جستجوی استاد راهنمای دانشگاهی

Keith Alexander Sharkeyمشاهده پروفایل

استاد

• Enteric nervous system
• Gut-brain axis
• Endocannabinoid system
• +۳ مورد دیگر

Dr. Keith Alexander Sharkey is a Professor in the Department of Physiology and Pharmacology at the Cumming School of Medicine, University of Calgary. He is also a Full Member of both the Hotchkiss Brain Institute and The Calvin, Phoebe and Joan Snyder Institute for Chronic Diseases. Dr. Sharkey has been at the University of Calgary since his appointment as Assistant Professor in 1990, dedicating his career to understanding the neural control of the gastrointestinal tract. From 2005-2021, he held the Crohn's and Colitis Canada Chair in Inflammatory Bowel Disease Research, demonstrating his longstanding commitment to advancing knowledge in gastrointestinal sciences. Dr. Sharkey's educational journey began with a BSc (Hons) in Nutrition from the University of London in 1981, followed by a PhD in Physiology from the University of Liverpool in 1985. After completing postdoctoral training in Hungary, the UK, and Canada, he joined the University of Calgary faculty in 1990, where he has remained throughout his distinguished academic career. Dr. Sharkey's research program centers on understanding the physiology and pathophysiology of the neural control of the gastrointestinal tract and brain-gut interactions in health and disease. His laboratory investigates two main areas: the role of the endocannabinoid system in regulating GI motility and intestinal barrier function, and the physiology of the enteric nervous system in controlling motility and barrier function. His work employs state-of-the-art approaches including live cell imaging and molecular genetics. Recent publications show his expanding interest in connections between gut function and neurodegenerative conditions like ALS, with multiple 2024-2025 papers examining sexual dimorphism in disease processes and gut-brain axis mechanisms. Fellow, Royal Society of Canada (2024) Cumming School of Medicine's van de Sande Distinguished Achievement Award for Mentorship (2021) Distinguished Research Award, American Physiological Society (2021) Finkelstein Award for Excellence, Crohn's and Colitis Canada (2016) Fellow, Canadian Academy of Health Sciences (2015) Fellow, Canadian Association of Gastroenterology (2015) Killam Annual Professor Award, University of Calgary (2013) Dr. Sharkey has mentored numerous students throughout his career, as evidenced by his 2021 Mentorship Award. His research is supported by significant funding, including a CIHR Foundation grant exploring how enteric nerves and glia maintain intestinal homeostasis. He has also participated in university strategic initiatives focused on Brain and Mental Health (2015-2021) and Infections, Inflammations and Chronic Diseases (2015-2021), demonstrating his interdisciplinary approach. The Sharkey Lab provides a safe, inclusive, and diverse research environment that encourages open scientific exchange from diverse viewpoints. His laboratory is actively engaged in multiple collaborative projects, including investigations with UBC Okanagan on diet and probiotics targeting the gut-brain metabolic interactome, and with University of Calgary colleagues studying gut microbiota's role in ALS. Dr. Sharkey continues to advance our understanding of neural mechanisms controlling gastrointestinal function with upcoming courses scheduled for Fall 2024 and Winter 2025.

• Machine Learning
• Explainable AI
• Neural Networks
• +۳ مورد دیگر

Jonas Fischer is the head of the Explainable Machine Learning group at the Max Planck Institute for Informatics, Department of Computer Vision and Machine Learning. His research focuses on interpreting complex machine learning models, particularly in genomics and healthcare, aiming to enhance robustness and alignment with human decision-making. Prior to his role at MPI, he was a postdoctoral fellow at Harvard University's Department of Biostatistics, where he worked on interpretable models for gene regulatory systems in cancer. Education: PhD in Computer Science from Saarland University (2022), with a thesis titled More than the sum of its parts , exploring the intersection of pattern mining and deep learning. He has contributed to advancing methods in neural network pruning, federated learning, and low-dimensional embeddings (e.g., dtSNE, Mercat). His work bridges computational biology, data mining, and machine learning, with applications in DNA methylation analysis, graph-based differential networks, and biomedical informatics. Key research areas include: (1) Explainable AI and neural network interpretability, (2) Biomedical applications of machine learning (e.g., gene regulatory networks, cancer genomics), (3) Low-dimensional embeddings and visualization techniques, (4) Federated learning for privacy-preserving collaborative models, and (5) Pattern mining for error analysis in NLP and classification tasks. Publications span top venues like NeurIPS, ICLR, Bioinformatics, and Genome Biology. His group develops tools such as BONOBO for omics data integration and node2vec2rank for scalable graph analysis. He actively collaborates with biomedical researchers to address challenges in data-driven healthcare and precision medicine.

Tülay Adaliمشاهده پروفایل

استاد

• Statistical Signal Processing
• Machine Learning
• Medical Image Analysis
• +۳ مورد دیگر

Tülay Adali is a Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). She has held this position since 1992 and was named a Distinguished University Professor in 2015 for her contributions to statistical signal processing and machine learning. Currently serving as Editor-in-Chief of the IEEE Signal Processing Magazine, she has also held leadership roles in IEEE committees and conferences. Her research focuses on statistical signal processing, machine learning, and their applications in medical imaging and data fusion. Dr. Adali earned her Ph.D. in Electrical Engineering from North Carolina State University in 1992. Her work integrates foundational signal processing techniques with biomedical applications, addressing challenges in neuroimaging analysis. She leads the Machine Learning for Signal Processing laboratory, supported by grants from NSF and NIH. Her lab develops algorithms for analyzing complex signals in medical contexts, emphasizing reproducibility and interdisciplinary collaboration. Recognition includes IEEE Fellow, AIMBE Fellow, AAIA Fellow, Humboldt Research Award, and NSF CAREER Award. She has authored numerous papers on fMRI analysis, independent component analysis, and multimodal data fusion. Her editorial leadership and service to technical communities reflect her commitment to advancing signal processing and education. Education: Ph.D. in Electrical Engineering, North Carolina State University (1992) Grants: NSF, NIH-funded projects on medical imaging and signal processing Awards: SPS Meritorious Service Award, SPIE Pioneer Award

• Sexual Delinquency
• Juvenile Prostitution
• Psychopathy
• +۵ مورد دیگر

Christopher M EARLS is a Professor in the Department of Psychology at Université de Montréal's Faculty of Arts and Sciences. He specializes in forensic psychology, psychopathology, and behavioral studies with a focus on sexual delinquency and juvenile prostitution. His research explores the intersections of psychopathy, criminal behavior, and mental health comorbidities. He teaches courses including Psychopathology: Introduction across undergraduate programs in psychology, social sciences, and cognitive neuroscience. His academic contributions span over two decades, with notable work on psychopathy assessment, parenting practices in non-criminal populations, and sexual behavior conditioning. Education Affiliations: Université de Montréal (primary) Teaching Programs: Baccalauréat en psychologie, Neuroscience cognitive, Social Work programs Dr. EARLS has directed 10+ theses and mémoires since 1998, focusing on forensic psychology topics like sexual delinquency correlates and psychopathy measurement validity. His work bridges clinical psychology with sociocultural factors, particularly in marginalized populations like sex workers and juvenile offenders. Research Highlights: Clinical assessment tools comparison (paper vs. digital psychopathy scales) Gender differences in psychopathy expression Impact of childhood trauma on sexual interest development Though no formal awards are listed, his extensive publication record reflects sustained contributions to forensic and clinical psychology research.

Alexis Battleمشاهده پروفایل

دانشیار

• Genomics
• Machine Learning
• Computational Biology
• +۳ مورد دیگر

Alexis Battle is an Associate Professor at Johns Hopkins University with appointments in Biomedical Engineering , Computer Science , and Genetic Medicine (secondary). She directs the Malone Center for Engineering in Healthcare and serves as Deputy Director of the Data Science and AI Institute . Educated at Stanford University (PhD in Computer Science, 2013), Battle transitioned to academia after leadership roles at Google. Research Focus: Battle’s work bridges genomics and machine learning , emphasizing the impact of genetic variation on human health. Her lab develops tools like Watershed to predict functional effects of rare variants, aiming to enhance rare disease diagnosis. Key themes include non-coding DNA analysis , personalized genomics , and systems biology , with applications in cardiovascular disease and neurodegenerative disorders . Publications & Awards: Over 60 peer-reviewed articles in journals like Nature , Science , and Genome Biology , with recent emphasis on single-cell transcriptomics , multiomics integration , and telomere biology . Recipient of the President’s Frontier Award (2022), Microsoft Investigator Fellowship (2019), and Searle Scholar (2016). Scientific Awards: 2022 President’s Frontier Award 2019 Microsoft Investigator Fellowship 2019 Johns Hopkins Discovery Award 2017 Johns Hopkins Catalyst Award 2016 Searle Scholar Advising & Funding: Mentors 11 PhD students, 3 undergraduates, and postdoctoral fellows. Her research is funded by NIH, Searle Scholars, and institutional grants. The Battle Lab collaborates on projects like the GTEx Consortium , focusing on gene regulation and clinical genomics .

Dennis Säringمشاهده پروفایل

استاد

• Deep Learning
• Medical Image Analysis
• Artificial Intelligence
• +۵ مورد دیگر

Prof. Dr. Dennis Säring is a faculty member at the University of Applied Sciences Wedel , specifically affiliated with the School of Engineering. His academic and research activities focus on Deep Learning , Medical Image Analysis , and applications of Artificial Intelligence in healthcare and biomedical imaging. He has led seminars on Deep Learning topics and supervised student projects in Autonomous Driving at Audi's AADC 2018 competition. Research Highlights : Cardiovascular imaging, forensic age estimation via MRI, neural network-based bone segmentation, and cerebrovascular aneurysm analysis. Technical Expertise : Cardiac MRI, 3D/4D image processing, parametric mapping, and spatiotemporal data fusion. His recent publications (2018-2023) emphasize 3D MR segmentation for age assessment, CMR strain analysis in athletes, and T1/T2 mapping for myocarditis. Key collaborations include institutions like the University Medical Center Hamburg-Eppendorf and Wedler Hochschulbund, with funding for autonomous vehicle research. While no explicit scientific awards are listed, his work spans clinical cardiology, forensic radiology, and AI-driven medical diagnostics.

• Thermal Biology
• Animal Behavior
• Urban Ecology
• +۳ مورد دیگر

Dr Dominic McCafferty is a Senior Lecturer in Physiology, Ageing & Welfare at the University of Glasgow, based at the Scottish Centre for Ecology and the Natural Environment. He holds academic roles including Editor-in-Chief of the Journal of Thermal Biology and previously Ibis . His research focuses on thermal adaptation, behavioral thermoregulation, and urban wildlife ecology, particularly using thermal imaging techniques. He has a Ph.D. and BSc in Ecological Science from the University of Edinburgh (1989–1993 and 1985–1989). His work spans physiological studies in mammals, birds, and marine species, emphasizing conservation applications. Notable projects include habitat suitability modeling for urban water voles and thermal physiology studies in elephant seals. His educational background includes advanced studies in ecological science, complemented by post-doctoral research at institutions like the British Antarctic Survey (1993–1998). He has contributed to over 99 publications, advancing methodologies in non-invasive wildlife monitoring and ecological field studies. His editorial roles reflect expertise in thermal biology and avian science. McCafferty has led projects on carrion dynamics, stress physiology, and behavioral adaptations in diverse species, with a focus on applying findings to conservation challenges. Labs/Teams: Scottish Centre for Ecology and the Natural Environment (SCENE), part of the broader University of Glasgow's ecological research network. Collaborations include the Muséum National d’Histoire Naturelle in France and the National Trust for Scotland.

Elizabeth A. Simpsonمشاهده پروفایل

دانشیار

• Developmental Psychology
• Autism Spectrum Disorders
• Social Cognition
• +۷ مورد دیگر

Elizabeth A. Simpson is an Associate Professor in the Department of Psychology at the University of Miami's College of Arts and Sciences. She serves as Associate Director of the Child Division and directs the Social Cognition Laboratory, focusing on infant social and cognitive development through interdisciplinary methodologies. Education: Ph.D. in Psychology (unspecified institution) Key Research Areas: Developmental Psychology, Autism, Social Cognition, Primate Studies, Visual Attention, Infant Behavior Her research investigates individual differences in infant visual attention, social motivation, and physiological markers like salivary oxytocin. Recent studies demonstrate: Stability of attentional patterns from newborn to 14 months Sex differences in early face detection Links between oxytocin levels and social affect in infants Neurophysiological markers in newborns later diagnosed with ASD Scientific awards include the NSF CAREER grant for neonatal imitation research. She contributes to open science initiatives through the ManyBabies consortium and develops remote eye-tracking methods for broader accessibility. Current lab work explores: Parent-infant affective interactions during still-face episodes Predictive power of early attentional biases Development of pathogen avoidance behaviors Cross-species comparisons of social cognition

Kathryn Roederمشاهده پروفایل

استاد

• Statistical Genetics
• Genomics
• Biostatistics
• +۵ مورد دیگر

Kathryn Roeder is the UPMC University Professor of Statistics and Life Sciences at Carnegie Mellon University (CMU), affiliated with the Dietrich College of Humanities and Social Sciences and the Departments of Statistics & Data Science and Computational Biology. Her research focuses on developing statistical methods for genetic and genomic data, particularly in identifying autism risk genes and analyzing single-cell multi-omic data. She earned her Ph.D. in Statistics from Penn State University and has been at CMU since 1994, previously serving as Vice Provost for Faculty (2015–2019). Education: Ph.D. in Statistics, Penn State University (1988) B.S. in Wildlife Resources, University of Idaho (1982) Research Interests: Her work integrates modern statistical techniques (high-dimensional statistics, machine learning, networks) to study complex diseases like autism and schizophrenia. Recent efforts include tools for analyzing single-cell RNA-seq and proteomic data, such as UNICORN, DAWN, and SCEPTRE. Key Awards: COPSS Distinguished Achievement Award (2020) National Academy of Sciences Member (2019) COPSS Presidents’ Award (1997) AAAS Fellow (2020) Advising & Grants: She has advised over 20 Ph.D. students, many contributing to landmark studies in autism genetics. Her grants include NIH funding for projects like the Autism Sequencing Consortium. Current research teams focus on computational biology and statistical genetics. Labs & Collaborations: Her lab develops software tools (e.g., TADA, MIND) and collaborates with the Autism Sequencing Consortium and iPSYCH-BROAD Consortium on large-scale genomic studies.

Susanne Weisمشاهده پروفایل

استاد پژوهش

• Neuroimaging
• Cognitive Neuroscience
• Machine Learning in Neuroscience
• +۳ مورد دیگر

Susanne Weis is a Research Professor and Group Leader of the 'Variability of the Brain' group at the Department of Brain and Behavior (INM-7), part of the Institute of Neuroscience and Medicine (INM) at Research Center Jülich GmbH. Her work focuses on understanding brain variability through advanced neuroimaging techniques and machine learning, with particular emphasis on sex differences, hormonal influences, and clinical applications in mental health. Her research interests include neuroimaging methodologies, machine learning applications in cognitive neuroscience, and the structural-functional relationships underlying brain variability. She investigates how factors like sex hormones and naturalistic stimuli (e.g., movies) affect brain connectivity and cognitive performance, aiming to improve diagnostic and predictive tools for disorders such as schizophrenia and Alzheimer’s disease. Publications highlight her contributions to developing datasets (e.g., SpEx), analyzing confound leakage in ML models, and exploring meta-analytic networks during naturalistic viewing. Her work bridges basic science and clinical impact, addressing challenges in interpreting neuroimaging data and advancing personalized medicine approaches. In her role as a group leader, Weis oversees research projects and collaborates with interdisciplinary teams. She is affiliated with the Helmholtz Association and contributes to the broader scientific community through her research in neuroimaging and computational neuroscience.

Carmen Bergomمشاهده پروفایل

دانشیار

• Radiation Oncology
• Breast Cancer
• Tumor Microenvironment
• +۵ مورد دیگر

Carmen Bergom, MD, PhD, is an Associate Professor of Radiation Oncology at Washington University School of Medicine (WashU Medicine), where she joined the faculty in 2020. She holds secondary appointments in the Division of Cancer Biology and the Siteman Cancer Center. Her research focuses on leveraging genetic models to improve radiation therapy efficacy while mitigating radiation-induced cardiotoxicity , particularly in breast cancer patients. Key areas include radiation biology , tumor microenvironment , and cardio-oncology . Recent publications highlight her work in genetic mapping of radiation sensitivity (e.g., rat chromosome 3 variants), innovative imaging techniques (e.g., integrin-targeted PET), and clinical trial design for cardiovascular risk stratification. Her laboratory has pioneered the first genetic studies of radiation-induced cardiac dysfunction. Scientific awards include the Michael Fry Research Award (2021) and recognition as a Top Doctor in America (2018, 2019). She serves as Chair of the ASTRO Science Council Scientific Review Panel and co-chair of the Clinical and Experimental Research in Radiation Oncology meeting at ESTRO. Dr. Bergom treats breast cancer patients clinically and mentors students across all levels (undergraduate to postdoctoral). Her work bridges basic research with clinical applications , aiming to develop biomarkers and therapeutic targets for radiation oncology.

Erik Willcuttمشاهده پروفایل

استاد

• Behavioral Genetics
• Psychiatric Genetics
• ADHD Etiology
• +۳ مورد دیگر

Erik Willcutt is a Professor in the Department of Psychology and Neuroscience at the University of Colorado Boulder. His research focuses on the genetic and neurobehavioral underpinnings of ADHD, learning disabilities, and developmental psychopathologies. He holds positions at the Institute for Behavioral Genetics and the Center for Neuroscience. Education: PhD in Psychology from the University of Denver (1998). Research Interests: Etiology and assessment of ADHD, reading disabilities, and developmental psychopathologies. His work integrates behavioral genetics, neuroimaging, and longitudinal twin studies to understand cognitive and psychiatric disorders. Key topics include neuroanatomical correlates of ADHD, genetic influences on dyslexia, and comorbidity between learning disabilities and psychiatric conditions. Publications highlight advanced methods like genome-wide association studies (GWAS) and phenotype harmonization (e.g., Rosetta method). His work bridges molecular genetics with clinical psychology, emphasizing translational research. Lab/Affiliations: Active in the Institute for Behavioral Genetics and collaborates with interdisciplinary teams studying neurodevelopmental disorders. Office located at Muenzinger D451B.

Priya Ramanمشاهده پروفایل

دانشیار

• Molecular mechanisms of vascular smooth muscle cell phenotypic switching
• Non-lipid causes of vascular disease in metabolic syndrome
• Mechanistic links between metabolic syndrome, vascular dysfunction, and Alzheimer’s disease
• +۳ مورد دیگر

Priya Raman, Ph.D., FCVS, is an Associate Professor of Integrative Medical Sciences at Northeast Ohio Medical University (NEOMED). She holds tenure and serves as Co-Director of the Basic and Translational Biomedicine (BTB) Graduate Program and Chair of the Kent State University-Biomedical Sciences Pharmacology Graduate Program. Her academic roles include teaching in NEOMED’s medical curriculum, focusing on pharmacology, cardiovascular systems, and clinical therapeutics. Raman’s research explores molecular mechanisms linking metabolic disorders (e.g., diabetes, metabolic syndrome) to vascular dysfunction and Alzheimer’s disease, using mouse models and cellular/molecular techniques. She has published extensively on thrombospondin-1, O-GlcNAc signaling, and atherosclerosis pathogenesis. Education: B.Pharm. and M.Pharm. (India), Ph.D. in Pharmacology (University of Louisiana at Monroe). She has over 25 years of postdoctoral and faculty experience, including roles at the Cleveland Clinic and Indiana University School of Medicine. Raman serves on editorial boards for journals like International Journal of Cardiology and Frontiers in Cardiovascular Medicine , and reviews grants for the American Heart Association and NIH. Research focus areas include: (1) Vascular smooth muscle cell phenotypic switching in metabolic diseases, (2) Non-lipid mechanisms of vascular disease in metabolic syndrome, and (3) Interactions between metabolic disorders and neurodegeneration. Her lab employs biochemical assays, mouse models (e.g., ApoE-/-, KKAy), and advanced imaging techniques to study these pathways. Notable recent work includes discovering that O-GlcNAc transferase deletion reduces atherosclerosis in hyperglycemic mice and identifying thrombospondin-1’s role in leptin-driven vascular pathology. She has also linked metabolic syndrome-induced O-GlcNAc deficits to Alzheimer’s-like cognitive impairment in aging mice. Raman is actively involved in interprofessional education and mentoring, directing graduate programs and teaching courses in pharmacology, molecular signaling, and diabetes/vascular disease. Her work bridges basic science and clinical applications, aiming to develop novel therapies for metabolic syndrome-related vascular complications.

Nathan Nunnمشاهده پروفایل

استاد

• Political Economy
• Economic History
• Economic Development
• +۴ مورد دیگر

Nathan Nunn is a Professor at the Vancouver School of Economics at the University of British Columbia. He holds a Canada Research Chair in cultural economics and is affiliated with multiple prestigious research organizations including the Canadian Institute for Advanced Research (CIFAR), the National Bureau of Economic Research (NBER), and BREAD. His office is located in the Iona Building 172 at UBC. Professor Nunn's primary research interests span political economy, economic history, economic development, cultural economics, and international trade. His work focuses on the historical and dynamic processes of economic development, particularly examining how institutions and cultures evolve across societies. He has published extensively on historical factors crucial for economic development, including distrust, gender norms, religiosity, conflict, immigration, state formation, and support for democracy. His contemporary research examines the effects of Fair Trade certification, CIA interventions during the Cold War, foreign aid, school construction, climate shocks, and trade policies, with particular emphasis on how local context influences development policy effectiveness. Nunn's recent publications reveal a strong focus on the relationship between culture, institutions, and economic outcomes. His work increasingly examines how zero-sum thinking affects economic behavior and political divides, the persistence of traditional religious beliefs in Africa, and the historical roots of contemporary economic phenomena. His publications frequently appear in top economics journals including the Quarterly Journal of Economics, Econometrica, American Economic Review, and Science. His scientific contributions have been recognized through fellowships and editorial positions, including serving as an editor at the Quarterly Journal of Economics. He has advised numerous PhD students who have gone on to faculty positions at leading universities worldwide. Professor Nunn actively disseminates his research through various media channels, including podcasts, online courses, and public lectures. His teaching includes courses on economic history, development economics, and political economy, with a particular focus on how historical perspectives inform contemporary economic issues.

Huiyan Sangمشاهده پروفایل

استاد

• Spatial Statistics
• Bayesian Nonparametrics
• Machine Learning
• +۹ مورد دیگر

Huiyan Sang is a Professor and Director of the Undergraduate Program in the Department of Statistics at Texas A&M University (College of Arts & Sciences). She earned her Ph.D. in Statistics from Duke University and a B.Sc. in Mathematics and Applied Mathematics from Peking University. Her research focuses on spatial statistics, Bayesian nonparametric methods, machine learning, computational statistics, and applications in environmental sciences, geosciences, urban planning, and biomedical research. Her interdisciplinary work integrates statistical methodologies with real-world challenges, such as analyzing extreme environmental events, optimizing urban infrastructure, and modeling complex systems like human mobility during pandemics. She has contributed to advancing spatio-temporal modeling, Gaussian processes, and Bayesian hierarchical frameworks for large datasets. Recent publications highlight innovations in nonparametric regression, spatial functional data analysis, and stochastic frontier analysis, often leveraging computational efficiency and scalability. Her work addresses critical societal issues, including the impact of community design on public health and environmental monitoring through remote-sensing data. No scientific awards are explicitly listed in the provided texts. She advises no students or grants in the current dataset but collaborates widely on interdisciplinary projects. Her research lab focuses on developing cutting-edge statistical tools with applications in engineering, public health, and environmental science.