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Chase BroederszView profile

Associate Professor

• Cell Migration
• Chromosome Organization
• Biopolymer Mechanics
• +3 more

Chase Broedersz is an Associate Professor at Vrije Universiteit Amsterdam, affiliated with the Faculty of Science's Physics of Living Systems department and the LaserLaB - Energy research group. He leads interdisciplinary research on cell migration, chromosome mechanics, and active matter, combining experimental and theoretical approaches. His work contributes to UN Sustainable Development Goals related to health and innovation. Research Interests: Focus on cell migration dynamics , chromosome organization , biopolymer mechanics , and nonlinear elasticity . Recent studies explore bacterial chromosome topology, metastasis prevention mechanisms, and 3D nuclear deformation during cell movement. His methods include Hi-C data analysis, single-molecule tweezers, and computational modeling. Publications Trends: Recent work emphasizes chromosome condensation mechanics , active matter dynamics , and nonlinear elasticity in biopolymers . Key 2024-2025 studies include ion-mediated mitotic chromosome mechanics and metastasis suppression by miR-200c. Awards: None explicitly listed. Grants/Advising: Supervised one PhD thesis and contributes to datasets like biopolymer matrix nonlinear elasticity studies. Labs/Teams: Active in LaserLaB and collaborates internationally on cell migration and chromosome physics.

Kechen ZhangView profile

Associate Professor

• Theoretical Neuroscience
• Computational Neuroscience
• Neural Computation
• +3 more

Kechen Zhang is an Associate Professor of Biomedical Engineering and Neuroscience at Johns Hopkins University School of Medicine. He holds affiliations with the Center for Hearing and Balance and the Kavli Neuroscience Discovery Institute. His research focuses on theoretical and computational neuroscience, particularly neural computation and spatial navigation models. Zhang earned a B.S. and M.S. from Peking University, a Ph.D. in Cognitive Science from UC San Diego, and completed a postdoc at the Salk Institute. Research Interests Zhang’s lab studies nervous system dynamics using mathematical and computational models, collaborating with experimental labs. Key areas include grid cells, place cells, path integration, oscillatory interference models, and neural coding mechanisms. His work bridges biophysical models and network-level computations. Publications Over 30 peer-reviewed articles in Neural Computation , PNAS , Journal of Neuroscience , and others, addressing topics like attractor networks, theta rhythms, and spatial representation. Recent work explores cognitive swarming and neuro-inspired robotics. Collaborations & Teaching Collaborates with Jim Knierim, Xiaoqin Wang, and others. Teaches Biomedical Systems II , Theoretical Neuroscience , and co-leads the Johns Hopkins Systems Neuroscience Journal Club.

Mihaela PerteaView profile

Associate Professor

• Computational Genomics
• Gene Annotation
• Transcriptome Assembly
• +3 more

Mihaela Pertea, PhD, is an Associate Professor in the Department of Biomedical Engineering at Johns Hopkins University, with affiliations in Genetic Medicine and the Computer Science department. She leads the Pertea Lab, focusing on computational methods for analyzing genomic and transcriptomic data to understand cellular function, particularly in gene finding, alternative splicing, and RNA-seq analysis. Her work integrates machine learning and statistical techniques to improve gene annotation and maintain genomic catalogues. Education: PhD in Computer Science (Johns Hopkins University, 2001); multiple degrees from University of Bucharest (BS in Psychology, BS and MS in Computer Science). Affiliations: Center for Computational Biology at Johns Hopkins. Research interests include developing algorithms for transcriptome assembly, splice site prediction (e.g., Splam tool), and tools like StringTie for RNA-seq analysis. Her lab’s work has contributed to genome projects of malaria parasites, nematodes, and other pathogens. Recent achievements include an AIMBE College of Fellows recognition (2025) and innovations in AI-driven gene splicing analysis. Publications span over 70 peer-reviewed articles, emphasizing computational biology tools and genomic studies. Notable collaborations include work on the ENCODE project and genome sequencing of Plasmodium falciparum. Her lab’s tools (e.g., CHESS, GFF Utilities) are widely used in genomic research.

• Reproductive Medicine
• Medical Biotechnology
• Molecular Biology
• +3 more

Andres Salumets is a Professor of Reproductive Medicine at the Department of Clinical Science, Intervention and Technology, Karolinska Institutet. His research focuses on molecular mechanisms underlying reproductive health, including endometrial biology, assisted reproduction technologies, and environmental influences on fertility. He leads studies on uterine fluid extracellular vesicles, genomic analysis of reproductive disorders, and the impact of endocrine disruptors on reproductive tissues. Salumets collaborates with multidisciplinary teams to translate findings into clinical applications, such as improving non-invasive prenatal testing (NIPT) and developing probiotics for male reproductive health. His work integrates cutting-edge technologies like AI-driven histology analysis, single-cell RNA sequencing, and genome-wide association studies (GWAS). Key research areas include polycystic ovary syndrome (PCOS), endometriosis, and recurrent implantation failure (RIF). Recent studies explore phthalate effects on endometrial cells and novel therapies for breast cancer using natural extracts. Salumets' research bridges basic science with clinical practice, aiming to enhance assisted reproduction outcomes and address global infertility challenges.

Deyou ZhengView profile

Professor

• Computational Genomics
• Bioinformatics
• Gene Regulatory Networks
• +3 more

Dr. Deyou Zheng is Professor in the Saul R. Korey Department of Neurology, Department of Genetics, and Dominick P. Purpura Department of Neuroscience at Albert Einstein College of Medicine. His research specializes in computational genomics and bioinformatics, analyzing high-throughput genomic data to understand genome structure, transcription regulation, and evolutionary dynamics during development and disease. Core research areas include: (1) Neural system development and neuropsychiatric disorders using iPSC-derived neurons and single-cell transcriptomics; (2) Genetic bases of congenital heart diseases; (3) Cancer genomics focusing on tumor microenvironment and immunotherapy resistance. Collaborative projects employ iPSC technology, RNA-seq, and CRISPR-Cas9 to model disorders like autism and schizophrenia. Recent publications emphasize: Single-cell integration algorithms for transcriptomic data Cancer-associated fibroblasts in glioblastoma/osteosarcoma CHD8 mutations in neurodevelopmental disorders Allele-specific expression in human brain cells

Anne DekasView profile

Assistant Professor

• Geomicrobiology
• Biogeochemistry
• Deep-Sea Microbiology
• +3 more

Anne Dekas is an Assistant Professor in the Department of Earth System Science at Stanford University, affiliated with the Stanford Doerr School of Sustainability. She holds a courtesy appointment in Earth and Planetary Sciences. Her research focuses on geomicrobiology, exploring how microbial life influences Earth's chemistry and climate, particularly in deep-sea environments. She earned a PhD in Geobiology from Caltech (2013) and an AB in Earth and Planetary Sciences from Harvard (2004). Her lab, the Dekas Geomicrobiology Laboratory, investigates microbial diversity and activity in the deep ocean, including carbon, nitrogen, and sulfur cycling. Key research topics include greenhouse gas dynamics, subsurface microbiomes, and microbial adaptations to extreme environments. She has pioneered techniques combining molecular biology and isotope geochemistry to study microbial function in habitats like hydrothermal vents, hypersaline brines, and methane seeps. Her work bridges Earth science and astrobiology, examining analogs for extraterrestrial ocean worlds. Notable findings include insights into ANME archaea scarcity in seeps and the role of urea in dark ocean nitrogen assimilation. She also explores soil carbon storage via anoxic microsites and the metabolic flexibility of SAR324 lineages. Lab facilities are located in the Green Earth Sciences Building at Stanford. Her research has been supported by grants including the NSF CAREER award (2022) and NASA astrobiology initiatives. The lab actively collaborates on oceanographic expeditions and environmental management projects.

• Genomics
• Epigenetics
• Bioinformatics
• +3 more

Dr. Gary Hon is an Assistant Professor at UT Southwestern Medical Center affiliated with the Cecil H. and Ida Green Center for Reproductive Biology Sciences and the Lyda Hill Department of Bioinformatics. He leads a research program focused on decoding the complexity of the human genome through two primary directions: understanding the molecular basis of cell state for regenerative medicine applications, and elucidating how non-coding variants contribute to development and disease. His lab employs integrative techniques at the interface of gene regulation, epigenetics, genome engineering, single-cell genomics, and bioinformatics. His research interests span genomics, epigenetics, bioinformatics, gene regulation, stem cell biology, and disease mechanisms. Dr. Hon earned his graduate degree from UC San Diego's Bioinformatics and Systems Biology Program and completed post-doctoral training in Dr. Bing Ren's lab before joining UT Southwestern in 2015. Dr. Hon has received significant recognition including the CPRIT Scholar award and NIH Director’s New Innovator Award. His recent publications demonstrate a focus on advanced genomic techniques including Perturb-Seq optimization, single-cell transcriptomics in cancer and reproductive biology, enhancer network mapping, and stem cell modeling of human development.

• Alzheimer's Disease
• Neurodegeneration
• Molecular Genetics
• +3 more

Mikko Hiltunen is a Professor of Tissue and Cell Biology at the Institute of Biomedicine, School of Medicine, University of Eastern Finland. His research focuses on molecular mechanisms of neurodegenerative disorders, particularly Alzheimer's disease and idiopathic normal pressure hydrocephalus (iNPH). He leads several research groups including the Molecular Genetics of Alzheimer's Disease (Hiltunen Lab) and participates in the Brain Research Unit and Genome Center of Eastern Finland. Research interests span Alzheimer's pathogenesis, neuroinflammation, genetic risk factors, biomarker discovery, and therapeutic development. His work integrates molecular biology, genetics, and clinical neuroscience to investigate microglial function, amyloid pathology, and cerebrospinal fluid biomarkers. Key areas include APOE genetics, PLCγ2-mediated neuroprotection, and machine learning applications in neurodegeneration. His recent publications demonstrate a strong focus on cerebrospinal fluid biomarkers, genetic association studies, neuroinflammation mechanisms, and therapeutic interventions. Article themes consistently emphasize microglial biology, genetic risk modifiers, and translational approaches for Alzheimer's and iNPH. Collaborative projects include Neuro-Innovation (2021-2026) and NOVEL MSCA Postdoctoral Programme (2024-2029). Hiltunen leads the Clinical Alzheimer Research group and co-directs the UEF Brain Research Unit. His team utilizes advanced models including iPSC-derived microglia and pericyte systems to study neurovascular interactions. Current work explores phospho-tau immunotherapy, lysosomal dysfunction, and polygenic risk score applications across diverse populations.

Vassilis P. PlagianakosView profile

Associate Professor

• Machine Learning
• Neural Networks
• Bioinformatics
• +5 more

Vassilis P. Plagianakos is an Associate Professor at the Department of Computer Science and Biomedical Informatics, University of Thessaly, Greece. He has held visiting academic roles at the University of the Aegean, University of Patras, and University of Central Greece. He currently serves as the Department Head and Director of the postgraduate program Informatics and Computational Biomedicine in the School of Sciences. His research focuses on machine learning, neural networks, bioinformatics, and parallel computing with applications in healthcare and education. Education : Bachelor’s in Mathematics (1996), University of Patras Ph.D. in Mathematics (2003), University of Patras Research Interests : Plagianakos explores neural networks, evolutionary algorithms, and machine learning applications in bioinformatics, medical diagnosis, and educational technology. His work bridges computational methods with real-world challenges in healthcare (e.g., precision medicine) and STEM education (e.g., flipped classrooms, AI integration). Recent Trends in Publications : Recent work emphasizes predictive precision medicine using big data, blockchain scalability solutions, and AI ethics in automated content detection. He has pioneered methods like the HCER hierarchical clustering-ensemble regressor and developed tools for analyzing single-cell RNA sequencing data. Professional Activities : Member of IEEE Neural Networks Society, IEEE BBTC, and former Board Member of the Hellenic AI Society. Active in collaborative projects like CrowdHEALTH for policy-driven health data analytics.

Claudio Contreras AburtoView profile

Professor

• Statistical Physics
• Condensed Matter Physics
• Biological Physics
• +3 more

Dr. Claudio Contreras Aburto is a Full-Time Professor at the Faculty of Physics of the Universidad Veracruzana since September 2020, holding a Tenured Career C position. Previously, he served as a Full-Time Professor B at the Autonomous University of Chiapas (2016–2020) and completed postdoctoral research at institutions including the University of Sonora and Guanajuato. He earned his PhD in Physics from Cinvestav (2008) and holds a Master’s (2004) and Bachelor’s (2002) from the same institution. Education : Bachelor of Science in Physics, University of Veracruz (2002) Master of Science in Physics, Cinvestav (2004) PhD in Science (Physics), Cinvestav (2008) Agricultural Informatics Technician, CBTA 86 (1998) Research Focus : His work centers on charged particle dispersions, including hydrodynamic interactions, conductive-diffusive transport, and crystallization kinetics. Tools include statistical physics, molecular simulation, and field theory. Recent studies involve electrolyte solutions and colloidal systems. Publications : Over 12 peer-reviewed articles focus on charged fluids, diffusion mechanisms, and molecular dynamics simulations. Key themes include electrokinetic properties, mode-coupling theories, and biological membrane interactions. Academic Service : Coordinates the Applied Physics Academy and Graduate Monitoring at FF-UV. Supervised 3 undergraduate and 3 master’s theses. Actively participates in national/international conferences and seminar presentations. Labs/Teams : Engaged in collaborative research through the FF-UV’s physics department, focusing on interdisciplinary projects at the physics-biology interface.

Joseph IbrahimView profile

Professor

• Biostatistics
• Bayesian Survival Analysis
• Prior Elicitation
• +6 more

Joseph Ibrahim is an Alumni Distinguished Professor in the Department of Biostatistics at the Gillings School of Global Public Health, University of North Carolina at Chapel Hill, where he has served since 2002. He currently holds dual leadership roles as Director of Graduate Studies for the Department of Biostatistics and Director of the Biostatistics for Research in Genomics and Training Grant. His methodological innovations in Bayesian survival analysis and missing data methodologies have significantly advanced public health research, particularly in cancer genomics applications. Professor Ibrahim's research program centers on developing statistical frameworks for complex clinical and genomic data. His seminal contributions include Bayesian cure rate models, prior elicitation techniques, and diagnostic tools for high-dimensional survival analysis. Current work focuses on integrating multi-omics data with longitudinal tumor burden metrics and refining adaptive clinical trial designs for biomarker-driven populations. These methodologies directly address critical challenges in precision oncology and pharmacovigilance, enabling more robust inference from real-world evidence. His 2025 publications reveal three dominant trends: (1) Advancements in cure rate modeling for joint longitudinal-survival data with change points, (2) Computational innovations for high-dimensional penalized models using autoencoders and R packages like hdbayes, and (3) Methodological refinements for Bayesian trial design incorporating historical controls. These works consistently bridge theoretical statistics with cancer research applications, particularly in tumor phylogeny inference and signal detection for adverse events. Scientific awards include: Samuel S. Wilks Memorial Award (2024) from the American Statistical Association for distinguished contributions to biostatistics Professor Ibrahim has mentored 48 pre-doctoral students and 8 postdoctoral fellows, with exceptional thesis publication records in top statistical journals. As principal investigator of the T32 Cancer Genomics Training Grant since 2004, he has secured funding for 35 doctoral students. His curriculum leadership includes modernizing eight graduate courses and establishing new data science computing sequences since 2015. Current advising focuses on Bayesian methodology development for cancer genomics applications. He directs the department's Biostatistics for Research in Genomics initiative and leads the T32 Cancer Genomics Training Grant team, which integrates statistical methodology development with translational cancer research across UNC's Lineberger Comprehensive Cancer Center and clinical partners.

• Pancreatic Cancer
• Gastrointestinal Cancer
• Surgical Oncology
• +5 more

Dr. Andrew M. Lowy is a Professor of Surgery at the University of California San Diego School of Medicine, specializing in surgical oncology with a primary focus on pancreatic, liver, and gastrointestinal cancers. As a leading expert in pancreatic cancer treatment, he has pioneered the use of heated intraperitoneal chemotherapy (HIPEC) or 'chemo bath' for advanced abdominal cancers. Dr. Lowy serves on editorial boards of the Journal of Clinical Oncology and Annals of Surgical Oncology, and co-chairs the National Cancer Institute's Pancreatic Cancer Task Force. His research centers on pancreatic carcinogenesis and therapy, with particular emphasis on the RON receptor tyrosine kinase and its role as a potential therapeutic target. His laboratory develops models for testing novel therapeutics, focusing on translational applications for pancreatic cancer treatment. His work spans molecular biology, cancer signaling pathways, and innovative therapeutic approaches including targeted therapies and immunotherapies. Analysis of Dr. Lowy's recent publications reveals a strong emphasis on molecular mechanisms driving pancreatic cancer progression, with particular focus on tumor microenvironment interactions, metastasis mechanisms, and therapeutic resistance. His work increasingly incorporates advanced genomic and transcriptomic approaches while maintaining strong clinical relevance through participation in major cooperative group trials like SWOG. Dr. Lowy has secured significant research funding as Principal Investigator on multiple NIH grants, including several R01 awards from the National Cancer Institute, demonstrating the importance and impact of his research program. His extensive involvement in clinical trials reflects his commitment to translating laboratory findings into improved patient care. His laboratory and clinical team focus on advancing pancreatic cancer treatment through innovative surgical approaches, novel therapeutic targets, and biomarker development to guide personalized treatment strategies. The integration of basic science with clinical practice characterizes his comprehensive approach to improving outcomes for patients with gastrointestinal malignancies.

• Cancer Immunotherapy
• Gene Editing
• Immune Cell Engineering
• +3 more

Yueqi Zhang is a Molecular Research Assistant in the Department of Neuroscience at Yale University, affiliated with the Yale School of Medicine. Their research focuses on advancing therapeutic immune cell engineering, gene editing technologies, and cancer immunotherapy. Zhang holds an MD from Yale University (expected 2026) and a bachelor's degree from Central South University (2019). Key research areas include CRISPR-based genome editing systems (e.g., Cas12a and Cas13d), AAV-mediated delivery of genetic payloads, and metabolic modulation of CAR-T and CAR-NK cells. They have pioneered composite systems combining mRNA and viral vectors for immune cell engineering and developed in vivo CRISPR screens to identify therapeutic targets in tumor-infiltrating immune cells. Zhang's recent work (2023–2025) emphasizes multiplexed gene inhibition strategies, combinatorial immunotherapies, and translational platforms for clinical application. Their studies bridge molecular biology, systems immunology, and clinical oncology to address challenges in targeted therapy resistance and immune evasion mechanisms. Education: MD Candidate, Yale University School of Medicine (2026) Bachelor's Degree, Central South University (2019) Labs/Teams: Active in Yale's Molecular and Cellular Neuroscience programs and collaborates with teams developing AAV-based gene therapies and CRISPR engineering platforms.

• Membrane Biology
• Protein Folding
• Biophysics
• +6 more

Yongli Zhang is a Professor of Cell Biology and holds a secondary appointment as an Associate Professor in Molecular Biophysics and Biochemistry at Yale University. His research focuses on molecular mechanisms of membrane fusion, protein folding dynamics, and the development of single-molecule biophysical tools. He earned a bachelor’s degree in applied physics from China, a master’s in theoretical physics from the Chinese Academy of Sciences, and a PhD in Molecular Biophysics and Biochemistry from Yale University. His postdoctoral training at UC Berkeley under Prof. Carlos Bustamante expanded his expertise in optical tweezers and molecular biophysics. Key areas of research include regulated SNARE protein assembly, membrane protein interactions, and instrumentation development. The Zhang Lab uses advanced optical tweezers and fluorescence microscopy to study molecular forces in biological processes like exocytosis and endocytosis. Recent work explores SNARE-mediated membrane fusion mechanisms and the role of mechanical forces in protein function. Awards include the Jane Coffin Childs Postdoctoral Fellowship and the Sinsheimer Scholar award. The lab is actively involved in training students and postdocs in biophysical techniques and interdisciplinary research. Collaborations span structural biology, neuroscience, and computational modeling to address fundamental questions in membrane biology and protein dynamics.

Min ChenView profile

Professor

• Statistical Genomics
• Bioinformatics
• Bayesian Methods
• +5 more

Dr. Min Chen is a Professor in the Department of Mathematical Sciences at the University of Texas at Dallas (UTD), affiliated with the School of Natural Sciences and Mathematics. He holds an adjunct professorship at the University of Texas Southwestern Medical Center. His expertise spans statistical genomics, bioinformatics, Bayesian methods, and sampling techniques. He completed his Ph.D. in Statistics and Decision Science at the University of Texas at Austin and a postdoctoral fellowship in statistical genomics at Yale University. Education: B.S. in Computer Science (University of Science & Technology of China, 1994); M.A. in Statistics (University of Pittsburgh, 1999); Ph.D. in Statistics (UT Austin, 2006); Postdoc in Statistical Genomics (Yale University, 2008–2010). Research focuses on statistical methodologies in genomics, including genome-wide association studies, network-based modeling, and Bayesian integrative analysis. He also explores spatial modeling and ranked set sampling. His work addresses challenges in cancer genetics, epigenetics, and single-cell gene regulation. Notable awards include the NIH Career Development Award (2013), David Bruton Fellowship (2006), and R.L. Anderson Student Paper Award (2006). He is a member of the American Statistical Association and International Chinese Statistical Association. He advises graduate students in Data Science, Statistics, and Bioinformatics & Computational Biology (BCBM) programs. His teaching includes courses on advanced statistical methods and data science. Research contributions span over 40 peer-reviewed articles, with recent work in tumor pathology imaging, antibiotic resistance, and Alzheimer’s disease mechanisms.