Cell Segmentation and Tracking Professors and Supervisors

Manuel Fernández Delgadoمشاهده پروفایل

دانشیار

University of Santiago de CompostelaSpain

Manuel Fernández Delgado is an Associate Professor at the University of Santiago de Compostela (manuel.fernandez.delgado@usc.es). His research spans Machine Learning , Pattern Recognition , and Computer Vision with applications in medical diagnostics, agricultural monitoring, and gender-inclusive education. PhD in Computer Science (1999) Developed software tools: Govocitos , CystAnalyser , STERapp Research highlights: Medical Imaging : Breast cancer and oral leukoplakia analysis via image segmentation/classification Agricultural AI : Nutrient deficiency detection in wheat, marbling analysis in ham Gender Equality : Pioneering computational thinking education with gender perspectives Robotics : Fault diagnosis systems for antenna arrays Key methodologies include Extreme Learning Machines, Support Vector Machines, and Deep Learning. He collaborates with teams in TELGalicia and TecAnDaLi networks.

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Daria Ilatovskayaمشاهده پروفایل

دانشیار

Augusta UniversityUnited States

Dr. Daria Ilatovskaya is a tenured Associate Professor of Physiology at the Medical College of Georgia, Augusta University where she also serves as Graduate Program Director for the Physiology Graduate Program. She leads the Kidney and Hypertension Research Group and has adjunct roles in The Graduate School. Education: Ph.D. Cellular Biology, Institute of Cytology, Russian Academy of Sciences, 2012 M.S. Physics, Peter the Great Saint Petersburg Polytechnic University, 2009 B.S. Physics, Peter the Great Saint Petersburg Polytechnic University, 2007 Research Focus: Dr. Ilatovskaya’s laboratory integrates in vivo, ex vivo and in vitro approaches to dissect how ion channels, mitochondrial bioenergetics and sex hormones govern cardiorenal homeostasis. Areas of emphasis include: Salt-sensitive hypertension and blood pressure control Polycystic kidney disease (ARPKD & ADPKD) Mitochondrial dysfunction in podocytes and tubular epithelia Sex-specific pathobiology and precision medicine Her team employs state-of-the-art techniques such as single-channel electrophysiology on freshly isolated nephron segments, live-cell confocal imaging, high-resolution mitochondrial respirometry and chronic blood-pressure telemetry. Publication Impact: Across 93 scholarly outputs (h-index 29), her 2024–2025 portfolio reveals a surge in translational studies elucidating ANP-mediated mitochondrial protection, sex-specific redox control of podocytes, and community-based hypertension interventions in rural Georgia. Awards & Honors: Outstanding Early Career Basic Science Faculty Award, Augusta University (2025) Young Investigator Award, APS Renal Section (2024) Lazaro J Mandel Young Investigator Award (2019) FAHA distinction, American Heart Association (2018) Edward J. Lennon Award for Outstanding Woman Postdoc (2014) Funding & Mentorship: Dr. Ilatovskaya is PI or Co-I on five active NIH grants totaling >$4 million, including two NHLBI R01s investigating ANP signaling and women’s cardiovascular health. She mentors graduate students, postdocs and undergraduates, and champions diversity through CUR’s STR program. Laboratory & Team: The Ilatovskaya Lab (Lab CA-3091) currently includes an Assistant Scientist (track), senior research assistant, three graduate students and an honors undergraduate, fostering an inclusive environment centered on rigorous science and trainee success.

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Gözde YOLCU ÖZTELمشاهده پروفایل

استادیار

Sakarya UniversityTurkey

Gözde YOLCU ÖZTEL serves as Assistant Professor in the Department of Software Engineering at Sakarya University's Faculty of Computer and Information Sciences. With a Ph.D. in Computer and Information Engineering completed in 2019, she has established herself as an active researcher in artificial intelligence with significant contributions to computer vision applications. Her educational journey includes: Ph.D. in Computer and Information Engineering (2014-2019) with thesis on deep learning-based interest detection through facial analysis M.Sc. in Computer and Information Engineering (2012-2014) focusing on Kinect-based virtual mirror design B.Sc. in Computer Engineering (2007-2011) from Sakarya University Dr. YOLCU ÖZTEL's research bridges deep learning with practical healthcare and public safety applications. Her work demonstrates exceptional adaptability to emerging challenges, particularly in developing AI systems for pandemic response (masked face detection, social distancing monitoring) and medical diagnostics (monkeypox/skin lesion classification). She specializes in creating efficient mobile-compatible deep learning models that maintain accuracy while operating on resource-constrained devices. Analysis of her 15 most recent publications reveals a clear trajectory toward healthcare-oriented computer vision, with increasing focus on mobile medical applications since 2020. Her research consistently combines novel deep learning architectures with real-world implementation constraints, particularly smartphone deployment. The integration of traditional computer vision techniques (like LBP) with modern deep networks represents a distinctive methodological signature across her work. She actively contributes to research through TÜBİTAK 2209 projects as student advisor and leads institutional research initiatives including SAYZEK-ATP (2024) and MAG Engineering Research Support Group. Her project portfolio spans from mathematical assistant software development to emergency drone-based object detection and MRI-based brain tumor classification. Dr. YOLCU ÖZTEL teaches core software engineering courses including Database Management Systems, Artificial Intelligence Fundamentals, and Data Mining while maintaining active research output. She previously organized the 2017 Facial Expression Recognition workshop, demonstrating ongoing commitment to academic community building.

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Christian Doellerمشاهده پروفایل

استاد

Norwegian University of Science and TechnologyNorway

Translational Neuroscience of Ageing
Alzheimer's Disease
Cognitive Neuroscience of Learning and Memory
+۶ مورد دیگر

Christian Doeller is a Professor of Medicine (Neuroscience) at the Norwegian University of Science and Technology (NTNU), leading research at the Kavli Institute for Systems Neuroscience . He also serves as Managing Director of the Max Planck Institute for Human Cognitive and Brain Sciences and Professor of Psychology (Learning and Memory) at Leipzig University , Germany. Specializes in translational neuroscience of ageing and Alzheimer's disease Focuses on cognitive neuroscience of learning and memory Key projects: Jebsen Centre for Alzheimer's Disease, Helse Midt-Norge, and ERC-CoG project GEOCOG His recent research explores hippocampal-entorhinal cognitive maps, spatial navigation, and memory reconfiguration across abstract and Euclidean spaces. Collaborations span NTNU, Max Planck Institute, and Leipzig University. Notable article trends include human cognitive neuroscience applications, neuroimaging techniques (DTI-fMRI, eye tracking), and neural coding in memory systems. Themes like stress effects on memory and cortical motor system interactions with cognitive maps are recurrent. Christian Doeller's team investigates brain mapping and neurodegenerative diseases, leveraging advanced neuroimaging and computational models. His work bridges basic neuroscience with clinical applications in Alzheimer's research.

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Adrian Rangaمشاهده پروفایل

دانشیار

KU LeuvenBelgium

Adrian Ranga is an Associate Professor at the Department of Mechanical Engineering within KU Leuven's Faculty of Engineering Science . He leads research at the BioMechanics (BMe) section, with affiliations to multiple institutes including the KU Leuven Institute of Physics-based Modeling for In Silico Health , Brain Institute , and Institute for Single Cell Omics . His work focuses on organoid engineering , mechanical force manipulation , and vascularization technologies using microfluidic devices . Key Research Areas: Vascular and neural organoid development Microfluidic cell culture systems Mechanotransduction mechanisms Stem cell-based tissue engineering Recent Publications (2025–2024) demonstrate expertise in 3D bioprinting , force-mediated angiogenesis , and comparative neurodevelopment across species. His patent applications include discrete cell culture microenvironments and photopolymerized devices . Collaborative projects span the Interreg Biomat-on-Chip Consortium and FWO-funded initiatives .

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Mackenzie Weygandt Mathisمشاهده پروفایل

استادیار

Swiss Federal Institute of Technology in LausanneSwitzerland

Prof. Mackenzie Weygandt Mathis is Tenure-Track Assistant Professor and Bertarelli Foundation Chair of Integrative Neuroscience at EPFL’s Brain Mind Institute . Leading the Mathis Lab since 2020, she unites machine learning and systems neuroscience to decipher how brains learn and control movement. Education : PhD in Neuroscience, Harvard University (2017, advisor Naoshige Uchida) Post-doctoral training, University of Tübingen with Matthias Bethge (2017) Rowland Fellow, Harvard University (2017-2020) Research Focus : the lab develops open-source AI tools ( DeepLabCut , CEBRA , AmadeusGPT ) and combines them with large-scale neural recordings in behaving mice to uncover the neural basis of adaptive motor control. Core themes include sensorimotor learning, proprioception, and brain-inspired algorithms for robotics. Publications Trend : recent work spans robust machine-learning methods (ICLR, AISTATS 2025), foundational models for pose estimation ( SuperAnimal , 2024), and integrative studies linking neural population dynamics to muscle-level control ( Nature 2023, Cell 2024). Scientific Awards : Swiss Science Prize Latsis 2024 Robert Bing Prize 2024 Eric Kandel Young Neuroscientist Prize 2023 FENS EJN Young Investigator Prize 2022 Vallee Scholar, ELLIS Scholar, NSF Graduate Fellow Advising & Funding : she mentors 4 current PhD students and several postdocs, supported by SNSF Starting Grant (1.5 M CHF), CZI, Novartis, Radala Foundation, and Kavli Foundation grants. Labs & Teams : the Mathis Lab is located at Campus Biotech , Geneva, and actively collaborates with the Alexander Mathis group, Allen Institute, and international consortiums on open-source neuroscience tools.

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Qian Zhuمشاهده پروفایل

استادیار

Baylor College of MedicineUnited States

Qian Zhu is an Assistant Professor at Baylor College of Medicine in the Department of Molecular Genetics . He earned a BSc in Computer Science and Biochemistry from the University of Ottawa , a PhD in Computational Biology from Princeton University , and completed postdoctoral training at Dana-Farber Cancer Institute/Harvard Medical School . Research Focus : Computational Biology, Cancer Genomics, Spatial Transcriptomics Key Projects : Spatial Multiomic Integration, Triple Negative Breast Cancer Disparities, Chromatin Structure Analysis, Software Development Recent Trends : His 15 most recent publications (2025-2018) focus on spatial transcriptomics tools ( Giotto , Xenomake ), cancer disparities research, chromatin structure analysis, and computational methods for single-cell data integration. These works reflect expertise in machine learning application to biomedical imaging, tumor microenvironment characterization, and epigenetic regulation. 2025 : Spatial omics analysis of racial disparities in TNBC 2024 : BCL11A tetramer function, xenograft data processing 2023 : CRISPR screening in leukemia 2022 : Chromatin regulators in developmental disease Awards : 2025 - Marion R. Wright Award for Scientific Excellence 2022 - CPRIT Tenure-Track Faculty Recruitment Award Collaborations : Works with experimental biologists on tumor progression, therapy resistance, and hematopoietic development. His lab includes bioinformatics programmers and graduate students.

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Robert Knightمشاهده پروفایل

پژوهشگر

King’s College LondonUnited Kingdom

Dr. Robert Knight is a Reader in Developmental Genetics at King’s College London, affiliated with the Centre for Craniofacial & Regenerative Biology and Faculty of Dentistry, Oral & Craniofacial Sciences. He obtained his PhD in Molecular Evolution from the University of Reading in 2000, followed by postdoctoral work at UC Irvine and University of Sheffield, focusing on AP-2 genes, neural crest, and cranial muscle development in zebrafish. His research explores molecular regulation of muscle regeneration and stem cell behavior, combining live imaging, transcriptomics, and zebrafish models. Key findings include the role of Ret tyrosine kinase in facial muscle development and FSHD therapy, RhoA coupling migration/differentiation, and NF-κB in macrophage function during repair. Collaborations span systems biology (Dresden), physiology (Amsterdam), and macrophage signaling (Lyon). Recent publications highlight trends in muscle stem cell dynamics , signaling pathways (Wnt, Notch, Ret), and age-related regeneration . His work aligns with SDGs via health (musculoskeletal diseases) and innovation (AI in biosciences, multiphoton microscopy). Scientific Awards: BBSRC Project Award MDUK Studentship NC3Rs Studentship Royal Society Partnership Award Carl Zeiss Collaboration Current projects address DUX4-activated Ret in FSHD, chromatin organization in aging, and macrophage-stem cell interactions . He leads grants from BBSRC, Dunhill Medical Trust, and Leverhulme Trust.

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Yulong Yanمشاهده پروفایل

استاد

University of Texas Southwestern Medical CenterUnited States

Dr. Yulong Yan is a Professor in the Department of Radiation Oncology at UT Southwestern Medical Center, where he serves as Director of Computational Physics and faculty in the Division of Medical Physics & Engineering. His career spans academic, clinical, and technical domains in radiation oncology and biomedical engineering. Bachelor's & Master's: Nanjing University of Aeronautics and Astronautics Ph.D.: Biomedical Engineering, Southeast University, Nanjing Fellowship/Residency: Stanford University School of Medicine Dr. Yan's research focuses on Medical Physics , Adaptive Radiotherapy , and Deep Learning applications in clinical oncology. Key areas include: Functional lung avoidance techniques (FWAS, virtual bronchoscopy) Deep learning for synthetic CT generation and tumor segmentation Dose verification platforms (ART2Dose) Radiation toxicity modeling for brain and lung treatments Bluetooth-based localization systems for clinical applications MR-only radiotherapy workflows His publications demonstrate expertise in Image-Guided Radiotherapy , Treatment Planning Optimization , and Radiation Dose Modeling , with a 2013–2024 publication record showing sustained contributions to Medical Physics , Radiotherapy and Oncology , and PLOS One . Dr. Yan has served as Associate Editor for Medical Physics and Journal of Clinical Medical Physics , while chairing the Southwest Chapter AAPM Communications and IT Committee since 2014. As an educator since 2013, he mentors medical physics residents and postdoctoral fellows while delivering lectures in the Medical Physics Certificate Program.

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Benedikt Wirthمشاهده پروفایل

استاد

University of MünsterGermany

Prof. Dr. Benedikt Wirth is a Professor of Mathematics at the University of Münster, Germany, affiliated with the Institute for Analysis and Numerics within the Department of Mathematics and Computer Science. He is an active researcher and educator specializing in optimization and calculus of variations, with significant contributions to mathematical imaging and shape analysis. His research interests include image processing, scientific computing, numerical analysis, optimization, shape spaces, geodesics in shape space, variational methods, elastic deformation, and optimal transport. Wirth has developed innovative mathematical frameworks for shape analysis, particularly focusing on Riemannian metrics for shape spaces and variational approaches to shape comparison and optimization. His recent publications (2023-2025) demonstrate continued leadership in mathematical optimization, with particular focus on PET reconstruction, dimension reduction techniques, manifold embeddings, and branched transport theory. His work bridges theoretical mathematics with practical applications in medical imaging and computer vision, showing particular strength in connecting geometric analysis with computational methods. CRC 1450 - A05: Targeting immune cell dynamics by longitudinal whole-body imaging and mathematical modelling CRC 1450 - A06: Improving intravital microscopy of inflammatory cell response by active motion compensation EXC 2044 - C1: Evolution and asymptotics EXC 2044 - C2: Multi-scale phenomena and macroscopic structures EXC 2044 - C3: Interacting particle systems and phase transitions EXC 2044 - C4: Geometry-based modelling, approximation, and reduction Prof. Wirth actively supervises numerous bachelor's and master's students, with over 40 theses completed under his guidance since 2015. His teaching portfolio includes courses on inverse problems, numerical methods for partial differential equations, shape spaces, optimization, and optimal transport. He has consistently maintained an active research program while contributing significantly to the education of the next generation of mathematicians.

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Johannes Schönebergمشاهده پروفایل

استادیار

University of California, San DiegoUnited States

Johannes Schöneberg serves as Assistant Professor of Pharmacology at the University of California San Diego's School of Medicine, holding joint appointments in Chemistry & Biochemistry. His research integrates cutting-edge microscopy, computational biology, and stem cell technologies to quantitatively analyze cellular behavior in native tissue environments. His laboratory focuses on mitochondrial dynamics and their role in neurological disorders including Parkinson's Disease and epilepsy. Key methodologies include stem cell-derived organoids, 4D adaptive optics lattice light-sheet microscopy, high-performance computing, and machine learning applications. Research spans computational modeling of cellular processes through tools like ReaDDy software to advanced image analysis techniques for tracking subcellular structures. The group's publication record demonstrates expertise across biophysics, computational biology, and neuropharmacology, with recent work emphasizing mitochondrial network tracking and 4D cellular imaging. Though newly established at UCSD, the lab shows strong interdisciplinary connections through collaborations with microscopy pioneers like Eric Betzig. No scientific awards are currently listed in available sources. The laboratory maintains active research in neurological disease mechanisms with emphasis on mitochondrial dysfunction pathways. As a newly formed research group, current activities focus on establishing organoid models and advanced imaging pipelines. The lab leverages UCSD's strong infrastructure in computational biology and neuroscience research, with potential for future grant development in mitochondrial disease mechanisms and imaging technology.

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Robert Haaseمشاهده پروفایل

مدرس

Leipzig UniversityGermany

Dr. Robert Haase is a Lecturer and Training Coordinator at the Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) under Leipzig University , with prior leadership roles at the DFG Cluster of Excellence 'Physics of Life' at TU Dresden . He specializes in Bioimage Analysis , GPU-Accelerated Image Processing , and Large Language Models (LLMs) for life sciences. His research focuses on democratizing bioimage analysis through open-source tools like CLIJ , clesperanto , and bia-bob , aiming to bridge microscopy with data science . Recent projects explore LLM-driven code generation for image analysis and interactive workflow design in platforms like napari . He leads initiatives such as the NFDI4BioImage consortium for research data management in Germany and GloBIAS , a global society for bioimage analysts. Funded by organizations including the Chan Zuckerberg Initiative (CZI) and DFG , his work emphasizes reproducibility , open science , and interdisciplinary collaboration in bioimaging. As an educator, he conducts training programs like "Large Language Models for Bioimage Analysis" and "Collaborative Working with Git" , and contributes to workshops at institutions such as EMBO , Institut Pasteur , and ScaDS.AI Summer Schools .

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Nikolay Kutuzovمشاهده پروفایل

استادیار

University of CopenhagenDenmark

Nikolay Kutuzov serves as an Assistant Professor in the Department of Neuroscience at the University of Copenhagen's Faculty of Health and Medical Sciences. His research employs two-photon microscopy and deep learning to investigate cerebrovascular dynamics, blood-brain barrier function, and pericyte biology in health and aging. Kutuzov's work centers on neurovascular coupling, with key interests including blood-brain barrier transport mechanisms, capillary pericyte function, and the role of precapillary sphincters in regulating cerebral blood flow. He integrates experimental neuroscience with computational approaches, particularly deep learning applications for nanoparticle tracking and image analysis in two-photon microscopy. His recent publications (2018-2025) demonstrate a progression from foundational studies on myelin organization to innovative work combining deep learning with in vivo imaging. Current research emphasizes aging-related cerebrovascular changes and nanoparticle diffusion modeling, reflecting a multidisciplinary approach that bridges molecular neuroscience and biomedical engineering. Though specific advising details are unreported, his collaborative publications with leading neuroscientists suggest mentorship activities. His laboratory likely utilizes advanced imaging facilities at the University of Copenhagen for studying neurovascular unit dynamics, with potential focus on developing new computational tools for brain barrier research.

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