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Karin DormanView profile

Professor

• Bioinformatics
• Computational Biology
• Genetics
• +3 more

Karin Dorman is a Professor in the Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology at Iowa State University, where she conducts interdisciplinary research at the intersection of computational methods and biological systems. Her work bridges bioinformatics algorithm development with investigations into immune signaling pathways and stem cell biology. Her educational background includes: PhD in 2001 from the University of California, Los Angeles B.S. in 1994 from Indiana University, Bloomington Dr. Dorman's research focuses on bioinformatics, computational biology, and molecular genetics, with significant contributions to genomic analysis methods and immunological mechanisms. She develops computational tools like MULTICLUST for population genetics and CAPG for polyploid genotyping, while investigating NOD1-dependent NF-kB signaling in hematopoietic stem cell specification. Her work on antimicrobial resistance prediction models bridges veterinary and human health through One Health frameworks. Analysis of her 2022-2025 publications reveals dual methodological and biological emphases: (1) innovative bioinformatics tools for genotyping, epigenomics, and microbiome analysis; (2) mechanistic insights into inflammatory signaling dynamics in stem cell development. This integration of computational and experimental approaches characterizes her interdisciplinary research program. No scientific awards are documented in the provided information. While specific advisees aren't listed in available materials, Dr. Dorman contributes to graduate education through Iowa State's Bioinformatics and Computational Biology Program. Her collaborative work with researchers like Ambuj Kumar and Robert Jernigan demonstrates active engagement in interdisciplinary teams focused on protein interactions and genomic analysis.

Thomas LeonardView profile

Professor

• Lipid signaling
• Protein kinases
• Signal transduction
• +5 more

Thomas Leonard is a tenured Professor at the Max Perutz Labs (University of Vienna), where he leads a research group focused on lipid-mediated signal transduction and structural mechanisms of kinase regulation . His lab combines structural biology , biochemistry , and cell biology to dissect how cells integrate spatial and temporal signals. PhD in Structural Biology (MRC Laboratory of Molecular Biology, Cambridge) Postdoctoral work at NIH, Bethesda His research explores how lipid second messengers like PIP3 and PI3P control kinases such as Akt, PDK1, and Sgk3, with implications for cancer , neurodevelopmental disorders , and metabolic diseases . Recent work redefined PHLPP1/2 as pseudophosphatases and revealed novel activation mechanisms in Protein Kinase D (PKD) and DMPK kinases. The lab's publication trends highlight structural phylogenomics , membrane scaffolding , and allosteric regulation . Collaborations with institutions like LMU Munich and FWF-funded projects underscore their interdisciplinary approach. Lab Manager: Ronja Reinhardt PhD Students: Sumire Antonioli, Magdalena Otto, Lucas Piech, Eva Krotenheerdt, Felix Wolkenstein Master Students: Gabriela Ariza, Emese Galgóczi, Stefan Lenz The lab actively recruits at Master, PhD, and Postdoc levels for molecular signaling research.

Alessandro SanzeniView profile

Assistant Professor

• Neuroscience
• Mathematical Modeling
• Statistical Physics
• +6 more

Alessandro Sanzeni is an Assistant Professor at Bocconi University's Department of Computing Sciences since September 2022. Prior to this, he conducted research at Columbia University, Duke University, and the National Institutes of Health, with visiting appointments at the University of Chicago, University of California San Diego, and the Pasteur Institute in Paris. He holds a background in theoretical physics from the University of Milan, Italy. His research integrates theoretical frameworks (mathematical modeling, statistical physics, machine learning) with experimental neuroscience to study the visual system's computational principles, focusing on: Functional Models: Visual hierarchy transformations and abstraction mechanisms. Mechanistic Models: Neural dynamics across scales (dendritic, circuit, and multi-area interactions). Normative Models: Evolutionary advantages of brain network architectures over artificial models. Publications highlight his work on cortical networks, optogenetic stimulation, and mechanotransduction in sensory processing.

Mario JolicoeurView profile

Professor

• Biochemical Engineering
• Biomedical Engineering
• Metabolic Engineering
• +3 more

Mario Jolicoeur is a Full Professor in the Department of Chemical Engineering at Polytechnique Montréal. His research focuses on metabolic engineering, biomedical applications, and bioreactor design. He is affiliated with Spheroid AI Inc. (Co-founder, Scientific Director), Viridios (Collaborating Researcher), and the Institute of Biomedical Engineering (Member). Education: B.Sc.A., M.Sc.A., Ph.D. (Polytechnique Montréal and Paul-Sabatier University, Toulouse), Visiting Engineer (MIT) Jolicoeur develops metabolic engineering tools for cancer therapies and therapeutic agent production, designs mathematical models for cellular metabolism regulation, and creates aseptic culture equipment for diverse cells. His work spans CHO cells , microalgae , and tissue engineering . Recent publications highlight metabolic therapies for ovarian cancer, dynamic modeling of CHO cultures, and lipid production in Chlorella. Trends include cancer metabolism, mitochondrial dynamics, and bioreactor optimization. Supervision: He has mentored 43 graduate students since 1990, including those working on metabolic models, bioreactors, and biotherapies. Notable projects involve methylene blue in cancer treatment, ABE fermentation, and chondrocyte culture systems. Labs & Teams: Collaborates with interdisciplinary groups in biomedical engineering and chemical engineering, utilizing advanced bioreactor platforms and computational models.

• Mechatronics
• Signal Processing
• Control Systems
• +7 more

Jonas Sjöberg is a Full Professor of Mechatronics at Chalmers University of Technology, where he leads the Mechatronic research group in the College of Engineering. His research spans multiple aspects of mechatronic systems with a strong focus on automotive applications. Sjöberg holds leadership roles in numerous research projects related to autonomous vehicles, vehicle control systems, and transportation safety. His research interests encompass a broad spectrum of mechatronics applications, with particular emphasis on model-based methods, signal processing, control systems, system identification, and optimization for design and product development of mechatronic systems. Sjöberg's work bridges theoretical control engineering with practical automotive applications, especially in the domains of Automotive Active Safety and Hybrid Electric Vehicles. Analysis of Sjöberg's recent publications reveals a strong research trajectory focused on autonomous vehicle technologies, with particular attention to vehicle dynamics control, intersection safety, road surface condition estimation, and optimization of vehicle maneuvers. His work demonstrates a consistent approach of applying advanced control theory to solve real-world transportation challenges, with increasing emphasis on machine learning techniques integrated with traditional control systems. Sjöberg actively supervises research and education at both undergraduate and graduate levels while leading multiple research projects funded by VINNOVA, the European Commission, and other organizations. His research group collaborates extensively with both academic institutions and industry partners in the automotive sector. His laboratory work focuses on mechatronic systems development, particularly for automotive applications including autonomous bicycles, bus docking systems, and vehicle control algorithms. The research group maintains strong connections with the automotive industry, particularly in Sweden's robust vehicle technology ecosystem.

• Cutaneous Biology
• Wound Healing
• Aging
• +7 more

Julie Thornton is a Senior Lecturer in Biomedical Sciences at the School of Chemistry & Biosciences, University of Bradford. She is the Academic Director of the Centre for Skin Sciences and Academic Lead for the Plastic Surgery and Burns Research Unit (PSBRU), focusing on skin and hair biology, wound healing, and aging. Her research emphasizes epigenetic processes and 3D co-culture models. Education: Not explicitly detailed in the text. Her research spans cellular and molecular studies of skin and hair biology, particularly in post-menopausal women. She investigates wound healing, aging, epigenetic changes, and gene regulatory networks using primary human cells and 3D cultures. Her work also explores collaborations with industry partners like Aveda/Estee Lauder, Nutraceutical Wellness LLC, and Follicum AB. Recent publications highlight blue light therapy in wound healing, estrogen's role in skin aging, intracrine steroid synthesis, and hormonal effects on hair follicles. Scientific trends include hormone receptors (ERβ, AR), oxidative stress, and bioimaging for model validation. Students: Lucy Trevor (radiotherapy tissue), Rachael Sutherland-Sedman (hair follicle aging), Paul Norton (antimicrobial resistance), Aqib Ahmed (TET enzymes), Aaiad Al Rikabi (fibroblast inflammation). Industry collaborations span KTP Innovate UK with Labskin, Aveda/Estee Lauder (hair aging), Nutraceutical (hair thinning), and Follicum AB (hair loss and diabetes).

• Veterinary Anatomy
• Comparative Pharmacology
• Neuroendocrinology
• +2 more

Prof. dr Milena Đorđević is an Associate Professor at the Department of Anatomy, Faculty of Veterinary Medicine, University of Belgrade. Her work focuses on veterinary anatomy, pharmacokinetics, and pathological studies in animals. Veterinary Anatomy Comparative Pharmacology Animal Physiology Diagnostic Imaging Techniques Her research spans anatomical variations in wildlife species, pharmacokinetic differences between animal species, and clinical diagnostics of canine/feline diseases. She has published extensively in veterinary journals like Acta Veterinaria and Veterinarski Glasnik , covering topics from rodent vascular systems to feline liver pathologies. Key collaborations include studies with researchers such as Vanja Krstić, Nikola Krstić, and Miloš Blagojević. Her work integrates histopathological , imaging , and clinical analysis for veterinary diagnostics and wildlife anatomical research.

Anna CaiView profile

Lecturer

• Mathematical Biology
• Biomathematics
• Mathematical Modeling
• +3 more

Dr. Anna Cai is a Lecturer in the Department of Applied Mathematics within the School of Mathematics & Statistics at the University of New South Wales (UNSW), a position she has held since 2011. Prior to this, she served as a postdoctoral researcher and lecturer at the University of California, Irvine from 2007 to 2011. Her educational background: Ph.D., The University of Melbourne, 2008 B.Sc. (First Class Honours), The University of Melbourne, 2004 Dr. Cai's research centers on Mathematical Biology , with specialization in cell migration dynamics , developmental pattern formation , and robustness in biological systems . She employs multi-scale mathematical modeling and stochastic analysis to investigate phenomena ranging from wound healing to zebrafish hindbrain development. Her work bridges theoretical mathematics with experimental biology to decode fundamental mechanisms governing cellular behavior and morphogenesis. Analysis of her 11 publications (2006-2015) reveals an evolutionary trajectory from foundational work on cell migration mechanics to sophisticated studies of developmental robustness. Early research established mathematical frameworks for wound-healing assays and immune cell dynamics, while later work pioneered noise-driven pattern formation models in zebrafish. A unifying thread is her focus on how biological systems maintain precision despite environmental fluctuations. Administrative responsibilities include: Applied representative on the postgraduate review committee UNSW study abroad and exchange course authority Current teaching assignments: MATH2121: Theory and Applications of Differential Equations MATH2018: Engineering Mathematics 2D Prior courses taught: MATH3041: Mathematical Modeling for Real World Systems MATH6781: Biomathematics

Ville PaavilainenView profile

Researcher

• Biochemistry
• Cell Biology
• Molecular Biology
• +9 more

Ville Paavilainen is a Research Director at the Institute of Biotechnology, University of Helsinki, and supervisor for doctoral programs in Biomedicine and Integrative Life Science. With a postdoctoral background at the University of California, San Francisco (2008–2014), he focuses on Biochemistry , Cell Biology , and Molecular Biology , particularly mechanisms of protein translocation, membrane biology, and structural modeling. His research includes groundbreaking work on Sec61 translocon inhibition for cancer therapy and mitochondrial gene expression noise . Recent publications address lipid scrambling pathways, glioma stem cell targeting, and actin regulation. Active projects span EU-funded drug discovery and NIH collaborations. Key scientific contributions include Elucidating Sec61-client interactions Developing computational models for signal peptide prediction Uncovering mitochondrial-ER communication mechanisms He has supervised PhD theses (e.g., Paul Carlson) and contributed to over 39 research outputs. His work bridges structural biology, computational modeling, and translational pharmacology, with applications in tumor biology and neurodegenerative disease research.

Jasmine FooView profile

Professor

• Cancer Evolution
• Mathematical Oncology
• Stochastic Modeling
• +4 more

Jasmine Foo serves as Associate Head and Distinguished McKnight University Professor at the University of Minnesota-Twin Cities' School of Mathematics, holding the Northrop Professorship and co-directing the Therapy Modeling and Design Center. Her leadership spans academic administration and interdisciplinary research initiatives in mathematical oncology. Foo's research pioneers stochastic evolutionary modeling of cancer dynamics, integrating mathematical theory with clinical data to understand tumor initiation, progression, and treatment resistance. Her group focuses on five interconnected themes: plasticity and epigenetics in tumor evolution; drug resistance optimization; data-driven precision oncology; spatial carcinogenesis; and tumor-microenvironment interactions using organoid models. This work bridges probability theory, systems biology, and clinical oncology to develop novel therapeutic strategies. Analysis of her 15 most recent publications reveals a consistent emphasis on quantitative approaches to cancer evolution, with growing integration of machine learning and high-resolution experimental data. Key trends include modeling phenotypic plasticity in resistance development, optimizing dosing schedules using evolutionary principles, and translating spatial tumor dynamics into clinical applications. Scientific recognition includes: Honorable Mention, Feldman Prize for theoretical contributions to tumor evolution modeling Foo actively mentors graduate students and postdoctoral researchers through the School of Mathematics, with research supported by multiple grants (though specific funding sources aren't detailed). Her group maintains strong collaborations with experimental oncology labs and clinical researchers, facilitating data-driven model validation. She co-leads the Therapy Modeling and Design Center and organizes the UMN MathBio Group Meetings, fostering cross-disciplinary collaboration between mathematicians, biologists, and clinicians in cancer research.

Angela DepaceView profile

Assistant Professor

• Gene Regulation
• Cis-Regulatory Elements
• Transcriptional Networks
• +5 more

Angela Depace is an Assistant Professor at Harvard Medical School, specializing in Gene Regulation , Cis-Regulatory Elements , and Quantitative Developmental Biology . Her research integrates experimental and computational approaches to study how transcription factors and enhancer sequences control gene expression in Drosophila embryos, with implications for evolutionary biology and synthetic biology . B.S., Molecular Biophysics and Biochemistry, Yale University Ph.D., Biochemistry, University of California, San Francisco (advisor: Jonathan Weissman) Postdoctoral Research, University of California, Berkeley (advisor: Michael Eisen) Her work focuses on unraveling the kinetic roles of transcriptional activators , the evolution of regulatory sequences , and the computational modeling of gene networks . Recent publications explore mechanistic principles of enhancer function , transcriptional synergy , and developmental precision . Scientific contributions include the NSF CAREER Award and co-authoring Visual Strategies: A Practical Guide to Graphics for Scientists and Engineers . Her lab emphasizes collaborative research , mentoring , and innovative teaching in systems biology graduate courses.

Zuri SullivanView profile

Research Fellow

• Immunology
• Neuroscience
• Neuroimmunology
• +5 more

Zuri Sullivan is a postdoctoral researcher at Harvard University, affiliated with the Catherine Dulac Lab. Her work focuses on the intersection of immunology and neuroscience, particularly how inflammatory signals influence social behavior in mice through hypothalamic circuits. Education: PhD in Immunobiology from Yale University AB in Molecular and Cellular Biology (MCB) from Harvard College Research interests span neuroimmunology, inflammation, and genetic screening. Key projects include studying mast cell-leukotriene signaling in anaphylaxis, hypothalamic circuitry in social homeostasis, and the role of γδ T cells in nutrient sensing. Her work often integrates immunobiology with behavioral neuroscience. Recent publications highlight her contributions to understanding immune-gut-brain axis interactions, genetic tools for tissue mapping, and disease mechanisms in obesity-related cancer and tuberculosis. She also develops innovative multimodal screening platforms for in vivo gene function analysis. Scientific Awards: HHMI Hanna H. Gray Postdoctoral Fellowship Zuri actively promotes science communication, diversity in STEM, and education outreach. She previously studied intestinal immune adaptation to diet during her PhD at Yale under Ruslan Medzhitov. Collaborations with William Bishai and Ruslan Medzhitov feature prominently in her research portfolio.

Irène MarcoviciView profile

Professor

• Probability Theory
• Dynamical Systems
• Cellular Automata
• +4 more

Irène Marcovici is a Professor in the Department of Mathematics at the University of Rouen Normandy, affiliated with the Raphaël Salem Mathematics Laboratory (LMRS). She leads the Probability and Dynamical Systems team within LMRS and participates in the ALEA and SDA2 working groups of the GDR Informatique Fondamentale et ses Mathématiques. PhD in Mathematics (2013, University of Paris Diderot) Habilitation à Diriger des Recherches (2021, University of Lorraine) Her research focuses on probability theory , dynamical systems , and cellular automata , with significant contributions to percolation theory, self-organization phenomena, and combinatorics on words. She investigates how randomness influences complex systems, particularly through probabilistic cellular automata and their ergodic properties. Analysis of her recent publications (2021-2025) reveals a strong emphasis on percolation dynamics (e.g., corner percolation with directional bias), self-stabilization mechanisms in cellular systems, and combinatorial structures like Kolakoski sequences. Her work bridges theoretical computer science and pure mathematics, often employing stochastic methods to solve problems in symbolic dynamics and discrete geometry. Supervision & Collaborations: Currently supervising Maxence Poutrel (with Jérôme Casse) Previously supervised Pierrick Siest (2021-2024), Jocelyn Begeot (now Associate Professor), and Pierre-Adrien Tahay (now PRAG at Telecom Nancy) Regular collaborations with Régine Marchand, Nazim Fatès, and Pascal Moyal Laboratory Context: As leader of the Probability and Dynamical Systems team at LMRS, she contributes to France's national research infrastructure in fundamental mathematics, with connections to CNRS and international working groups focused on automata theory and discrete probability.

• Hematopoiesis
• Developmental Biology
• Imaging Flow Cytometry
• +3 more

Kathleen E. McGrath is a Research Professor in the Department of Pediatrics, Hematology and Oncology at the University of Rochester School of Medicine and Dentistry. She earned her Ph.D. in Biology from the University of Rochester in 1993, an M.S. in Biology from the same institution in 1987, and a B.A. in Biology from Reed College in 1983. Dr. McGrath's research focuses on the emergence and regulation of hematopoiesis in mammalian embryos and its recovery post-radiation. She specializes in imaging flow cytometry for analyzing rare hematopoietic populations and studies erythroid-myeloid progenitors during embryogenesis. Her work intersects developmental biology, hematology, and regenerative medicine. Her recent publications highlight advancements in erythroid self-renewal, megakaryocyte immune roles, and radiation injury recovery. Notable collaborations include contributions to the Palis Lab's investigations into hematopoietic stem cell dynamics and niche interactions. Scientific Awards: Leon Wheeless Innovation in Cytometry Award (2007)

Olivier GevaertView profile

Associate Professor

• Biomedical Data Fusion
• Machine Learning
• Cancer Driver Genes
• +6 more

Olivier Gevaert is an Associate Professor at Stanford University with dual appointments in the Department of Medicine (Biomedical Informatics) and the Department of Biomedical Data Science. He leads interdisciplinary research at the intersection of machine learning and biomedical data fusion, with significant contributions to cancer genomics, imaging biomarkers, and synthetic biomedical data generation. His work spans multiple Stanford institutes including Bio-X, Cancer Institute, and Neurosciences Institute. His research focuses on: Biomedical data fusion across molecular, cellular, and tissue scales Multi-omics integration for cancer driver gene discovery Imaging genomics/radiogenomics Medical digital twin frameworks Synthetic data generation for machine learning Key awards include Faculty Fellow at Stanford Center at Peking University and fellowships from King Baudouin Foundation and Belgian American Educational Foundation. His lab has produced transformative tools like Moonlight, EpiMix, SEQUOIA, and RNA-GAN. He teaches foundational courses in biomedical data science and machine learning approaches.