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Mehrdad NaderiView profile

Lecturer

• Classification
• Cluster Analysis
• Finite Mixture Models
• +5 more

Mehrdad Naderi is a Lecturer in Statistics at the Department of Mathematics, Physics, and Electrical Engineering , Northumbria University . His academic journey includes a PhD in Mathematical Statistics from Shahid Bahonar University of Kerman (2017) and postdoctoral research at National Chung Hsing University (Taiwan), Ferdowsi University of Mashhad (Iran), and University of Pretoria (South Africa). Education: PhD in Mathematical Statistics, Shahid Bahonar University of Kerman (2017) His research focuses on applied statistical inference with emphasis on classification , cluster analysis , factor analysis , finite mixture models , and EM algorithm for robust estimation. He has contributed to multivariate and matrix-variate analysis, particularly in handling outliers and asymmetrical data structures. Recent work includes three-way data clustering using matrix-variate normal distributions and robust Bayesian inference for censored mixture models. His publications demonstrate expertise in distribution theory, statistical computation, and applications to financial data, environmental modeling, and astrophysics. Current collaborations span multiple institutions, focusing on heavy-tailed distributions and computational methods for complex data structures.

• Machine Learning
• Deep Learning
• Robustness in Neural Networks
• +2 more

Dr. Grigorios Chrysos is a faculty member in the Department of Electrical & Computer Engineering at the University of Wisconsin-Madison. His research focuses on reliable machine learning, emphasizing robustness to noise, out-of-distribution generalization, and theoretical understanding of neural/polynomial networks. Education: PhD in Machine Learning, Imperial College London (2020) M.Eng. in Electrical Engineering, National Technical University of Athens (2014) Key research interests include robustness in deep networks , inductive bias analysis , and polynomial network design for high-order input interactions. His work explores adversarial robustness, fair model generalization, and extrapolation properties in generative frameworks. Recent awards include the prestigious DAAD AInet Fellowship (2023), Best Reviewer Awards at NeurIPS (2022), ICLR (2022), and IMCL (2021), alongside Amazon Cloud Credits and Nvidia GPU donations (2019). Scientific Contributions: Advancing tensor methods in machine learning Developing polynomial networks for robustness Designing efficient EEG seizure analysis algorithms

Eero VuoksimaaView profile

Researcher

• Neuropsychology
• Cognitive Aging
• Neurosciences
• +4 more

Eero Vuoksimaa is a Senior Researcher at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki, with the academic title of Docent (Adjunct Professor) in Neuropsychology. He supervises doctoral candidates in the Brain & Mind and Population Health programs. His research bridges psychology, neuroscience, and health sciences, focusing on cognitive aging, brain structure, and dementia risk factors. Education: Adjunct Professor of Neuropsychology, University of Helsinki (2015) Postdoctoral training, UC San Diego (2012-2013) PhD in Psychology, University of Helsinki (2010) M.Psych, University of Helsinki (2004) Research Focus: Investigates neurocognitive aging through population studies and neuroimaging, with emphasis on dementia prediction, brain structure-behavior relationships, and genetic influences. Core methodologies include twin studies, MRI analysis, and cognitive assessment. Projects: Leads NeuroEye Insight (2024-2026) and Juselius kulut (2024-2028), and contributes to the Center of Excellence in Complex Disease Genetics and Finnish Twin Cohort studies. Research addresses clinical translation of cognitive biomarkers. Professional Activities: Regular peer reviewer for neuroscience journals ( Cerebral Cortex , Neurobiology of Aging ), conference participant, and science communicator featured in media on topics like Alzheimer's prediction and cognitive development.

Can YücesoyView profile

Professor

• Skeletal Muscle Mechanics
• Biomechanics
• Myofascial Force Transmission
• +7 more

Can Yücesoy is a Professor and the Managing Director of the Institute of Biomedical Engineering at Boğaziçi University. He received his B.Sc. and M.Sc. degrees from the Mechanical Engineering Department of Middle East Technical University in 1993 and 1997, and his Ph.D. from the University of Twente in the Netherlands in 2003. Since June 2004, he has been with Boğaziçi University, serving as the Director of the Institute since January 2016. He also directs the Biomechanics Laboratory and serves as the academic lead for Boğaziçi University in The European University of Brain and Technology - NeurotechEU. Professor Yücesoy's research focuses on skeletal muscle mechanics, myofascial force transmission, spasticity, orthopedic biomechanics, and medical imaging. His work combines finite element modeling, MRI analyses, animal experiments, histology, and intraoperative testing in patients. He has made significant contributions to understanding how muscles interact with surrounding tissues through myofascial pathways. His recent research trends show a strong emphasis on spasticity management, particularly regarding botulinum toxin treatments and their effects on muscle mechanics. He has also been developing advanced control algorithms for powered ankle prostheses using neural networks and surface electromyography. His work bridges fundamental biomechanical principles with clinical applications in movement disorders and rehabilitation. Türkiye Bilimler Akademisi, Üstün Başarılı Genç Bilim İnsanı Ödülü (TÜBA - GEBİP) 2008 Boğaziçi Üniversitesi Vakfı, Araştırmada Üstün Başarı Ödülü 2008 Best Oral Biomechanics Presentation Award at EORS 2020 Professor Yücesoy has successfully supervised numerous graduate students and postdoctoral researchers. His current research includes a TUBITAK-funded project on developing novel control algorithms for smart ankle prostheses and leadership in the NeurotechEU initiative. He teaches graduate courses in tissue biomechanics, motion biomechanics, skeletal muscle mechanics, and fundamental mechanics for biomedical engineers. His laboratory maintains active collaborations with institutions across Europe and continues to push the boundaries of biomechanical research with both theoretical and experimental approaches.

Chengsheng MaoView profile

Assistant Professor

• Data Mining
• Machine Learning
• Medical Informatics
• +5 more

Chengsheng Mao serves as a Research Assistant Professor in the Department of Preventive Medicine at Northwestern University's Feinberg School of Medicine, specializing in data mining and machine learning applications across medical informatics, computer vision, and natural language processing. His educational background includes: BS from Huazhong University of Science and Technology (2008) PhD from Lanzhou University (2016) Dr. Mao's research integrates computational methods with clinical domains including medical imaging, bioinformatics, and sepsis analysis. His work leverages big data frameworks to develop predictive models for disease progression and treatment response, with particular emphasis on translational applications in radiology, CAT scan analysis, and X-ray diagnostics. This interdisciplinary approach bridges computer science and clinical medicine to address complex healthcare challenges. Recent publications reveal a strong focus on applying tensor factorization to cancer mortality prediction, spatial transcriptomics for drug discovery, and immune signature analysis in transplantation contexts. His work demonstrates consistent innovation in adapting machine learning techniques to Alzheimer's disease treatment and SARS-CoV-2 research, highlighting cross-disciplinary impact across neuroscience, oncology, and immunology. Scientific Awards: No scientific awards mentioned in the provided text Advising and Grants: While no formal advisees are listed, Dr. Mao's active research output suggests ongoing grant-supported work through institutional affiliations. His involvement with NUCATS and the Institute for Augmented Intelligence in Medicine indicates access to translational research funding mechanisms focused on clinical data science applications. Labs and Teams: Dr. Mao contributes to the Computational & Social Sciences in Health (COMPASS) initiative and Collaborative AI in Healthcare group, while maintaining core membership in Computational Imaging and Signal Analytics in Medicine, Deep Phenotyping and Precision Therapeutics, and Medical Education in Data Science and Digital Health programs. These affiliations position him at the intersection of AI development and clinical implementation within Northwestern's medical ecosystem.

Kewei ChenView profile

Research Professor

• Biomatematics
• Biostatistics
• Neuroimaging
• +5 more

Kewei Chen is a part-time Research Professor at Arizona State University (ASU) College of Health Solutions since 2023, while concurrently holding a full Research Professor position at the University of Arizona College of Medicine-Phoenix, Department of Neurology for over 14 years, and an adjunct professorship at ASU School of Mathematical and Statistical Sciences for 30+ years. He is also a senior scientist and consultant at Banner Alzheimer’s Institute (BAI) , where he directed the Neuroimaging Research and Analysis Lab and Data Management and Statistical Core . Education: Ph.D. Biomathematics, University of California-Los Angeles (UCLA) M.Sc. Biomathematics, UCLA M.Sc. Biomathematics, Beijing Normal University, China B.Sc. Mathematics, Beijing Normal University, China Research Interests: Dr. Chen’s work focuses on developing and applying advanced methodologies in biomathematics , biostatistics , machine learning/AI , and neuroimaging . His primary applications include Alzheimer’s disease (AD) prevention and diagnostics using PET and MRI, as well as studies in diabetes , obesity , and oncology . He is a pioneer in harmonizing multi-tracer amyloid PET data and developing AI-driven cross-modality translation tools (e.g., Plasma-CycleGAN). Publications & Impact: With 831+ publications and an h-index of 109 (Google Scholar), his work has been cited over 123,190 times. Research.com ranks him among the top 7,000 scientists worldwide in Medicine (2024). Scientific Collaborations: He consults for institutions including ADMdx , PharmatrophiX , Green Valley Pharmaceutical , and international hospitals in China, South Korea, and Germany. He serves on the board of United Neuroscience Limited (Ireland). Labs & Teams: Dr. Chen has led the Neuroimaging Research and Analysis Lab at BAI and collaborates with global teams in longitudinal AD studies, including the Alzheimer’s Prevention Initiative and DIAGNOSE CTE Research Project .

Timothy BeckerView profile

Assistant Professor

• Genomics
• Deep Learning
• Generative Modeling
• +8 more

Timothy Becker serves as the John D. MacArthur Assistant Professor of Computer Science at Connecticut College, where he joined in 2023. His research focuses on transforming complex datasets into functional instruments through advanced computational techniques. His academic background includes: B.M. in Music Production from The Hartt School of Music B.S. in Computer Science from the University of Hartford Ph.D. in Computer Science and Engineering from the University of Connecticut Becker specializes in genomics applications but maintains active interdisciplinary collaborations in ecology and transportation. His core methodology integrates deep learning, generative modeling, and data visualization to develop open-source software tools. He emphasizes practical implementations for real-world data analysis and creates interactive tutorials to foster persistent student learning. His publication record from 2018-2025 reveals consistent contributions to bioinformatics and environmental data science, particularly in structural variation analysis and river connectivity modeling. Key trends include developing neural network frameworks for genomic data integration and creating visualization methods for multi-omic datasets. Becker actively seeks undergraduate research collaborators, encouraging students with domain-specific data or research questions to initiate projects. His interdisciplinary approach connects computer science with life sciences and environmental studies through numerous cross-institutional partnerships.

Heather E. WebberView profile

Assistant Professor

• Psychophysiology
• Reward Functioning
• Addiction Neuroscience
• +5 more

Dr. Heather E. Webber is an Assistant Professor at the Center for Neurobehavioral Research on Addiction (CNRA) within the Faillace Department of Psychiatry and Behavioral Sciences at McGovern Medical School, The University of Texas Health Science Center at Houston (UTHealth Houston). She earned her doctorate in psychology with a concentration in cognitive neuroscience from the University of South Florida in 2017 and joined UTHealth Houston initially as a postdoctoral research fellow, where she received the Dean's Award for Excellence in Postdoctoral Research. Dr. Webber's research focuses on the neural mechanisms of motivation, reward sensitivity, emotional functioning, trauma, and sleep as they relate to addiction. She employs human electrophysiological methods , particularly event-related potentials (ERPs), to investigate how these processes contribute to substance use disorders. Her current NIH-funded work aims to identify ERP targets for brain stimulation to develop new treatments for cocaine and other substance use disorders. Her publication record demonstrates significant contributions to the field, with over 25 peer-reviewed articles focusing on electrophysiological biomarkers in addiction, reward processing, and the neural mechanisms underlying substance use disorders. Her work frequently employs meta-analytic approaches to synthesize findings across studies. Scientific Recognition: Dean's Award for Excellence in Postdoctoral Research Award NIDA K01 Award recipient for research on event-related potential targets for brain stimulation Active research program with significant NIH funding As an early-career faculty member, Dr. Webber is enthusiastic about training the next generation of scientists and has mentored several visiting undergraduate and medical students. Her research program bridges basic cognitive neuroscience with clinical applications, aiming to translate neurophysiological findings into novel treatment approaches for substance use disorders. The Center for Neurobehavioral Research on Addiction provides a collaborative environment for her work, connecting basic science with clinical treatment development.

Nuray YozbatiranView profile

Associate Professor

• Neurorehabilitation
• Stroke Rehabilitation
• Spinal Cord Injury Rehabilitation
• +7 more

Dr. Nuray Yozbatiran is an Associate Professor for Research in the Department of Physical Medicine and Rehabilitation at McGovern Medical School, The University of Texas Health Science Center at Houston (UTHealth). She is affiliated with the Neuromodulation and Rehabilitation Laboratories at the UTHealth NeuroRecovery Research Center at TIRR Memorial Hermann, where she conducts cutting-edge research in neurorehabilitation. Dr. Yozbatiran's research focuses on developing and optimizing treatment protocols for upper-limb movement rehabilitation in individuals with stroke, spinal cord injury, and traumatic brain injury. Her work integrates various approaches including non-invasive brain stimulation techniques (transcranial direct current stimulation and transcranial magnetic stimulation), robotic exoskeletons, and exercise therapies. She also investigates the underlying neural mechanisms of recovery using advanced neuroimaging techniques such as diffusion tensor imaging and functional MRI. Her research has been supported by significant grants including a Principal Investigator role on a Mission Connect/TIRR Foundation-funded project examining combined tDCS and robotic-assisted training for spinal cord injury, and a Co-Investigator role on an NIH-National Institute of Neurological Disorders and Stroke grant focused on brain-machine interface control of therapeutic exoskeletons. Dr. Yozbatiran has published extensively in her field, with research spanning from fundamental neuroimaging of motor recovery to clinical trials of novel rehabilitation techniques. Her publication record demonstrates a consistent focus on translating basic neuroscience into practical rehabilitation applications for patients with neurological conditions. Her research methodology combines clinical assessment with advanced neurophysiological and neuroimaging techniques to understand both the behavioral outcomes and neural mechanisms underlying rehabilitation interventions. This comprehensive approach allows her to develop more targeted and effective treatment protocols for patients with neurological injuries.

• Pediatric Traumatic Brain Injury
• Neuroimaging
• Neurocognitive Outcomes
• +5 more

Talin Babikian is an Associate Clinical Professor in the Department of Psychiatry and Biobehavioral Sciences at the David Geffen School of Medicine at UCLA. With extensive expertise in pediatric traumatic brain injury (TBI) and neuroimaging, Dr. Babikian's research focuses on understanding neurocognitive outcomes, recovery trajectories, and the application of advanced neuroimaging techniques to assess brain structure and function following pediatric TBI. Dr. Babikian's research interests span multiple areas within pediatric neurotrauma, including neuroimaging techniques (particularly DTI and MRS), neurocognitive assessment following TBI, white matter integrity disruptions, long-term outcomes of pediatric concussion, and the impact of family environment on recovery. Her work frequently examines how brain injury affects developing neural systems and cognitive functioning in children and adolescents, with emphasis on translating research findings to clinical practice. Analysis of Dr. Babikian's recent publications reveals a strong focus on collaborative, large-scale research initiatives, particularly through the ENIGMA consortium. Her work increasingly addresses health disparities in concussion care, racial biases in sports-related concussion assessment, and the biopsychosocial factors influencing recovery. There's also a growing emphasis on multimodal approaches to understanding brain injury, combining neuroimaging, cognitive assessment, and clinical outcomes to develop more comprehensive models of TBI recovery. Dr. Babikian has been actively involved in significant research funding, most notably as Principal Investigator on the NIH-funded study "Neuroimaging and Recovery after Pediatric Brain Injury" (F32NS053169, 2006-2008). She is a key contributor to several major collaborative efforts including the UCLA RAPBI study, the ENIGMA Pediatric TBI working group, and the CARE4Kids study examining persistent post-concussive symptoms in adolescents. Her work has contributed substantially to our understanding of the neurobiological underpinnings of cognitive and emotional difficulties following pediatric TBI.

• Sleep Medicine
• Nutritional Neuroscience
• Cognitive Development
• +3 more

Dr. Cecilia Rosa Algarin Crespo is an Assistant Professor at the Institute of Nutrition and Food Technology (INTA), University of Chile. She holds a Physician-Surgeon degree from Javeriana University (1982) and specializes in postgraduate courses including 'Nutrients and Cognitive Functions,' 'Sleep in the Elderly,' and 'Sleep, Nutrition, and Health.' Her research integrates sleep physiology, nutritional neuroscience, and developmental health, focusing on lifelong impacts of early nutritional deficiencies. Research Focus: Dr. Algarin investigates the interplay between sleep, nutrition, and cognitive development across life stages. Key areas include effects of iron deficiency on neurodevelopment, sleep-wake patterns in obesity, and metabolic impacts of sleep disruption. Her work employs neuroimaging, hormonal assays, and longitudinal cohort studies to analyze how early-life factors influence adult health outcomes. Research Projects: She has led multiple national grants including FONDECYT projects such as 'Sleep-wake patterns in prepubescence as predictors of obesity in adolescence' (2011-2014) and 'Prevention of diabetic retinopathy through reduction of plasma AGEs' (2014-2016). Her publications emphasize translational research with clinical implications for pediatric and adolescent health. Publication Trends: Recent articles (2020-2024) demonstrate a strong focus on neurocognitive impacts of sleep/nutrition deficiencies, using advanced methodologies like fMRI and hormonal biomarkers. Longitudinal designs dominate her work, tracking outcomes from infancy to adulthood in Chilean cohorts.

• Perinatal Imaging
• Brain Development
• Neonatal MRI
• +7 more

Professor Serena Counsell is a leading researcher in perinatal imaging and early brain development at King's College London's Centre for the Developing Brain within the Faculty of Life Sciences & Medicine. She holds the Chair in Perinatal Imaging & Health and leads cutting-edge research using advanced MRI techniques to study brain development in fetuses and neonates. Professor Counsell's research expertise spans multiple critical areas: Magnetic Resonance Imaging (100% expertise according to fingerprint analysis) Brain Development (74%) Diffusion MRI (61%) Fractional Anisotropy (60%) Thalamus research (45%) Diffusion Tensor Imaging (36%) Gray Matter analysis (35%) Premature Labor studies (29%) Her recent publications demonstrate a strong focus on understanding how genetic factors, congenital conditions, and environmental influences affect early brain development. Professor Counsell's work bridges neuroscience, cardiology, and imaging technology to improve outcomes for vulnerable infants, with particular emphasis on congenital heart disease and its neurological impacts. With over 18,081 citations across 255 research outputs, Professor Counsell has received significant recognition for her contributions to perinatal neuroscience. Her research has been consistently supported by major funding bodies including the Medical Research Council, British Heart Foundation, and National Institutes of Health. As an active supervisor, Professor Counsell has guided the work of 10 students and currently leads multiple research projects examining critical questions in perinatal brain development. Her Centre for the Developing Brain serves as a hub for innovative research at the intersection of neuroscience, imaging, and perinatal medicine, contributing to United Nations Sustainable Development Goals related to good health and well-being.

• Particle Physics
• High Energy Physics
• Charmonium Physics
• +2 more

Zhang W. is a researcher at GSI Helmholtzzentrum für Schwerionenforschung GmbH in Darmstadt, Germany, actively contributing to the field of experimental particle physics through the BESIII experiment at the Beijing Electron Positron Collider. As evidenced by numerous publications from 2024-2025, they specialize in charmonium physics and heavy quark decays, working as part of large international collaborations in the field. Their research focuses on precision measurements in the charm sector, including detailed studies of charmonium states, D meson decays, and searches for exotic hadronic structures. Recent work includes investigations of rare decays, lepton flavor universality tests, and spectroscopy of charmonium and light hadron systems. The diversity of topics covered in their publications indicates broad expertise across multiple aspects of heavy flavor physics. Analysis of their recent publications shows a strong emphasis on precision measurements that test the Standard Model of particle physics and search for potential new physics effects. Their work contributes to our understanding of quantum chromodynamics in the non-perturbative regime and helps map out the spectrum of hadronic states containing charm quarks. Zhang W. collaborates extensively with researchers from institutions worldwide, as reflected in the large author lists typical of modern particle physics publications. While specific details about their academic rank or departmental affiliation are not provided in the available information, their active publication record suggests they hold a significant research position within the particle physics community.

Christoph FraenzView profile

Researcher

• Neuroimaging
• Cognitive Psychology
• Individual Differences
• +4 more

Dr. Christoph Fraenz is a researcher at the Leibniz Research Centre for Working Environment and Human Factors (IFADO) in Dortmund, Germany, where he works within the Psychology and Neurosciences department in the Neuroimaging and interindividual differences research group under Prof. Dr. Michael Nitsche. His research focuses on the neural basis of interindividual differences in cognitive functions and personality, utilizing a multimodal approach combining psychometrics, fMRI, DTI and EEG methodologies. Dr. Fraenz's work primarily investigates how variations in brain structure and function relate to individual differences in intelligence, personality traits, and cognitive abilities across the human population. Dr. Fraenz completed his academic training with a Bachelor's degree in Psychology from Westfälische Wilhelms University of Münster (2009-2012), followed by a Master's degree in Psychology from Ruhr University Bochum (2012-2015). He earned his PhD from the Department of Biopsychology at Ruhr University Bochum (2015-2019) and subsequently worked as a Research Associate there (2019-2020) before joining IFADO. His publication record demonstrates a strong focus on understanding the relationship between brain structure/function and cognitive abilities, with recent work particularly examining white matter microstructure, neurite density imaging, functional connectivity patterns, and genetic correlates of brain organization. His research often employs polygenic scoring approaches to understand how genetic factors contribute to individual differences in cognition. Dr. Fraenz has published extensively in high-impact neuroscience journals including Cerebral Cortex, Nature Communications, NeuroImage, and Human Brain Mapping, with numerous collaborative publications featuring researchers like Erhan Genç, Caroline Schlüter, and Sebastian Ocklenburg.