جست‌وجوی استاد و پژوهشگر

Jason Ernstمشاهده پروفایل

استاد

• Epigenomics
• Regulatory Genomics
• Non-coding Genome Interpretation
• +۴ مورد دیگر

Jason Ernst is a Professor of Biological Chemistry and Computational Medicine at the University of California, Los Angeles (UCLA), where he leads a computational biology lab focused on epigenomics, regulatory genomics, and non-coding genome interpretation. His work spans multiple departments and institutes including the David Geffen School of Medicine, Computer Science Department, Computational Medicine Department, Interdepartmental Bioinformatics Program, Institute for Quantitative and Computational Biosciences, Broad Stem Cell Research Center, Jonsson Comprehensive Cancer Center, and Molecular Biology Institute. Dr. Ernst received his BS in Computer Science and Mathematics from the University of Maryland, College Park (2002), his PhD in Machine Learning from Carnegie Mellon University (2008), and completed postdoctoral training in Computational Biology at MIT (2011). His research interests center on developing computational methods to analyze chromatin states, DNA methylation patterns, and regulatory elements across diverse cell types and species. His recent publications reveal a strong focus on epigenomic data integration, with particular emphasis on chromatin state annotation, cross-species methylation analysis, and the functional interpretation of non-coding genomic regions. His lab has developed influential computational frameworks like ChromHMM for chromatin-state discovery, which has been widely adopted in the field. Current research directions include investigating regulatory elements in autism, developing methods for cross-species methylation imputation, and exploring the relationship between epigenetic patterns and life-history traits across mammals. Dr. Ernst actively mentors graduate students, with recent PhD defenses including work on autism genomics. His lab collaborates extensively across UCLA and with researchers worldwide, particularly in the fields of epigenetics, computational genomics, and disease mechanisms. His research is supported by multiple NIH grants and institutional resources, enabling the development of cutting-edge computational approaches to analyze large-scale genomic datasets. Dr. Ernst's lab maintains strong connections with both computational and experimental research groups, facilitating the translation of computational findings into biological insights.

Jonathan Frederic Rest Flintمشاهده پروفایل

استاد

• Genetics
• Genomics
• Psychiatry
• +۵ مورد دیگر

Jonathan Frederic Rest Flint is a Professor-in-Residence at the University of California Los Angeles (UCLA) in both the Department of Psychiatry and Biobehavioral Sciences and the Department of Human Genetics. He holds the Billy and Audrey Wilder Endowed Chair in Psychiatry and Neuroscience . His research bridges genetics, psychiatry, and computational biology, focusing on the genetic architecture of mental health disorders, particularly major depressive disorder (MDD), and innovative methodologies for depression detection via speech analysis. Flint has pioneered genetic association studies of MDD, exploring links between voice pitch and depression, and leveraged deep learning for phenotypic subtyping in biobank data. His work on speaker disentanglement addresses privacy-preserving depression detection, while studies on epigenetic stratification refine biomarkers in minoritized populations. He also investigates complementation testing to identify genes influencing fear-related behavior and dominance in mammalian gene expression. Recent publications highlight his leadership in integrating genomic and behavioral data , including smartphone-based mood prediction and SARS-CoV-2 epidemiology. His scientific awards include the Wilder Endowed Chair, recognizing his contributions to psychiatric genetics and neuroscience. Flint’s work emphasizes translational applications, combining rodent models and human studies to unravel the molecular underpinnings of mental health.

• Animal Nutrition
• Ruminant Physiology
• Microbiology
• +۴ مورد دیگر

Todd Callaway is an Adjunct Professor in the Department of Poultry Science at the University of Georgia’s College of Agricultural & Environmental Sciences. His research focuses on animal microbiology, probiotics, rumen fermentation, and gastrointestinal health in livestock. Contact: todd.callaway@uga.edu (706-542-0962). Research interests include optimizing animal nutrition through microbiome modulation, evaluating forage quality impacts on rumen function, and developing antibiotic alternatives for livestock. His work addresses both production efficiency and environmental sustainability in agriculture. Recent publications explore topics such as tannin effects on equine digestion, biofilm inhibition in poultry pathogens, and the role of Amla supplementation in dairy cow rumen health. He also investigates One Health aspects of climate impacts on foodborne pathogens and neurorecovery mechanisms in porcine TBI models. Awards: Not explicitly mentioned in available texts. Grant/Advising: No specific grants or advisees listed. Collaborations likely involve interdisciplinary teams across microbiology, animal nutrition, and veterinary medicine. Labs/Teams: Engaged with research groups studying rumen microbiology, probiotic development, and animal health solutions at UGA’s College of Agricultural & Environmental Sciences.

Aaron S.W. Wongمشاهده پروفایل

مدرس پاره‌وقت

• Computer Science
• Artificial Intelligence
• Robotics
• +۱۶ مورد دیگر

Dr Aaron Wong is an Honorary Lecturer at the School of Psychology , University of Newcastle , with dual affiliations in Computer Science and Software Engineering . His career spans interdisciplinary research in robotics, cognitive neuroscience, and neuroimaging, supported by roles in the Functional Neuroimaging Laboratory and Priority Research Centre for Stroke and Brain Injury . Education: PhD in Computer Science, University of Newcastle Bachelor of Engineering (Computer Engineering) with Honours Bachelor of Computer Science Research Focus: Dr Wong's work bridges machine learning , humanoid emotion modeling , and multimodal neuroimaging (MRI/EEG). Key projects include developing brain-computer interfaces , acoustic localization systems for rescue robots, and semi-supervised manifold alignment techniques. Publication Trends: Recent articles emphasize theta oscillations in cognitive control , EEG-MRI joint modeling , and deep learning for speech emotion recognition . Collaborative themes span neurodevelopmental studies , stroke research , and urban robotics . Scientific Awards: 2008 RoboCup SPL World Champion 2011 RoboCup Australian Open Champion 2014 Global Leader of Innovation (UON) 2011 Best Student Paper (ANZAScA) Supervision & Grants: Served as co-supervisor for two PhD students. Secured $23,775 in grants including a 2018 Hunter Medical Research Institute award for EEG-MRI predictive modeling and 2016 Keats Endowment funding for cognitive flexibility research . Labs & Teams: Central to the Functional Neuroimaging Laboratory and PRC Stroke and Brain Injury , with global RoboCup collaborations and contributions to the Age-ility Project data repository.

Sarah Londonمشاهده پروفایل

دانشیار

• Neuroscience
• Neural Plasticity
• Learning and Memory
• +۲ مورد دیگر

Sarah London is an Associate Professor at the University of Chicago's Department of Psychology. She received a BA in Biology and Psychology from Middlebury College and a PhD in Neuroscience from UCLA, followed by postdoctoral research at University of Illinois Urbana-Champaign. Her research examines neural mechanisms of developmental learning using zebra finch songbirds as models. Key interests include experience-dependent neural plasticity, sensitive periods in development, and molecular/genomic correlates of behavior, with implications for human speech acquisition and neurodevelopmental disorders. Publications focus on autism spectrum disorder, Down syndrome neurodevelopment, advanced MRI methodologies, and computational neuroimaging approaches. Recent work investigates white matter development, functional connectivity patterns, and early behavioral biomarkers in neurodevelopmental conditions. Leads the London Lab studying neurogenomics of learning potential and critical period mechanisms.

Monica Rosenbergمشاهده پروفایل

دانشیار

• Cognitive Neuroscience
• Attention Mechanisms
• Neuroimaging
• +۳ مورد دیگر

Monica Rosenberg is an Associate Professor in the Department of Psychology at The University of Chicago, affiliated with the Committees on Computational Neuroscience and Neurobiology and the Institute for Mind and Biology. Her research focuses on attention mechanisms, brain activity patterns, and neuroimaging techniques. She holds a PhD and postdoctoral training from Yale University's Department of Psychology, following an undergraduate degree in cognitive neuroscience from Brown University. Her work integrates behavioral studies, neuroimaging, and machine learning to explore how attention fluctuates over time and interacts with cognitive processes. Notably, she developed models predicting attention and cognition from resting-state MRI data, revealing insights into individual differences in focus and memory. Rosenberg's research also addresses neurocognitive maturation in adolescence and the impact of urban environments on cognitive performance. Her lab, the Cognition, Attention, and Brain Lab, advances methodologies like functional connectome fingerprinting and connectome-based predictive modeling. These tools enable personalized insights into brain behavior relationships, with applications in clinical settings and neurodevelopmental studies. Rosenberg's contributions bridge computational neuroscience and psychological theory, emphasizing predictive modeling and translational research.

Steven Piantadosiمشاهده پروفایل

استادیار

• Cognitive Psychology
• Computational Linguistics
• Numerical Cognition
• +۴ مورد دیگر

Steven Piantadosi is an Assistant Professor of Psychology at the University of California, Berkeley. His research integrates formal computational methods and behavioral experiments to investigate how humans learn language, form conceptual systems, and process numerical/mathematical information. He holds a PhD in Psychology from MIT and is affiliated with the Department of Psychology, contributing to interdisciplinary research on cognition and culture. His academic journey includes a focus on the intersection of cognitive science, linguistics, and computational modeling. Key research areas include the cultural evolution of numerical systems, the cognitive mechanisms underlying language acquisition, and the neural basis of conceptual representation. Dr. Piantadosi's work often explores how computational principles shape human learning, bridging theoretical and empirical approaches. Recent studies highlight themes such as cross-cultural mathematical cognition, the role of vector semantics in the brain, and the dissociation between deductive/inductive reasoning processes. His research emphasizes the importance of cultural context in shaping cognitive abilities, as seen in studies of indigenous Amazonian groups and comparisons across species. While no specific advising details are provided, his work likely involves collaborations with graduate students and postdoctoral researchers in computational psychology and neuroscience. Notable contributions include challenging traditional nativist theories of concept formation and advancing models of symbolic learning through metaprogram search. His findings have implications for education, artificial intelligence, and our understanding of human uniqueness in cognitive capacity.

Robert Kassمشاهده پروفایل

استاد

• Computational Neuroscience
• Bayesian Inference
• Graphical Models
• +۷ مورد دیگر

Robert Kass is the Maurice Falk University Professor of Statistics and Computational Neuroscience at Carnegie Mellon University, with affiliations in the Department of Statistics & Data Science, Machine Learning Department, and Neuroscience Institute. He has served as Department Head of Statistics for 9 years and held leadership roles in academic societies. Ph.D. in Statistics (University of Chicago, 1980) B.A. in Mathematics (Antioch College) Postdoctoral training at Princeton University His research bridges statistics and neuroscience, focusing on: Statistical methods for neural data analysis Bayesian inference and graphical models Point process modeling of spike trains High-dimensional and time-series analysis Computational neuroscience education Recent publications span computational neuroscience, emphasizing phase coupling analysis, latent variable modeling, and cross-population dynamics, with methodological innovations in neural data interpretation. As founding Editor-in-Chief of Bayesian Analysis and Executive Editor of Statistical Science , he shaped academic discourse in statistics. Key scientific recognitions: Outstanding Statistical Application Award (ASA) Distinguished Achievement Award (COPSS) National Academy of Sciences member (2023) He co-authored the influential textbook Analysis of Neural Data and developed international workshops like Statistical Analysis of Neuronal Data (2002-2017), advancing neuroscience methodology globally.

• Psychology
• Adolescent Mental Health
• Social Psychology
• +۳ مورد دیگر

Kirsten Thomas is a Researcher in the Department of Psychology at the University of Cambridge . Her scholarly activities focus on adolescent psychological responses to social isolation and digital media impacts on mental health . The department's research structure includes specialized units like the Adaptive Brain Lab , Auditory Perception Group , and Cambridge Social Decision-Making Lab that likely inform her work. Current research trajectory examines social isolation's neurobehavioral effects through human studies and neuroscience frameworks Key publication themes include adolescent reward processing , internalizing disorders , and social media interaction patterns

Hwamee Ohمشاهده پروفایل

دانشیار

• Aging
• Alzheimer's Disease
• Cognition
• +۸ مورد دیگر

Hwamee Oh is an Associate Professor at Brown University with primary appointment in the Department of Psychiatry and Human Behavior and secondary appointment in Cognitive and Psychological Sciences . She is affiliated with the Carney Institute for Brain Science and serves as Director of Imaging Research at Butler Hospital's Memory and Aging Program . Her career spans roles at Columbia University and SUNY-Stony Brook. PhD in Biopsychology from SUNY-Stony Brook (2009) Postdoctoral work at UC-Berkeley's Helen Wills Neuroscience Institute (2009-2014) Dr. Oh's research investigates cognitive and neural changes in normal aging and Alzheimer's disease using multimodal neuroimaging (PET, MRI). Her work examines amyloid-beta, tau pathology, and functional connectivity as early biomarkers for dementia risk. Key themes include individual differences in brain-cognition relationships and cerebrovascular-Alzheimer's interactions . Recent publications span tau PET quantification , genetic Alzheimer's subtypes , and personality-neurodegeneration links . She leads NIH-funded projects on novel cognitive biomarkers and tau tracer harmonization , with coauthor networks spanning neurology , neuropsychology , and computational neuroscience . Scientific Awards include: The de Leon Prize in Neuroimaging (2014) NIH Early Career Reviewer Program (2016) Multiple Alzheimer’s Association Travel Scholarships Dr. Oh mentors trainees through Brown's Computational Psychiatry T32 Program and contributes to neuroimaging harmonization initiatives. Her work bridges academic research and clinical translation in neurodegenerative disease.

• Organizational Psychology
• Gerontology
• Workplace Health and Well-being
• +۴ مورد دیگر

Dr. Vanessa Loh is a Lecturer in the Discipline of Work and Organisational Studies at the University of Sydney Business School. She holds a PhD in Psychology from the University of Sydney, with postdoctoral research roles at the School of Psychology, Ageing, Work and Health Research Unit (Faculty of Health Sciences), and Macquarie University. Her research focuses on the intersection of individual differences, aging populations, and workplace dynamics, particularly in areas like retirement transition, health determinants, and age-inclusive HR practices. Dr. Loh’s academic background includes multidisciplinary work spanning organizational psychology, social gerontology, and cognitive psychology. She has contributed to studies on cognitive training efficacy, caregiver health impacts, and the role of life history in shaping later-life well-being. She teaches courses such as BUSS2000 Leading and Influencing in Business and WORK3205 Organisational Communication. Her research outputs emphasize themes like retirement pathways, age-inclusive workplace design, and the psychological factors influencing learning and health outcomes. Collaborative projects include work with the ARC Centre of Excellence in Population Ageing Research (CEPAR) and the 45 and Up Study. Dr. Loh’s contributions bridge academic insights with practical applications in workforce management and aging policy.

Alexis Hillمشاهده پروفایل

استادیار

• Neurobiology
• Molecular Genetics
• Developmental Biology
• +۳ مورد دیگر

Alexis Hill is an Assistant Professor and Neuroscience Program Director at Barnard College, Department of Neuroscience & Behavior. She also maintains an affiliation with the College of the Holy Cross, where she contributed to academic roles. Her research focuses on molecular mechanisms of neuronal activity and behavior using Drosophila melanogaster, with applications to human neurological diseases. She oversees the Hill Lab, which investigates gene-neurotransmission interactions and developmental processes. Education: Ph.D., Columbia University. Email contacts: ahill@barnard.edu (primary) and ahill@holycross.edu. Research interests include neurobiology, molecular genetics, and developmental biology. Students advised include Brendan Kelly (Holy Cross ’19) and Emily Hensley (Class of 2022, lab artwork contributor). Her research spans neurophysiological mechanisms in Drosophila, opioid research historiography, and STEM education innovation. Articles highlight ion channel roles in stress responses, synaptic transmission, and neurogenesis’s impact on mental health. Lab collaborations involve Barnard students and interdisciplinary approaches to neuroscience. No scientific awards explicitly noted, but contributions to neurobiology and education are notable.

Richard Schmidtمشاهده پروفایل

استاد

• Cognitive Science
• Interpersonal Coordination
• Interlimb Coordination
• +۶ مورد دیگر

Richard C. Schmidt is a Distinguished Professor of Liberal Arts in the Psychology Department Neuroscience at the College of the Holy Cross. He holds a Ph.D. from the University of Connecticut and specializes in the dynamics of interpersonal coordination, focusing on how bodily movements underpin social interactions. His research explores synchronization in collisions, sports, and conversations, with applications to autism and schizophrenia. He also develops computational models for social robotics to enhance human-robot interaction. Education: Ph.D. in Psychology, University of Connecticut Research Interests: Dr. Schmidt investigates unintentional synchronization in social interactions, dynamical systems theory, and embodied cognition. He examines how motor coordination breaks down in autism and schizophrenia, and how these insights can inform therapeutic interventions. His work bridges cognitive science, robotics, and clinical psychology to create socially intelligent agents. Article Trends: Recent studies focus on human-robot interaction, EEG biomarkers for autism, and attentional load during coordination. Key themes include social synchrony in mental disorders, motor dynamics in joint actions, and low-cost motion tracking systems for research. Awards: None explicitly listed in provided materials. Advising & Grants: No specific grant details or advisee names provided. His lab collaborates internationally on projects involving social robotics and neurodevelopmental disorders. Labs/Teams: Engages in interdisciplinary teams combining psychology, neuroscience, and engineering to study human movement and social interaction dynamics.

Yih-Choung Yuمشاهده پروفایل

دانشیار

• Bioengineering
• Control Systems
• Signal Processing
• +۵ مورد دیگر

Yih-Choung Yu is an Associate Professor and Acting Department Head of Electrical and Computer Engineering at Lafayette College. He holds a Ph.D. in Electrical Engineering from the University of Pittsburgh, an M.S. from SUNY Binghamton, and a B.S. from Chinese Culture University. His research focuses on interdisciplinary applications of control systems in bioengineering, including cardiovascular modeling, brain-computer interfaces (BCI), and medical device development. He has pioneered work in dyslexia classification using machine learning and BCI-based robotic navigation. Dr. Yu’s teaching philosophy emphasizes mentorship and student-driven projects, reflecting his third-generation teaching heritage. Notable honors include the B. Vincent Viscomi Engineering Prize for mentoring excellence. Education: Ph.D., Electrical Engineering, University of Pittsburgh M.S., Electrical Engineering, SUNY Binghamton B.S., Electrical Engineering, Chinese Culture University His work bridges electrical engineering with healthcare, addressing challenges in cardiac function monitoring, assistive robotics, and neurodevelopmental diagnostics. Recent projects include developing affordable BCI systems for robotic navigation and non-invasive cardiac monitoring algorithms. Dr. Yu collaborates with Easton Area High School to promote engineering education and mentors students in Lafayette’s robotics initiatives. Publications highlight innovations in cardiovascular modeling (e.g., rotary blood pump interactions), BCI applications (quadcopter control, dyslexia classification), and biomedical signal processing. His research trends emphasize interdisciplinary problem-solving, leveraging control theory and machine learning to advance healthcare technologies. Awards: B. Vincent Viscomi Engineering Prize for Excellence in Mentoring and Teaching Dr. Yu’s advising style emphasizes building student confidence and fostering creativity, with many projects arising from independent studies and collaborations. Grants and funding support his work in assistive technology and bioengineering. He leads Lafayette’s efforts in regional STEM outreach, connecting undergraduates with high school students through robotics teams and educational partnerships. Active in Lafayette’s Engineering Division, he oversees facilities and curriculum development, maintaining ABET accreditation. His lab focuses on cardiovascular system modeling, BCI development, and educational robotics, with ongoing projects in dyslexia biomarkers and low-cost medical devices.

Alessandro Maria Selvitellaمشاهده پروفایل

استادیار

• Machine Learning Applications to Biology and Medicine
• Mathematical Foundations of Machine Learning
• Statistics on Manifolds
• +۴ مورد دیگر

Alessandro Maria Selvitella is an Assistant Professor of Data Science and Applied Statistics at Purdue University, Fort Wayne. He holds a Ph.D. from SISSA (2010) and has held academic roles at institutions including McMaster University and the University of Ottawa. His research spans machine learning applications in biology/medicine, mathematical foundations of ML, statistics on manifolds, PDEs, and computational epidemiology.\n Key affiliations include leadership roles in the Thematic Program on Data Science and COVID-19, organizing workshops like the Workshop in Mathematical and Computational Biology (2021) and the Indiana Digital Crossroads grant initiative. He has received awards such as the Sigma-Xi Researcher of the Year Award (2020) and grants including the Lilly Endowment-funded Indiana Digital Crossroads project.\n His teaching spans courses like STAT 512 (Applied Regression), STAT 520 (Time Series), and interdisciplinary courses on data science and epidemiology. Research collaborations include work with Kathleen Foster on lizard biomechanics and Anolis locomotion studies. Notable publications address fMRI alignment, Simpson's paradox in quantum mechanics, and socio-economic impacts of pandemics.\n Labs/teams include leadership in the Data Science Week initiatives (2019-2020) and collaborations with institutions like the Mathematical Biosciences Institute (MBI). His work bridges theoretical mathematics with applied data science domains like public health and neuroimaging.