Pascal Frossard is a Full Professor at the Department of Electrical Engineering in the School of Engineering (STI) at EPFL, with a courtesy appointment in the School of Computer and Communication Sciences. He founded and directs the LTS4 laboratory since 2003, co-leads the EPFL AI Center and Swiss Data Science Center, and serves as Associate Dean for Research at STI. Research Focus: Machine Learning, Graph Signal Processing, AI Applications in Healthcare, Computer Vision Academic Leadership: IEEE Fellow, ELLIS Fellow, Conference Chair roles Key Projects: Digital Pathology for Oncology, Cardiac Digital Twins, Robust Machine Learning Research Interests: His work bridges signal processing, machine learning, and applied mathematics, emphasizing biomedical applications. Recent research includes adversarial robustness in classifiers, network representation learning, and 360-degree video analysis. Scientific Awards: IEEE Fellow ELLIS Fellow Leadership in IEEE technical committees Advising & Grants: Supervised 20+ PhD students and postdocs. Secured major grants from PHRT, Hasler Foundation, FNS-Sinergia, Armasuisse, Google, and Cisco.
Ole Winther is Professor in High dimensional biological data analysis/Machine learning at the Department of Biology, University of Copenhagen and Professor in Data science and complexity at DTU Compute, Technical University of Denmark. He serves as CRO and co-founder of raffle.ai, CTO and co-founder of FindZebra, Head of ELLIS Unit Copenhagen, and co-PI of the Machine Learning for Life Science Center. His research spans Bioinformatics , Machine Learning , and AI for Science , focusing on applying deep learning to biological sequence analysis, latent variable models, and medical NLP. Winther's work develops predictive and generative models for bioinformatics, with significant contributions to protein localization tools (SignalP, DeepLoc, DeepTMHMM), single-cell genomics, and novel deep learning architectures like variational autoencoders and diffusion models. Analysis of Winther's recent publications (2023-2025) reveals a strong trend toward integrating protein language models with traditional bioinformatics approaches and applying diffusion models to scientific problems. His work bridges theoretical machine learning advancements with practical applications in biology and medicine, particularly in protein sequence analysis, medical search engines, and scientific simulation acceleration. Winther currently supervises a diverse research group including Panagiotis Antoniadis, Rachael M. DeVries, Jun Wang, Beatrix M. G. Nielsen, Felix G. Teufel, Irene R. Rodriguez, Anders Christensen, and Christopher Heje Grønbech. His former students have established successful careers at institutions including Google, Apple, and various startups, with notable alumni like Casper Sønderby (Google Brain) and Søren Sønderby (Apple). He leads significant research initiatives including the ELLIS Unit Copenhagen and the Machine Learning for Life Science Center, while maintaining active industry partnerships through his co-founded companies raffle.ai (enterprise search using NLP) and FindZebra (search engine for rare diseases). His teaching includes Deep Learning courses at both DTU (02456) and University of Copenhagen (NDAK24002U).
Alexis Battle is an Associate Professor at Johns Hopkins University with appointments in Biomedical Engineering , Computer Science , and Genetic Medicine (secondary). She directs the Malone Center for Engineering in Healthcare and serves as Deputy Director of the Data Science and AI Institute . Educated at Stanford University (PhD in Computer Science, 2013), Battle transitioned to academia after leadership roles at Google. Research Focus: Battle’s work bridges genomics and machine learning , emphasizing the impact of genetic variation on human health. Her lab develops tools like Watershed to predict functional effects of rare variants, aiming to enhance rare disease diagnosis. Key themes include non-coding DNA analysis , personalized genomics , and systems biology , with applications in cardiovascular disease and neurodegenerative disorders . Publications & Awards: Over 60 peer-reviewed articles in journals like Nature , Science , and Genome Biology , with recent emphasis on single-cell transcriptomics , multiomics integration , and telomere biology . Recipient of the President’s Frontier Award (2022), Microsoft Investigator Fellowship (2019), and Searle Scholar (2016). Scientific Awards: 2022 President’s Frontier Award 2019 Microsoft Investigator Fellowship 2019 Johns Hopkins Discovery Award 2017 Johns Hopkins Catalyst Award 2016 Searle Scholar Advising & Funding: Mentors 11 PhD students, 3 undergraduates, and postdoctoral fellows. Her research is funded by NIH, Searle Scholars, and institutional grants. The Battle Lab collaborates on projects like the GTEx Consortium , focusing on gene regulation and clinical genomics .
Thomas Michaels is an Assistant Professor at the Department of Biology, ETH Zürich, leading the Michaels Group . His research focuses on theoretical models of biomolecular condensates and protein aggregation in biological systems. Research Themes : Protein aggregation, liquid-liquid phase separation, membrane biophysics, and the role of condensates in neurodegenerative diseases like Alzheimer’s and Parkinson’s. Collaborative Approach : Integrates theoretical physics, control theory, and computational biology with experimental validation to design therapeutic strategies. Recent Publications highlight his work on amyloid formation mechanisms, lipid interactions, and phase-separated compartments as biochemical reactors. His group trains PhD students in systems biology and biocondensate physics.
Qiaowei Pan is a Researcher at the University of Lausanne , focusing on Evolution and Ecology . They have held a Guest Researcher role at the Institute of Molecular Biology gGmbH (IMB) in Mainz, Germany since 2023, and a Postdoctoral Researcher position at the University of Lausanne since 2018. Education: PhD in Molecular and Evolutionary Biology (2014-2018), INRAe, University of Rennes II, France Erasmus Mundus Master in Evolutionary Biology (MEME) (2012-2014), University of Groningen (Netherlands) & University of Montpellier II (France) BSc in Biology (2008-2012), University of North Carolina-Chapel Hill, USA Research Interests: Qiaowei Pan's work centers on the intersection of molecular genetics , evolutionary biology , and developmental biology , particularly in sex determination mechanisms across diverse animal models. Their studies span non-coding RNA regulation , sex chromosome evolution , and signal transduction pathways like TGF-β in reproductive systems. Publication Trends: Recent articles highlight expertise in sex determination systems (5/12 publications), genomic approaches (6/12), and fish developmental evolution . Collaborative work includes computational methods ( RADSex workflow ) and comparative studies across ant , goldfish , catfish , and cavefish models. Labs & Teams: Currently affiliated with the Keller-Valsecchi group at IMB and the Department of Evolution and Ecology at the University of Lausanne.
Professor Knut Reinert is a leading figure in algorithmic bioinformatics at the Free University of Berlin, where he holds a professorship in the Department of Mathematics and Computer Science. He also maintains a significant affiliation with the Max Planck Institute for Molecular Genetics in Berlin, where he leads the Efficient Algorithms for Omics Data group. His research spans both institutions through the Reinert Lab, which focuses on developing novel computational approaches for biological data analysis. Reinert's educational background includes a Diploma in Computer Science (1994) and a Doctorate (Dr. Ing./Ph.D., 1999, with honors) from the Max-Planck-Institut for Computer Science and Universität des Saarlandes in Saarbrücken. Prior to his professorship, he worked as a computer scientist under Prof. Gene Myers at Celera Genomics in Rockville, USA (1999-2002). His primary research interests center on algorithmic bioinformatics with specific focus on developing novel algorithms and data structures for biomedical mass data analysis. This includes creating mathematical models for genomic sequence analysis and algorithms for mass spectrometry data to detect differential protein expression between normal and diseased samples. His work bridges the gap between computational tool development and practical biological applications, with particular emphasis on NGS and proteomics data. The publications and projects led by Prof. Reinert demonstrate a consistent focus on advancing computational methods in bioinformatics. His research spans genomic sequence analysis, RNA research (particularly long non-coding RNAs), parallel computing applications, and GPU acceleration for biological data processing. The work shows increasing sophistication in handling large-scale biological datasets through innovative algorithmic approaches. Intel® Parallel Computing Center designation for his lab CUDA Research Center status DFG funding of 530 thousand Euros for RNA research de.NBI funding of 2 million Euros BMBF funded projects 'LIVE-DREAM' and 'EssBar' Prof. Reinert leads multiple significant research projects and has established strong collaborations with international partners including Texas A&M, Kings College London, Eberhardt-Karls Universität Tübingen, Robert-Koch-Institute, and various Turkish institutions. His lab receives funding from major organizations including DFG, BMBF, and Intel. The Reinert Lab maintains active teaching responsibilities at FU Berlin, offering courses at BSc, MSc, and PhD levels using both traditional and innovative learning concepts like e-learning and inverted classrooms. The Reinert Lab consists of two interconnected research groups that work closely with experimental biologists and medical researchers to develop practical computational solutions for real-world biological problems. The lab has established itself as a key player in the German and international bioinformatics community through its development of the widely-used SeqAn library and participation in national infrastructure initiatives.
Dr. Lourdes Pena-Castillo is a Professor jointly appointed in the Departments of Computer Science and Biology at Memorial University of Newfoundland's Faculty of Science. Her research focuses on applying machine learning and bioinformatics to study bacterial gene regulation, with emphasis on transcriptomics, gene expression pathways, and microbiology. She leads the Bioinformatics Lab at MUN, developing computational tools like Promotech for promoter prediction and sRNARFTarget for sRNA target identification. Education: BSc in Information Systems Engineering, ITESM-Mexico MSc in Computer Science, University of Alberta PhD in Computer Science (Doktoringenieurin), Otto-von-Guericke Universität Magdeburg Postdoc in Bioinformatics, University of Toronto Research Interests: Bioinformatics, Genomics, Machine Learning, Artificial Intelligence, Transcriptomics, Gene Regulation, Microbiology Her work integrates computational methods with biological data to address challenges in molecular biology, including analyzing bacterial sRNA functions, promoter recognition, and disease diagnostics using machine learning. She has advised numerous graduate students, including PhD candidates Purvikalyan Pallegar and Bonita McCuaig, and MSc students like Ruben Chevez-Guardado and Kratika Naskulwar. Her lab focuses on translational research with applications in both basic science and clinical contexts. Publications span computational methods for bacterial gene regulation, bioinformatics tool development, and interdisciplinary projects in VR and healthcare informatics. Her research has contributed to understanding symbiotic relationships in marine organisms, inflammatory bowel disease diagnostics, and clavulanic acid production in Streptomyces. Grants & Collaborations: Works with interdisciplinary teams across computer science and biology, supported by grants enabling projects in bacterial genomics and computational tool development. Labs & Teams: Leads the Bioinformatics Lab at MUN, fostering collaborations with researchers in microbiology, computer science, and healthcare.
Dr. Sabine Krabbe is a Group Leader at the German Center for Neurodegenerative Diseases (DZNE) in Bonn, Germany, where she leads research on neural circuit mechanisms underlying adaptive learning and state-dependent decision-making. Her work integrates neuroscience, molecular biology, and behavioral approaches to understand how internal states influence behavior and how these processes are disrupted in neurological disorders. Dr. Krabbe's research focuses on the interactions between midbrain circuits of the substantia nigra and ventral tegmental area with their output structures such as the striatum and amygdala. She investigates how these networks integrate internal states with environmental cues to produce appropriate behavioral responses. Her laboratory employs state-of-the-art techniques including deep-brain calcium imaging at single-cell resolution in mice, opto- and pharmacogenetic manipulations, anatomical tracings, and molecular approaches to characterize neural circuit elements in detail. Her recent publications reveal significant insights into amygdala interneuron plasticity during fear learning, brain-wide representational drift in memory consolidation, and the molecular mechanisms underlying Parkinson's disease progression. Her work demonstrates how activity patterns within specific neural circuits change in early stages of neurodegenerative diseases and how this dysfunction contributes to cognitive deficits and emotional disturbances. Dr. Krabbe is actively involved in the neuroscience community, organizing the BonnBrain Conference 2026 and sharing research through social media platforms. She has established herself as an emerging leader in the field of systems neuroscience with a particular focus on the neural basis of emotional states and decision-making processes.
Dr. Yunfei Jiang is an Assistant Professor in the Department of Plant, Food, and Environmental Sciences at Dalhousie University's Faculty of Agriculture. Her research focuses on improving crop resilience to climate change and sustainable agronomic practices in Atlantic Canada, with expertise in agronomy, crop physiology, and environmental stress responses. She holds a Ph.D. in Plant Science from the University of Saskatchewan (2017), an M.Sc. from Dalhousie University (2013), and a B.Sc. in Horticulture from Fujian Agriculture and Forestry University (2010). Her research includes evaluating enhanced efficiency fertilizers, biochar, and intercropping systems to enhance soil health and crop yields. She teaches courses such as AGRN2001 (Cereal-Based Cropping Systems) and PLSC2001 (Plant Propagation Techniques). Funding and awards details, along with her graduate students' projects, are available on her lab website at jiangdal.ca . Dr. Jiang is affiliated with professional organizations including the Nova Scotia Institute of Agrologists and the American Society of Agronomy. Her lab, the Agronomy and Crop Physiology (ACP) Lab, emphasizes sustainable agriculture and crop adaptation to environmental challenges. Contact her via email at yunfei.jiang@dal.ca or visit her lab's address: PO Box 550, Truro, NS B2N 5E3.
Dieter Braun is a Professor in the Faculty of Physics at Ludwig Maximilian University of Munich (LMU), leading the Functional NanoSystems research group. He serves as speaker of the CRC 235 Emergence of Life and coordinates the Molecular Origins component of the Origins Cluster. Dr. Braun holds an ERC Synergy Grant (starting April 2025), leads the CRC 392 Molecular Evolution (starting April 2024), and is a Fellow in the Max Planck School Matter to Life (since October 2023). His research focuses on understanding the physical mechanisms that could have led to the emergence of Darwinian evolution from prebiotic molecules on early Earth. Braun's laboratory investigates non-equilibrium settings, particularly asymmetrically heated open cracks in rocks, which create intricate wet-dry cycles, temperature gradients, and fluidic effects that could drive molecular evolution. His work bridges physics, chemistry, and biology to explore how dead molecules might combine through physical forces into autonomous mechanisms of evolution. Analysis of Braun's recent publications reveals a strong focus on thermal gradients and non-equilibrium physics in prebiotic environments. His research demonstrates how heat flows can concentrate molecules, drive polymerization, create pH gradients, and enable non-enzymatic replication of nucleic acids. The publications span high-impact journals including Nature, Nature Physics, and Nature Chemistry, showing interdisciplinary work connecting physics, chemistry, geology, and biology in the context of life's origins. Klung-Wilhelmy Weberbank Price (2011) Technology Transfer Price of the DPG (with LMU and NanoTemper) Deutscher Innovationspreis (2012) Step Award (2012) Dr. Braun has successfully mentored numerous PhD students, including Stefan Duhr and Philipp Baaske who founded the award-winning startup NanoTemper Technologies. His research is supported by multiple prestigious grants including ERC Starting, Advanced, and Synergy Grants, as well as funding from the Simons Collaboration on the Origins of Life. His laboratory collaborates extensively with other researchers across disciplines and institutions, particularly with Hannes Mutschler in the new ERC Synergy project. The Braun laboratory operates within the CRC 235 Emergence of Life and the Origins Cluster at LMU Munich, with strong connections to the Max Planck Society through the Max Planck School Matter to Life. The research group maintains active collaborations with geochemists, biophysicists, and molecular biologists to create comprehensive experimental models of prebiotic environments.
Lin He is the Thomas and Stacey Siebel Distinguished Chair in Stem Cell Research and Professor of Cell Biology and Physiology at the University of California, Berkeley. His laboratory focuses on understanding the biological functions of non-coding RNAs in development and disease, with particular emphasis on microRNAs (miRNAs) in cancer, stem cell biology, and developmental processes. He developed the CRISPR-EZ method for highly efficient mouse genome editing, significantly advancing genetic research. Research interests include miRNAs' roles in tumor progression, metastasis, and pluripotency regulation in stem cells. His work bridges mouse genetics, genomics, and molecular biology to uncover mechanisms governing non-coding RNA functions. Current projects address miRNAs in oncogenesis, stem cell fate determination, and the interplay between non-coding RNAs and retrotransposons in development. Key contributions include identifying miRNA networks in cancer pathways, demonstrating miRNA requirements for ciliogenesis and lung development, and advancing CRISPR-based genome editing techniques. His interdisciplinary approach integrates genetic, genomic, and cellular tools to explore fundamental questions in biology and medicine. Lab website: helabucb.org CRISPR-EZ technology enables 100% genome editing efficiency in mouse zygotes Pioneering studies on miRNA regulation of PTEN, p53, and oncogene pathways
Jens S. Andersen is a Professor in the Department of Biochemistry and Molecular Biology at the University of Southern Denmark, where he leads research in Biomedical Mass Spectrometry and Systems Biology. His work is centered on the development and application of quantitative mass spectrometry and microscopy-based proteomics to study human cell biology, particularly the structure and function of organelles such as centrosomes, cilia, autophagosomes, and mitochondria. His research focuses on determining the protein composition and dynamic properties of cellular organelles, the roles of specific protein groups, and their contributions to biological processes and diseases. He investigates cell signaling mediated by post-translational modifications, especially within the DNA damage response, autophagy, and immune systems. His lab, the Jens S. Andersen Lab, is part of the Research Section of Biomedical Mass Spectrometry. The analysis of his recent publications reveals a strong interdisciplinary trend combining proteomics, structural biology, and cell signaling. His work spans cilia biology, RNA metabolism, DNA repair, and cancer mechanisms, with frequent use of advanced techniques like mass spectrometry, CRISPR, and live-cell imaging. The integration of systems biology approaches is evident across his research outputs. Professor, Department of Biochemistry and Molecular Biology, University of Southern Denmark Head of Research, Biomedical Mass Spectrometry and Systems Biology Principal Investigator, Jens S. Andersen Lab ORCID: 0000-0002-6091-140X While no specific scientific awards are mentioned in the provided texts, his extensive publication record in high-impact journals such as Science , Nature Communications , Molecular Cell , and EMBO Journal reflects significant scholarly contributions. He has supervised research projects and collaborated widely across Europe, though specific names of students are not listed. His research is supported by multiple ongoing projects, reflecting sustained funding and academic leadership. The Jens S. Andersen Lab operates at the intersection of proteomics and cell biology, contributing to fundamental understanding of organelle dynamics and disease mechanisms. The lab's work is highly collaborative, involving partnerships with groups in structural biology, RNA research, and cancer biology.
Peter A. Jones is President and Chief Scientific Officer at the Van Andel Institute (VAI) in Grand Rapids, Michigan, where he leads the Department of Epigenetics. He previously served as Director of the USC Norris Comprehensive Cancer Center from 1993 to 2011 and has been a central figure in advancing epigenetics research, particularly in cancer. His laboratory investigates DNA methylation, chromatin dynamics, and epigenetic therapies. Research Interests: Dr. Jones's work centers on epigenetic mechanisms in cancer, including DNA methylation, histone modifications, nucleosome positioning, and the therapeutic potential of epigenetic drugs. His research has pioneered the use of DNA methylation inhibitors like 5-azacytidine and explored viral mimicry as a mechanism for immune activation in cancer. He also studies transposable elements and their role in gene regulation and immune response. Publication Trends: His recent publications (2021–2024) reveal a strong focus on the interplay between epigenetics and immunotherapy, particularly how DNA methyltransferase inhibitors (DNMTi) induce viral mimicry, enhance immune recognition, and improve responses to checkpoint blockade. Studies span hematological malignancies, solid tumors, and T cell biology, with frequent collaboration with Stephen Baylin and others. Scientific Awards: Member, National Academy of Sciences Member, National Academy of Medicine Fellow, AACR Academy Fellow, AAAS Fellow, American Academy of Arts and Sciences Kirk A. Landon Award for Basic Cancer Research (2009) Medal of Honor, American Cancer Society (2011) Outstanding Investigator Grant, NCI Harvey Prize (2024) Advising and Grants: Dr. Jones mentors multiple postdoctoral fellows, graduate students, and research scientists. His lab is supported by major grants, including the VAI-SU2C Epigenetics Dream Team, which has launched 15 clinical trials. He has received sustained funding from the National Cancer Institute and collaborates with institutions worldwide to advance epigenetic therapies. Labs and Teams: He leads the Peter Jones Laboratory at VAI, a multidisciplinary team investigating epigenetic regulation in cancer. The lab includes computational biologists, clinical researchers, and molecular biologists, working on both basic mechanisms and translational applications. The team is part of larger collaborative initiatives such as the VAI-SU2C Epigenetics Dream Team and the International Linked Clinical Trials Program.
Kathrin Lang is a Full Professor at the Department of Chemistry and Applied Biosciences, ETH Zurich, and Head of the Organic Chemistry Laboratory. Her research focuses on chemical biology, particularly the development of tools for genetic code expansion to incorporate non-canonical amino acids into proteins and advance bioorthogonal chemistries for studying biological processes. Keywords: Genetic Code Expansion, Bioorthogonal Chemistry, Protein Engineering, Ubiquitylation Networks, Post-Translational Modifications. Lang’s work emphasizes proximity-triggered crosslinking reactions, bioorthogonal labeling, and in vivo chemistries to address challenges in protein interaction mapping and structural elucidation. Her group’s recent publications highlight methodologies for dual protein labeling, deciphering ubiquitin code, and enhancing cycloaddition reactivity. Current projects include exploring cyclopropene-fused dibenzocyclooctynes for improved labeling and investigating methylated lysine as a conformational regulator in Hsp90. Funding sources include the ERC (Ubl-tool), DFG (SFB1035, SPP1926), and ETH Zurich. She contributes to education through courses like Genetic Code Expansion for Studying Posttranslational Modifications and Chemical Biology and Synthetic Biochemistry . Collaborative efforts span structural biology, microbiology, and synthetic biochemistry, with applications in ubiquitin research and cellular imaging.
Igor Jurisica is a Professor at the University of Toronto and a Senior Scientist at the Krembil Research Institute’s Data Science Discovery Centre for Chronic Diseases. He also serves as Visiting Scientist at IBM CAS, Scientific Director of the World Community Grid, and Chief Scientist at the Creative Destruction Lab (Rotman School of Management). His research focuses on integrative computational biology, data mining, and AI-driven models for cancer mechanisms, drug discovery, and chronic disease management. Key affiliations include the Osteoarthritis Research Program, Schroeder Arthritis Institute, and leadership roles in open science initiatives like the World Community Grid, a global distributed computing platform with 810,000+ volunteers. Jurisica’s work bridges computational tools (e.g., NAViGaTOR visualization platform, MirDIP databases) and clinical applications, emphasizing explainable AI in healthcare. Research interests span proteomics, microRNA regulation, systems vaccinology, and multi-omics integration for disease stratification. Notable contributions include identifying prognostic signatures in cancer and osteoarthritis, machine learning models for drug repurposing, and sportomics analyses of athletic biomarkers. He has been recognized as a Thomson Reuters Highly Cited Researcher (2014-2016) and ranked among the Top 100 AI Leaders in Oncology (2023). His labs develop open-access tools like PathDIP, OsteoDIP, and miRAnno to advance translational research.
