جست‌وجوی استاد و پژوهشگر

• Psychiatry
• Clinical Psychology
• Psychosis Research
• +۴ مورد دیگر

Chantal Michel is an Associate Professor and Group Leader at the University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern. She is also the Scientific and Clinical Co-Head of the Early Detection and Intervention Centre for Mental Crisis (FETZ Bern). Her work focuses on early detection and intervention for individuals at clinical high risk (CHR) for psychosis, with expertise in transdiagnostic therapeutic approaches and the application of technologies like ecological momentary assessments and virtual reality. Dr. Michel holds a habilitation in Psychiatry and has led numerous studies on neuroimaging correlates of psychosis risk, cognitive deficits, and mental health service utilization patterns. Her research interests span psychosis spectrum disorders, developmental psychopathology, and the neurobiological underpinnings of mental health issues. Dr. Michel has published extensively on topics such as EEG biomarkers in psychosis, white matter abnormalities in CHR populations, and the implementation of national psychosis prevention networks. She is actively involved in clinical trials and machine learning approaches to personalize treatment decisions for at-risk individuals. Dr. Michel's contributions include pioneering work on age-related effects of psychosis symptoms, the role of coping strategies in psychopathology, and the integration of innovative technologies in mental health monitoring. She has presented her findings at major conferences like the International Early Intervention in Mental Health (IEPA) and the European Society for Child and Adolescent Psychiatry (ESCAP).

• Developmental Neuroscience
• Psychiatric Disorders
• Neuroimaging
• +۳ مورد دیگر

Ravi Bansal, PhD, serves as a Research Professor in the Departments of Psychiatry and Behavioral Sciences and Pediatrics at the University of Southern California (USC), with primary affiliation to the Keck School of Medicine. His research program integrates advanced neuroimaging with developmental psychiatry to investigate brain development from prenatal stages through adulthood, focusing on environmental and biological determinants of neurocognitive outcomes. Dr. Bansal's research interests center on Developmental Neuroscience and Psychiatric Disorders , utilizing Neuroimaging to examine how prenatal exposures—including maternal nutrition (zinc, iron), immune activation, air pollution, and socioeconomic factors—shape infant brain structure, metabolism, and connectivity. His work identifies early biomarkers for conditions like autism spectrum disorder and depression, employing multimodal MRI techniques to dissect tissue microstructure and functional networks. This research bridges pediatric neurology and psychiatry, emphasizing translational applications for early intervention. Analysis of his 15 most recent publications (2022-2025) reveals three dominant trends: (1) longitudinal studies tracking brain development in preterm/term infants exposed to prenatal risks; (2) neurotoxic effects of pediatric cancer treatments (e.g., methotrexate in leukemia); and (3) advanced statistical frameworks for parsing heterogeneity in psychiatric conditions. His methodology increasingly combines diffusion tensor imaging, spectroscopy, and machine learning to correlate imaging phenotypes with clinical outcomes across depression, autism, and schizophrenia spectra.

• Congenital Heart Disease
• Neurodevelopmental Outcomes
• Fetal Imaging
• +۵ مورد دیگر

Jodie K. Votava-Smith, MD, is a Clinical Associate Professor in the Department of Clinical Pediatrics at the University of Southern California , with clinical and research affiliations to Children's Hospital Los Angeles (CHLA) . Her work focuses on the neurodevelopmental and hemodynamic consequences of congenital heart disease in neonates and infants. Research Themes : Her publications highlight interdisciplinary research at the intersection of Pediatric Cardiology Neurovascular Interaction Fetal Brain Development Placental Hemodynamics Developmental Outcomes in Congenital Heart Disease Sociodemographic Influences on Cardiac Anomalies Scientific Contributions : Through over 20 peer-reviewed articles since 2005, she has advanced understanding of cerebral autoregulation , brain dysmaturation , and neurovascular coupling in cardiac infants, employing advanced imaging modalities like MRI and near-infrared spectroscopy.

Stefanos Aldo Papanicolopulosمشاهده پروفایل

مدرس ارشد

• Computational Mechanics
• Micromechanics of Materials
• Mechanics of Generalized Continua
• +۴ مورد دیگر

Dr. Stefanos Aldo Papanicolopulos is a Senior Lecturer in the School of Engineering at the University of Edinburgh, specializing in Civil and Environmental Engineering . His research focuses on computational mechanics, micromechanics of materials, and mechanics of generalized continua, with applications to granular materials and strain-gradient elasticity. Education: MEng in Civil Engineering (2002), National Technical University of Athens MSc in Structural Engineering (2004), National Technical University of Athens PhD in Mechanics (2008), National Technical University of Athens Research Interests: Mechanics of generalized continua, including Cosserat and micropolar theories Micromechanical modeling of granular materials using DEM and FEM Strain-gradient elasticity and computational methods Development of efficient finite element and cubature rules Experimental and numerical studies of particle breakage and flow Scientific Awards: Fellow of the Higher Education Academy Grant Collaborations: Active EU-funded projects like TUSAIL (Training In Upscaling Particle Systems) and grants from the Carnegie Trust for Scottish Universities. Key collaborations include the VELaSSCo platform for DEM data visualization.

Alejandro F Frangiمشاهده پروفایل

استاد

• Medical Image Analysis
• Computational Physiology
• Machine Learning
• +۲ مورد دیگر

Alejandro F. Frangi is the Bicentenary Turing Chair in Computational Medicine and Royal Academy of Engineering Chair in Emerging Technologies at the University of Manchester, with joint appointments in the School of Computer Science and School of Health Sciences. He serves as Director of the Christabel Pankhurst Institute and leads the NIHR Manchester Biomedical Research Centre's Digital Infrastructure theme. His education includes a PhD in Medicine from Utrecht University (2001) and an undergraduate degree in Telecommunications Engineering from Universitat Politècnica de Catalunya (1996). He holds honorary positions at KU Leuven and is an Alan Turing Institute Fellow. Professor Frangi's research bridges medical image analysis and computational modeling, with emphases on: Machine learning for population imaging In silico clinical trials for medical devices Computational physiology in cardiovascular and neurosciences Statistical methods for image-based biomarkers His recent publications demonstrate strong focus on AI-driven medical image reconstruction, computational modeling of vascular diseases, and virtual clinical trial methodologies. Research trends show consistent innovation in deep learning architectures for 3D medical image processing. Awards and honors include: IEEE Engineering in Medicine and Biology Technical Achievement Award (2021) Fellow of Royal Academy of Engineering (2023) ERC Advanced Grant recipient President's International Initiative Award from Chinese Academy of Science He has supervised 28+ PhD students to completion and currently leads multiple major grants including a £2.7m Royal Academy of Engineering Chair award. His laboratory develops open-source platforms (GIMIAS, MULTI-X) and has spun off three companies (GalgoMedical, adSilico). As Director of the Christabel Pankhurst Institute, he oversees interdisciplinary teams working on health technology innovation. He founded the InSilicoUK Innovation Network to advance regulatory science for in silico methods.

Hongxu Chenمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Data Mining
• Recommender Systems
• +۳ مورد دیگر

Dr. Hongxu Chen serves as an Honorary Research Fellow at the University of Queensland's School of Electrical Engineering and Computer Science. His research focuses on machine learning, data mining, and network analysis, particularly in the context of recommendation systems and graph-based models. He has contributed to advancements in graph neural networks, network representation learning, and social network analysis through collaborative projects with international researchers. Dr. Chen's work spans theoretical and applied domains, including social-boosted recommendation systems, graph convolutional networks for centrality analysis, and scalable tensor factorization models. His publications address challenges in link prediction, user behavior modeling, and mobility demand forecasting using graph-based and probabilistic approaches. While no formal awards are listed, his contributions reflect significant engagement with high-impact conferences like NeurIPS, ICDE, and KDD. No advising or grant details are provided in the text. His research activities are centered within the School of Electrical Engineering and Computer Science, though specific lab affiliations are not mentioned.

David Shattuckمشاهده پروفایل

استاد مدعو

• Neuroimaging
• Computational Biology
• Brain Imaging
• +۲ مورد دیگر

David Shattuck is an Adjunct Professor in the Department of Neurology at the University of California Los Angeles (UCLA) School of Medicine. He specializes in neuroimaging and computational neuroscience , with a focus on developing advanced software tools for brain analysis. Academic Affiliation: University of California Los Angeles Department: Neurology Research Focus: Neuroimaging, Brain Segmentation, Cortical Thickness Analysis, Computational Biology Research Contributions: Dr. Shattuck is the principal investigator for NIH R01NS074980 , developing the BrainSuite software suite for multimodal brain imaging analysis and visualization. His work spans human connectome mapping , mouse brain atlases , and neurodegenerative disease imaging . Scientific Trends: His recent publications emphasize deep learning in neuroimaging (e.g., SwinUNETR for mouse brain segmentation), structure tensor analysis for brain tissue orientation, and VR environments for neuroimaging visualization. Keywords across his work include Neuroscience , Medical Informatics , Genetic Disorders , and Biomedical Imaging . Collaborations: Dr. Shattuck collaborates extensively with researchers in neuroimaging genetics , clinical neuroscience , and computational biology , including Arthur Toga, Paul Thompson, and Richard Leahy.

Todd Martinezمشاهده پروفایل

استاد

• Theoretical Chemistry
• Photochemistry
• Mechanochemistry
• +۳ مورد دیگر

Todd Martinez is the David Mulvane Ehrsam and Edward Curtis Franklin Professor of Chemistry and Professor of Photon Science at Stanford University, affiliated with SLAC National Accelerator Laboratory. His research focuses on theoretical and computational chemistry, with emphasis on photochemistry, mechanochemistry, and quantum mechanical methods. He earned his PhD in Chemistry from UCLA in 1994, followed by postdoctoral work at UCLA and the Hebrew University in Jerusalem before joining Stanford in 2009. His group develops novel simulation tools, including GPU-accelerated quantum chemistry software (e.g., TeraChem) and virtual reality interfaces (InteraChem and MolAR) for interactive molecular modeling. Key interests include predicting molecular behavior under light and mechanical force, designing self-healing materials, and advancing reaction discovery through first-principles methods. Awards include the MacArthur Fellowship and recognition as a Fellow of the American Academy of Arts and Sciences. Education: PhD in Chemistry (UCLA, 1994); Postdoctoral Studies at UCLA and Hebrew University (Jerusalem) Research Themes: Molecular modeling, excited-state dynamics, mechanochemical reactions, and computational tools Publications span ultrafast spectroscopy, quantum mechanical modeling, and algorithm development for large-scale simulations. The Martinez Group’s work bridges theory and application, aiming to make molecular design predictive and accessible through interdisciplinary collaborations.

Steven Lippoldمشاهده پروفایل

استادیار

• Multilinear Algebra
• Generalizations of Linear Algebra Concepts
• Combinatorics

Steven Lippold is an Assistant Professor of Mathematics at Geneva College. He holds a B.S. in Mathematics and Physics from Clarion University of Pennsylvania (2017), an M.A. in Mathematics from Bowling Green State University (2018), and a Ph.D. in Mathematics from Bowling Green State University (2023). His research focuses on Multilinear Algebra, Generalizations of Linear Algebra Concepts, and Combinatorics. His work includes studies on matrix structures, determinant-like functions, and hypergraph partitions. Dr. Lippold has been recognized with the Graduate Excellence in Teaching Award (2023), the Judyta & Bronislaw Blass Memorial Fellowship (2022), and the James Robert and Gretchen Overman Scholarship (2018-2019). He is a member of the Mathematical Association of America, Association of Christians in the Mathematical Sciences, and the American Mathematical Society. His professional certifications include Python for Data Science and Machine Learning (Udemy, 2023), Teaching and Learning Certificate (Bowling Green State University, 2020), and Google IT Automation with Python (2021). His academic journey includes consistent academic excellence, reflected in his Dean’s List status at Clarion University (2014-2017) and membership in honor societies like Phi Kappa Phi and Pi Mu Epsilon. His research contributions span algebraic structures, linear algebra extensions, and combinatorial applications, with recent publications in Linear Algebra and Its Applications and Monatshefte fu¨r Mathematik .

Jens Macheمشاهده پروفایل

استاد

• Parallel and Distributed Systems
• Networking
• Cybersecurity
• +۳ مورد دیگر

Jens Mache is a Full Professor of Computer Science at Lewis & Clark College, where he has held roles including Chair of the Mathematical Sciences Department (2013–2016). He earned a Vordiplom from the University of Karlsruhe (1992), an M.S. from Southern Oregon University (1994), and a Ph.D. from the University of Oregon (1999). His research focuses on parallel/distributed systems, cybersecurity, cloud computing, and high-performance computing. Supported by NSF, W. M. Keck, and John S. Rogers Program grants, he has collaborated with Intel, Sandia National Laboratories, and German institutions. Mache has received the Guanajuato Award and a Konrad-Adenauer-Stiftung scholarship. He is a proponent of hands-on cybersecurity education, leading initiatives like EDURange and LIBRE-ary. His work emphasizes student success through machine learning, log analysis, and scalable frameworks. Research Interests: Parallel and Distributed Systems Cybersecurity (including cloud, network security, and pedagogy) High-Performance Computing Educational Technology and Assessment Grants & Collaborations: NSF-funded research on cybersecurity education and parallel computing W. M. Keck Foundation support for interdisciplinary projects Industry partnerships with Intel and Sandia National Labs Awards: Guanajuato Award (Southern Oregon University) Konrad-Adenauer-Stiftung Scholarship Projects: EDURange: Cybersecurity competition platform LIBRE-ary: Open-source digital archiving system

Aida Khajaviradمشاهده پروفایل

استادیار

• Mixed Integer Nonlinear Optimization
• Nonconvex Optimization
• Algorithm Development
• +۳ مورد دیگر

Aida Khajavirad is an Assistant Professor in the Department of Industrial and Systems Engineering at Lehigh University. Her research focuses on advancing Mixed-Integer Nonlinear Optimization (MINLP) at theoretical, algorithmic, and software levels, integrating convex analysis, integer programming, and constraint programming. She has recently expanded her work to optimization algorithms for data science and machine learning applications. Education: Ph.D. in Mechanical Engineering from Carnegie Mellon University (2012). Research Interests : Mixed Integer Nonlinear Optimization Nonconvex Optimization Algorithm Development Convex Analysis Combinatorial Optimization Her work emphasizes bridging theoretical foundations with practical algorithm design for real-world challenges. Awards : 2023 INFORMS Computing Society Prize This prestigious award recognizes her contributions to optimization theory and applications. Grants & Funding : Air Force Office of Scientific Research ($1M award, 2023) This funding supports her research on advanced optimization algorithms. Labs and Affiliations: Based in the Harold S. Mohler Laboratory, she leads interdisciplinary efforts in optimization and data science.

• Cardiovascular Engineering
• Biomechanics
• Congenital Heart Disease
• +۳ مورد دیگر

Prof. Dr. Kerem Pekkan serves as a Professor in the Department of Mechanical Engineering at Koç University's College of Engineering, where he leads groundbreaking research at the intersection of cardiovascular engineering and biomechanics. His exceptional contributions to science were recognized with the prestigious METU Parlar Foundation 2020 Science Award, highlighting his impact on advancing pediatric cardiovascular solutions. His research spans cardiovascular engineering, biomechanics, congenital heart disease, pediatric cardiology, and AI-driven medical imaging. Pekkan focuses on developing patient-specific computational models and medical devices for congenital heart defects, particularly Tetralogy of Fallot and Fontan circulation. His work integrates advanced MRI techniques, fluid-structure interaction modeling, and machine learning to optimize surgical outcomes for pediatric patients. Analysis of his 15 most recent publications (2023-2025) reveals a dominant trend toward AI-enhanced cardiovascular diagnostics and device innovation. Key themes include machine learning applications in cardiac tissue characterization, novel valve designs for neonatal reconstruction, and hemodynamic optimization of Fontan procedures using 4D flow MRI. His research consistently bridges engineering principles with clinical cardiology to address unmet needs in pediatric cardiovascular care. Scientific Awards: METU Parlar Foundation 2020 Science Award As a core faculty member in Koç University's Mechanical Engineering department, Pekkan actively supervises graduate students through numerous Master's and PhD thesis projects focused on cardiovascular biomechanics. His research is supported by competitive grants enabling advanced in-vitro testing facilities and computational resources. Current projects include AI-based clinical decision tools and genetically modified bioprosthetic valves. He directs a specialized cardiovascular fluid mechanics laboratory equipped for particle image velocimetry, 3D tissue mapping, and patient-specific phantom modeling. The team collaborates closely with medical institutions to translate engineering innovations into clinical practice, with ongoing work on self-powered ventricular assist devices and personalized surgical planning systems.

• Probability Theory
• Functional Analysis
• Geometry
• +۴ مورد دیگر

Rohan Sarkar is an Assistant Research Professor (postdoc) in the Mathematics Department at the University of Connecticut. His research focuses on Probability Theory, Functional Analysis, and Geometry, with emphasis on spectral theory of non-self-adjoint Markov semigroups and functional inequalities. He completed his Ph.D. in 2022 from Cornell University's Department of Operations Research and Information Engineering, under the supervision of Pierre Patie. He holds a Master's and Bachelor's in Statistics from the Indian Statistical Institute, Kolkata. His research interests bridge spectral theory and stochastic processes, exploring connections between functional inequalities and geometric properties of operators. Recent work includes studies on Lévy-Ornstein-Uhlenbeck semigroups, dimension-independent functional inequalities, and solutions to the van Dantzig problem linked to the Riemann hypothesis. His articles address topics ranging from spectral analysis of Markov processes to applications in PDEs and bioinformatics. Notable contributions include isospectral schemes for stochastic processes and clustering methods for large biological datasets.

• Quantum Physics
• Theoretical Physics
• Quantum Simulation
• +۴ مورد دیگر

Prof. Dr. Hendrik Weimer is a Group Leader at the Institute of Theoretical Physics within the Faculty of Mathematics and Physics at Leibniz University Hannover. His research focuses on quantum simulation, entanglement, and topological quantum phenomena. Position: Professor Institution: Leibniz University Hannover Department: Institute of Theoretical Physics His work explores quantum phase transitions , multipartite entanglement , and topological order in driven-dissipative systems. Recent studies emphasize error correction for quantum simulations and dissipative state preparation using Rydberg atoms. Key trends in his publications include quantum computing , topological materials , and non-equilibrium quantum dynamics . His research often bridges quantum information theory with condensed matter physics .

Robert Crittendenمشاهده پروفایل

استاد

• Cosmology
• Cosmic Microwave Background
• Large Scale Structure
• +۳ مورد دیگر

Robert Crittenden is a Professor of Cosmology at the University of Portsmouth's Institute of Cosmology and Gravitation (ICG), part of the Faculty of Technology. He holds additional roles as Faculty Director of Postgraduate Research and PhD Supervisor. His academic journey includes a PhD from the University of Pennsylvania (1993) under Paul Steinhardt, followed by postdoctoral positions at Princeton University and the Canadian Institute for Theoretical Astrophysics (CITA). He joined the ICG in 2002 as a Reader in Cosmology and was promoted to Professor in 2014. Affiliations: Institute of Cosmology and Gravitation, University of Portsmouth. Education: B.S., University of Maryland; Ph.D., University of Pennsylvania (1993). Research Interests: Crittenden's work focuses on understanding cosmic structure formation and evolution through observations of the cosmic microwave background (CMB), galaxy distribution, and weak gravitational lensing. He is renowned for pioneering studies on the integrated Sachs-Wolfe effect linking galaxies and CMB anisotropies, providing independent evidence for dark energy. His research spans cosmology, CMB physics, large-scale structure, dark energy, early universe phenomena, and magnetic fields in the cosmos. Publications: His recent work explores dark energy dynamics using DESI and eBOSS data, gravitational lensing effects, and relativistic cosmological simulations. Key themes include galaxy clustering, BAO analysis, and cosmological constraints from multiwavelength surveys. Grants & Advising: Supervised over 15 PhD theses, reflecting his role in training early-career cosmologists. His research is supported by grants focusing on observational cosmology and theoretical frameworks for dark energy. Labs/Teams: Active in the ICG's dark energy and gravitational lensing research groups, contributing to international collaborations like the Dark Energy Survey and DESI projects.