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Jernej UleView profile

Professor

• RNA Biology
• Neurodegenerative Diseases
• Neuroscience
• +7 more

Jernej Ule is the Van Geest Professor of Neurodegeneration Research at King's College London and Director of the UK Dementia Research Institute (UK DRI) at King's. He leads the RNA Networks Laboratory, focused on understanding RNA's role in neurodegenerative diseases like ALS and FTD. His research integrates biochemistry and computational biology to map protein-RNA interactions. Key roles include Group Leader at the Francis Crick Institute and Professor of Molecular Neuroscience at UCL prior to joining King's in 2022. Affiliations: UK DRI, Francis Crick Institute, Institute of Psychiatry, Psychology & Neuroscience (IoPPN) Education: BSc from University of Ljubljana (1999), PhD from Rockefeller University (2004) under Robert B. Darnell Research interests center on RNA networks in neuronal function and disease, including RNA-binding proteins, condensates, and alternative splicing. His lab developed methods like iCLIP for transcriptome-wide analysis. Collaborations include Andrea Serio, Sonia Gandhi, and Pietro Fratta. Awards include the RNA Society Mid-Career Award (2020) and Person of the Year 2019. Key grants include a Wellcome Trust £5.4M award (2023) for gene regulation studies in neurodegeneration. He leads projects on RNA metabolism, protein aggregation, and tau-RNA interactions. His lab is part of the RNA Biology Research Interest Group and contributes to the Maurice Wohl Clinical Neuroscience Institute. Future work emphasizes therapeutic strategies targeting RNA dysregulation in ALS/FTD.

Hang Joon KimView profile

Professor

• Bayesian Statistics
• Causal Inference
• Statistical Genomics
• +6 more

Hang Joon Kim is a Professor in the Division of Statistics and Data Science within the Department of Mathematical Sciences at the University of Cincinnati's College of Arts and Sciences. He joined the university in 2015 as an Assistant Professor, was promoted to Associate Professor in 2021, and became a full Professor in 2025. His research spans multiple areas of statistics with applications in various scientific domains. Dr. Kim received his educational training from prestigious institutions: Ph.D. in Statistics from The Ohio State University, Columbus, OH M.S. in Applied Statistics from Yonsei University, Seoul, Korea B.A. in Applied Statistics from Yonsei University, Seoul, Korea B.A. in Business from Yonsei University, Seoul, Korea Dr. Kim's research focuses on advanced statistical methodologies with particular emphasis on Semiparametric Bayesian modeling , Causal inference , Meta analysis , Statistical genomics , Missing data , Survey sampling , Data privacy , and Synthetic data generation . His work bridges theoretical statistics with practical applications in biomedical research, official statistics, and data science. He has developed innovative approaches for handling complex data structures while maintaining statistical rigor and practical utility. His recent publications demonstrate a strong trend toward integrating multiple data sources while addressing privacy concerns. The 15 most recent articles show increasing focus on Bayesian methods for causal inference, synthetic data generation for privacy protection, and statistical approaches for genomic studies, reflecting his leadership at the intersection of statistical theory and real-world applications. Dr. Kim has received numerous prestigious awards and honors: Industrial Service Medal of Honor from the President of the Republic of Korea (Sep 2024) A&S Rising Star Award from the College of Arts and Sciences, University of Cincinnati (Apr 2018) Summer at Census Scholar from the U.S. Census Bureau (June 2017) KISS Career Development Award from the Korean International Statistical Society (Aug 2015) American Statistical Association Student Paper Award (Aug 2012) As an advisor, Dr. Kim has successfully mentored multiple PhD students to completion, with graduates securing academic and industry positions. His current research is supported by significant grants including an NSF-funded project on "Robust and efficient Bayesian inference for misspecified and underspecified models" (2024-2027) and a National Research Foundation of Korea project on "Statistically synthetic data generation" (2025-2028). He has served as PI on multiple substantial research projects totaling over $400,000 in funding. Dr. Kim leads research efforts in statistical methodology development, particularly in Bayesian modeling and data privacy. He has developed several R packages including synMicrodata for synthetic data generation, GGPA for genomic analysis, clusterMI for clustering with missing data, and DPImputeCont for imputation of continuous data. His work has practical applications in official statistics, biomedical research, and data science.

• Neuroscience
• Psychiatry
• Behavioral Genetics
• +4 more

Taylor Robert Young MD, MA, BA is an Assistant Professor in the Department of Psychiatry and Behavioral Sciences at UMass Chan Medical School, specifically within the T.H. Chan School of Medicine. His professional address is at UMass Memorial, 26 Queen Street, Worcester, MA 01610. His educational background includes: BA in Biology, Ecology & Evolution from Clark University, Worcester, MA MA in Environmental Science & Policy from Clark University, Worcester, MA MD from University of Massachusetts Medical School, Worcester, MA Dr. Young's research spans multiple disciplines at the intersection of neuroscience, psychiatry, and genetics. His work prominently features brain imaging techniques with a focus on thalamic structures, particularly examining volume alterations in neurodegenerative conditions like Alzheimer's Disease and psychiatric disorders such as schizophrenia. His research portfolio also encompasses genetic epidemiology, with significant contributions to studies on substance use disorders, including alcohol consumption patterns and smoking behavior across different populations. His work frequently employs advanced genomic methodologies to investigate the genetic underpinnings of various health conditions. Analysis of Dr. Young's publication history shows a consistent research trajectory from 2011 through 2024, with particular concentration in neuroscience and psychiatric genetics in recent years. His 2023-2024 publications demonstrate a sophisticated approach to neuroimaging analysis, particularly regarding thalamic nuclear volumes, while maintaining his longstanding interest in genetic factors influencing health behaviors. Dr. Young has established a robust collaborative network, working with researchers across multiple institutions on complex, multi-author studies. His work has been disseminated through high-impact journals including Science, Nature Genetics, and Biological Psychiatry. His research has garnered attention across various platforms, with mentions in news outlets, social media, and academic networks. His departmental colleagues include researchers such as Saranathan Manojkumar, Harris John, Ko Wei-Che, Vanguri Vijay, and Deng April, suggesting active participation in a vibrant research environment within the Psychiatry and Behavioral Sciences department.

Genevieve HousmanView profile

Researcher

• Primate Functional Genomics
• Complex Trait Evolution
• Skeletal Development and Maintenance
• +3 more

Genevieve Housman serves as Group Leader of the Skeletal Genomics Lab within the Department of Primate Behavior and Evolution at the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany. She leads research investigating the complex relationship between genotype and phenotype in primate skeletal systems using integrated laboratory and computational approaches. Her primary research interests focus on primate functional genomics , complex trait evolution , and skeletal development and maintenance . Through innovative skeletal cell culture systems using human and nonhuman primate pluripotent stem cells, her lab examines gene regulation across evolutionary scales, developmental timepoints, and environmental perturbations. Key research areas include skeletal gene regulation among primates, gene-by-environment interactions in bone, and evolutionary medicine applications to skeletal systems. Analysis of her recent publications (2022-2025) reveals a strong emphasis on comparative primate genomics, particularly using in vitro cell culture models to study skeletal evolution. Her work spans evolutionary anthropology, bone biology, and functional genomics, with recurring themes of mechanical stress response, osteoarthritis mechanisms, and epigenetic regulation across primate species. The research demonstrates methodological innovation through phylogeny-in-a-dish approaches and cross-species organoid systems. Housman's scientific contributions include developing novel skeletal cell culture methodologies for evolutionary studies and advancing understanding of genotype-phenotype relationships in primate skeletons. Her work bridges evolutionary anthropology with biomedical research, particularly in skeletal disease mechanisms. She actively mentors through her research group and collaborates across institutions, with significant contributions to primate genomics methodology development. Her laboratory maintains primary skeletal tissue collections and cell culture systems for comparative studies across multiple primate species.

Deborah CourtView profile

Professor

• Microbiology
• Molecular Genetics
• Immunology
• +4 more

Deborah Court is a Professor and Department Head of Microbiology at the University of Manitoba, leading the Court Lab focused on fungal mitochondrial proteins. Her research explores mitochondrial membrane proteins, including VDAC (voltage-dependent anion channel) structure-function relationships and antibiotic transport mechanisms. She collaborates extensively with Dr. Sabine Kuss (Chemistry) and Dr. Steven Theriault (Cytophage Research). Education: PhD in Microbiology (University of Guelph), BSc (Hons) in Biochemistry/Biology (University of Regina). Current research projects include mitochondrial inner membrane transporters, VDAC-hexokinase interactions, and bacteriophage-based vaccines. Funded by NSERC, MITACS, and University of Manitoba grants. Teaching focuses on molecular genetics and immunology, earning awards such as the 2020 UManitoba Merit Award and multiple Golden Apple awards (2011-2023). Advises graduate students in MSc/PhD programs and undergraduate researchers, with a focus on proteomics, transcriptomics, and phage engineering. Lab Highlights : Court Lab has pioneered fungal mitochondrial studies over 27 years, producing >50 publications. Key Collaborations : Interdisciplinary work with Chemistry and Virology departments. Student Support : Supervised 15+ students with awards like UMGF, FGS scholarships, and Mitacs grants. Recent projects investigate mitochondrial efflux pumps and antibiotic resistance mechanisms, with applications in combating fungal infections and developing novel antimicrobial strategies.

Chien-Wei LinView profile

Associate Professor

• Statistical Genetics
• Bioinformatics
• Multi-Omics Data Analysis
• +3 more

Dr. Chien-Wei Lin is an Associate Professor in the Department of Biostatistics at the Medical College of Wisconsin. His research focuses on developing statistical methodologies for omics data analysis, including single nucleotide polymorphism (SNP), copy number variation (CNV), DNA methylation, gene expression, proteomics, and metabolomics. He specializes in statistical genetics, bioinformatics, power calculations, integrative analysis, and machine learning applications in biomedical research. Key collaborations include the Department of Pediatrics and Department of Biomedical Engineering. His work addresses challenges in multi-omics data integration, study design frameworks (e.g., FastQDesign for scRNA-seq), and imputation methods for dropout events in single-cell data. Recent publications highlight contributions to chromatin state mapping, meta-analytic gene clustering, and translational studies in diabetes and cardiovascular biology. No explicit scientific awards are listed, though his prolific publication record reflects sustained research impact. He advises collaborative projects with clinical and engineering teams but no listed students. His lab’s work bridges computational statistics and translational biomedical applications, addressing pressing questions in precision medicine and systems biology.

Edward CallawayView profile

Professor

• Neuroscience
• Systems Neurobiology
• Neural Circuits
• +3 more

Edward Callaway, PhD, is a Professor and Principal Investigator in the Systems Neurobiology Laboratory at the Salk Institute for Biological Studies, holding the Vincent J. Coates Chair in Molecular Neurobiology. His research focuses on mapping neural circuits in the brain, particularly the visual cortex and its role in processing visual information. He pioneered viral tracing techniques using modified rabies viruses to study synaptic connections between neurons. Affiliations: Co-Director of the Kavli Institute for Brain and Mind. Education: BS in Biology (Stanford University), PhD in Biology (California Institute of Technology), Postdoctoral Fellow at Rockefeller University. His work uncovers how neural circuits organize to enable perception and cognition, with applications to diseases like schizophrenia and autism. Key innovations include tools for tracing brain-wide connections and studying epigenomic diversity in neurons. Research Interests: Neural circuit mapping, visual processing, viral circuit tracing, epigenomics, and the structural basis of brain function. Recent studies explore cortical circuits, thalamic pathways, and the interplay between cell-type specificity and connectivity. Articles Overview: Recent publications focus on corticothalamic circuits, epigenomic analysis of neurons, and viral tracing techniques. Studies highlight the organization of visual pathways and the role of specific cell types in neural computation. Awards: National Academy of Sciences (2019), Krieg Cortical Discoverer Award (2013), American Academy of Arts and Sciences (2012). Advising & Grants: Supervises a lab of ~12 graduate students and postdocs, including projects on circuit tracing and optogenetics. Collaborates internationally on projects like the BRAIN Initiative. Labs/Teams: The Callaway Lab at Salk employs interdisciplinary approaches, combining viral tools, electrophysiology, and genomics to dissect cortical function.

Casey PaquolaView profile

Researcher

• Neurodevelopment
• Neuroimaging
• Computational Neuroscience
• +3 more

Dr. Casey Paquola leads the Multiscale Neurodevelopment Team at the Institute of Neuroscience and Medicine (INM-7), Research Center Jülich. His research focuses on understanding neurodevelopmental processes through multiscale frameworks that integrate postmortem histology, transcriptomics, and in vivo neuroimaging (e.g., MRI, EEG). The team studies cytoarchitecture maturation, connectivity, and functional dynamics across early life to elucidate mechanisms of neurodevelopmental disorders. Their work emphasizes microstructure as a bridge between postmortem and in vivo data, identifying principles like large-scale cortical gradients. Research methods include microscopy, neuroimaging, and computational modeling to construct brain models. Key areas of study include the default mode network, epilepsy-related brain changes, and the interplay between genetics and brain structure. The team develops tools like BrainSpace and Micapipe for analyzing structural-functional relationships in neuroimaging datasets. Led initiatives: ENIGMA-Toolbox for transdiagnostic analysis, BrainStat for statistical neuroimaging analysis. Focus areas: Cortical development gradients, functional resilience, and translational neuroimaging. Collaborations: Multidisciplinary teams combining computational, clinical, and experimental neuroscience. Future work aims to advance precision medicine through personalized brain mapping and understanding neurodevelopmental disorders' multiscale origins.

Abdullah KahramanView profile

Lecturer

• Bioinformatics
• Cancer omics
• Alternative splicing
• +3 more

Abdullah Kahraman is Group Leader of Data Science in Life Sciences and Lecturer at the Institute for Chemistry and Bioanalytics in the School of Life Sciences at the University of Applied Sciences and Arts Northwestern Switzerland (FHNW). He holds a Diploma in Bioinformatics from University of Applied Science Giessen-Friedberg and a PhD in Computational Biology from the University of Cambridge. His research focuses on computational methods for cancer omics, particularly using long-read sequencing to study alternative splicing in cancer development and therapy resistance. Kahraman develops bioinformatics tools for analyzing isoform switching events in tumors and applies machine learning to identify biomarkers and therapeutic targets. His work bridges computational biology and clinical oncology through collaborations with university hospitals in Zurich and Basel.

Jessica KissingerView profile

Research Professor

• Parasite Genomics
• Bioinformatics
• Evolutionary Genetics
• +3 more

Jessica Kissinger is a Distinguished Research Professor in the Department of Genetics at the University of Georgia's Franklin College of Arts and Sciences. Her research focuses on parasite genomics, bioinformatics, and host-pathogen interactions, with emphasis on apicomplexan pathogens including Toxoplasma , Cryptosporidium , and malaria-causing Plasmodium species. Education: • A.B. cum laude, University of Chicago (1989) • Ph.D. in Molecular, Cellular & Developmental Biology, Indiana University (1995) • Postdoctoral training at NIH/NIAID, FIOCRUZ Brazil, and University of Pennsylvania Research Focus: Dr. Kissinger leads projects in comparative genomics, data integration, and systems biology of eukaryotic pathogens. Her lab develops computational tools for analyzing parasite genome evolution and host-pathogen dynamics, supported by NIH funding including the VEuPathDB resource center. Awards and Honors: University Professor, UGA (2025) Lamar Dodd Creative Research Award (2024) Fellow, AAAS (2021) Fulbright Scholar (2022) Distinguished Research Professor (2017) Current Projects: Her group combines wet-lab and computational approaches to study organellar genome evolution, gene regulation in Cryptosporidium , and multi-omics analysis of host-parasite systems through active NIH grants (R21AI180871, R01AI148667). She advises graduate students and collaborates internationally on parasitic disease research.

Cresten MansfeldtView profile

Assistant Professor

• Environmental Engineering
• Environmental Microbiology
• Bioinformatics
• +7 more

Cresten Mansfeldt is an Assistant Professor in Environmental Engineering at the University of Colorado Boulder, affiliated with the Civil, Environmental, and Architectural Engineering Department. He holds a B.C.E. from the University of Minnesota (2007) and a Ph.D. from Cornell University (2013). Previously, he worked as a Research Scientist at Eawag (Swiss Federal Institute of Aquatic Science and Technology). His research focuses on microbial processes interacting with human-engineered systems, including wastewater treatment, riverine ecosystems, and bioremediation. Key interests include microbial community dynamics, contaminant biotransformation, and reactor design for resource recovery. Mansfeldt’s lab actively recruits students at all levels, emphasizing interdisciplinary approaches combining computational modeling, molecular microbiology, and environmental analytics. Research highlights include developing frameworks for wastewater-based public health surveillance, analyzing wildfire impacts on water quality, and modeling microbial community responses to environmental perturbations. Awards include the 2025 '40 Under 40' recognition from the American Academy of Environmental Engineers and Scientists, and a 2008 NSF Graduate Research Fellowship. Recent work addresses ethical considerations in wastewater sampling and integrates ecological risk assessment with synthetic biology. His publications span topics like microbial enzyme biomarkers, micropollutant fate in activated sludge systems, and lipid-accumulating algae for biofuel production. Current projects aim to optimize wastewater treatment for trace organic contaminant removal while enhancing microbial community resilience.

• Neuroscience
• Developmental Biology
• Molecular Biology
• +4 more

Summer Thyme is an Assistant Professor at UMass Chan Medical School, primarily affiliated with the T.H. Chan School of Medicine's Department of Biochemistry and Molecular Biotechnology. She also holds roles in multiple departments including Neurobiology, NeuroNexus Institute, and the Morningside Graduate School of Biomedical Sciences. Her research focuses on neurodevelopmental disorders using zebrafish models, CRISPR genome engineering, and schizophrenia-associated genes. She holds a BA in Biology/Chemistry from Scripps College and a PhD in Biochemistry from the University of Washington. Her research interests span neurodevelopmental mechanisms, genetic mutations affecting brain structure, and translational applications of CRISPR technology. Key areas include studying autism-risk mutations, mitochondrial regulation in neural stem cells, and cerebellar development. She has contributed to platforms like ZebraShare for data dissemination and developed low-cost behavioral phenotyping systems for zebrafish. Recent publications highlight studies on diencephalon development, sensory system impairments in zebrafish mutants, and CRISPR-based genome editing tools. Collaborations involve interdisciplinary teams addressing neurodevelopmental and genetic questions. Her work has implications for understanding psychiatric and neurological disorders through model organism research.

Yawei LiView profile

Lecturer

• Artificial Intelligence
• Computer Vision
• Deep Learning
• +6 more

Yawei Li is a Lecturer at ETH Zürich, affiliated with the Integrated Systems Institute. His research focuses on efficient deep learning and AI systems for vision, language, and biosignals. Collaborating with Professors Luca Benini and Luc Van Gool, he explores topics like foundation models for biosignals, efficient neural network design, and deployment on RISC-V cores. He has organized workshops such as the NTIRE Challenge on Efficient Super-Resolution and served as a Senior Program Committee member for AAAI and IJCAI. He has supervised numerous PhD and Master students, with open positions available in foundational model development and bio-signal analysis. Key achievements include the Best Poster Presentation at ICVSS 2019 and contributions to projects like TinyYOLO for smart glasses. His work emphasizes practical applications of AI on embedded systems and low-power devices. Teaching includes courses like 'Deep Learning for Image Manipulation' and involvement in Computer Vision Lab initiatives. His research spans image restoration, neural network compression, and cross-modal analysis, with publications in top venues like CVPR, NeurIPS, and ECCV.

Martin AnderssonView profile

Professor

• Solid Oxide Fuel Cells
• Polymer Electrolyte Membrane Fuel Cells
• Heat and Mass Transfer
• +4 more

Martin Andersson is a Professor at Lund University's Department of Energy Sciences, affiliated with the LTH Profile Area: The Energy Transition and AdTherM: Advanced Computing for Sustainable Thermal Management in Industry. His research focuses on heat and mass transfer in fuel cells, including solid oxide (SOFCs) and polymer electrolyte membrane (PEMFCs) systems. He leads initiatives such as the Energy@LTH project and contributes to international collaborations like the IEA Advanced Fuel Cell Annexes. Andersson holds the titles of Director of First and Second Cycle Studies and Assistant Director, emphasizing educational leadership alongside research. His work aligns with UN Sustainable Development Goals, particularly energy systems and environmental sustainability. He has received awards including the Marie Curie Fellowship and VINNMER fellowship, and actively organizes seminars and conferences on energy transition topics. Research interests include modeling of transport phenomena in fuel cell components, nano/micro-structured materials' effects on energy efficiency, and sustainable thermal management strategies. His projects span numerical methods development, catalyst optimization for hydrogen production, and interdisciplinary approaches to electrochemical systems. Andersson has supervised seven research works and collaborates globally on topics like hydrogen business models and solar energy applications. Scientific contributions include over 150 peer-reviewed publications, with recent highlights on multiphysics modeling of porous media, hydrogen catalysts, and solar dryer systems. His work bridges computational analysis and experimental validation, addressing both fundamental and applied challenges in energy engineering.

• Bioinformatics
• Machine Learning
• Genomics
• +3 more

Dr. Alfredo Iacoangeli is a Reader in Bioinformatics at King’s College London, leading a joint research programme between the Department of Basic & Clinical Neuroscience and the Department of Biostatistics & Health Informatics at the Institute of Psychiatry, Psychology & Neuroscience. His work focuses on computational approaches for neurodegenerative diseases, particularly amyotrophic lateral sclerosis (ALS) and Alzheimer’s disease. He earned his PhD in Life Sciences from Sapienza University of Rome in 2016, specializing in structural bioinformatics. Key roles: Deputy Lead of the Motor Neuron Disease research theme at the NIHR Maudsley Biomedical Research Centre. Expertise: Bioinformatics, machine learning, genomics, and translational research. His research interests include developing computational tools for genomic analysis (e.g., RetroSnake, GEOexplorer), identifying genetic subtypes of ALS, and advancing precision medicine strategies. He has received awards such as the 2024 Paolo Gontijo Award and the 2022 Genes Young Investigator Award. Notable grants include £983k from the Medical Research Council for studying ancient viral DNA in ALS. He collaborates internationally, contributing to initiatives like Project MinE and the ALS Sequencing Consortium. His work bridges computational biology and clinical neurology, emphasizing multi-omics data integration for disease stratification and drug discovery.