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.

Assoc. Prof. Shweta Gupta
CMR University, Bengaluru, India

Dr. Shweta Gupta is Associate Professor in Department of Artificial Intelligence and Machine Learning, School of Engineering and Technology, CMR University, Bengaluru. He graduated her Electronics Engineering from Pune University, India and M.S. from Bits Pilani, Doctorate from Dr. K. N. Modi University, India and Executive MBA from I.I.M. Lucknow in Executive Global Business Management Programme. She has 6 patents published and one granted. She is Editor in IGI Global publisher book named “Bio-Inspired Algorithms and Devices for Cognitive Diseases using Future Technologies "with 600 USD initial Honoranium. Edited book for Taylor and Francis titled “Cognitive Predictive Maintenance Tools for treatment of Brain Diseases – Design and analysis" with 600 USD initial amount against royalty .She is Free Virtual Keynote Speaker in Euro- Global Conference on Biotechnology and Bioengineering ( ECBB 2024 ) , Rome Italy .Keynote Speaker at the 9th International Conference on Biomedical Engineering and Pharmaceutical Sciences (ICBEPS 2024) , Singapore .Keynote Speaker at the 10th International Conference on Biomedical Engineering and Pharmaceutical Sciences (ICBEPS 2024), Singapore. Topic: “Effect of Indian Food on Mental Health”. Her speech as come on Chinese BiliBili Platform. Awarded as Senior Scientist under International Travel Support Scheme by Science and Engineering Research Board (SERB Department) and sent to ICBBT2015, Singapore for a Research Paper Presentation. She was member of Elsevier Advisory Panel as on June 1st, 2022. She is Section Editor for Section Collection on “Big data and Artificial Intelligence” (ISSN 2811-0188) and Section Editor for "Wearable Devices" Section of the Wearable Technology (ISSN 2810-9783) journal, Asia Pacific Academy of Science Pte. Ltd, USA.

Speech Title: "Regenerative Medicine for Treatment of Cognitive Diseases"

Abstract: Most of the Cognitive Diseases happen due to death of certain brain cells which secretes neurochemicals that secrete those neurotransmitters, which when the brain stops getting it starts behaving indifferently and either movement of the body gets distorted like in Parkinson’s Disease etc. The idea here is that now instead to giving pills that can combat the deficiency of those neurochemicals due to death of dopamine generating cells in the substantia region of the brain, we do stem therapy for regeneration of dead cells in the substantia nigra region of the brain and the let new grown cells secrete dopamine naturally for Parkinson’s Disease. Major age-related diseases like stroke and Demetia are treated by repairing the dead cells or regenerating the dead brain cells using the concept of stem cells that can develop into neural brain cells. To develop the cell types depends on the gene types in the normal human development in the nervous system which result in neurons and different astrocytes that make up the brain. Thus, by simply changing culture conditions we could promote different cell phase and mature versions of brain cells. Thus, in layman terms instead of giving insulin to diabetic patient, we develop the insulin secreting cells that can secrete insulin naturally in body.