRNA, the proposed platform enables simultaneous characterization of microbial identity, viability, and functional activity at the single-cell level. Microfluidic systems further enhance diagnostic performance through automated sample processing, high-throughput analysis, and rapid turnaround times compatible with clinical workflows. This integrated platform enables culture-free detection and accelerates antimicrobial susceptibility testing, supporting timely therapeutic decisions. Single-cell measurements can also reveal phenotypic heterogeneity and host–microbe interactions that are inaccessible through conventional bulk analysis. By combining molecular sensing, single-cell analysis, and microfluidics, this approach provides a versatile framework for next-generation diagnostics, with potential applications in infectious diseases, microbiome-associated disorders, personalized therapy, and rapid functional profiling of clinical samples.

 

Prof. Igor Zhukov
Polish Academy of Sciences, Poland

Dr. Igor Zhukov, Professor at the Institute of Biochemistry and Biophysics, Polish Academy of Sciences (Warsaw, Poland), heads the Laboratory of Biological NMR. He earned a PhD in the structural analysis of Ca-binding S100 proteins in solution using NMR data. For five years, he worked at the Slovenian NMR Center (Ljubljana, Slovenia), where he performed structural studies of several pathological mutants of human prion protein (PrPC). After returning to IBB PAS, he worked on several projects involving structural analysis of membrane peptides and proteins and explored molecular dynamics processes in the protein backbone using 15N relaxation data. Recently, he began developing 19F NMR spectroscopy for applications to proteins and peptides containing paramagnetic metal ions (Cu, Fe, Ni, etc.). This technique shed light on oligomerization phenomena observed in Alzheimer peptides upon copper binding. Dr. Zhukov has authored more than 70 publications indexed in the Scopus database.

Speech Title: "Structural characterization of complex Cowpox Herpesvirus with antigenic peptide transporter (TAP) by multidimensional NMR spectroscopy and molecular dynamics simulations"

Abstract: Alphaherpesviruses encode immunomodulatory proteins that inhibit antigenic peptide transporter (TAP) function, allowing viral evasion of host immune responses. In this study, we analyze the CPXV012 protein, encoded by cowpox herpesvirus (CPXV). We divided the CPXV012 sequence into three fragments, synthesized as peptides, and analyzed them using multidimensional NMR spectroscopy. The 3D structures of the endoplasmic and cytoplasmic fragments showed an α-helical conformation for most residues, consistent with the AlphaFold model. Recently, cryo-EM determined the high-resolution structure of a TAP-CPXV fragment complex. Based on NMR structural data and molecular dynamics (MD) simulations, we conclude that CPX-E1 plays a key role in binding CPXV to TAP and identify residues that form critical hydrogen bonds with residues in the TAP subunits. As a result, CPXV locks TAP in a non-functional, outward-facing conformation, preventing it from rotating back to its inward-facing state to pick up peptides. Our results provide insight into viral immune evasion strategies and make possible the development of novel antiviral treatments against CPXV infections.

 

Prof. Yayoi Natsume-Kitatani
Kobe University, Japan

Dr. Yayoi Natsume-Kitatani is a Professor in the Department of Science, Technology and Innovation at Kobe University, where she joined in October 2026. She received her Ph.D. in Agriculture from the University of Tokyo in 2008. Her doctoral research investigated the molecular mechanisms by which dietary flavonoids protect intestinal epithelial cells from stress. This work sparked her interest in how biologically meaningful knowledge and hypotheses can be derived from large-scale data, and she changed her field to computational biology. She joined the Bioinformatics Center, Institute for Chemical Research, Kyoto University, as a postdoctoral fellow in 2008, and became a PRESTO researcher at the Japan Science and Technology Agency (JST) in 2010. In 2015, she joined the National Institutes of Biomedical Innovation, Health and Nutrition (NIBN), Japan, where she remained until September 2026, leading projects that integrate AI/machine learning and bioinformatics to accelerate drug discovery. At the AI Center for Health and Biomedical Research (ArCHER) at NIBN, she progressed from Senior Researcher and Sub Project Leader to Project Leader of the Bioinformatics Project (2021), then served as Deputy Director (2023) and Acting Director (2024), and was appointed Director in April 2025. Her research applies AI and machine learning to clinical and omics data to extract knowledge that drives data-driven drug discovery and medicine.