جست‌وجوی استاد و پژوهشگر

Jon D. Elhaiمشاهده پروفایل

استاد

• Cyberpsychology
• Internet Addictions
• Social Media Use
• +۳ مورد دیگر

Jon D. Elhai is a Distinguished University Professor in the Department of Psychology at the University of Toledo, with a joint appointment in Neurosciences and Psychiatry. His research focuses on cyberpsychology, internet addictions, and problematic smartphone/social media use. He previously studied PTSD and trauma but now emphasizes technology's psychological impacts. Dr. Elhai holds a Ph.D. in Clinical Psychology (2000) from Nova Southeastern University and completed a postdoctoral fellowship at the Medical University of South Carolina. He teaches courses on abnormal psychology, research design, and advanced data analysis. Education: Ph.D., Clinical Psychology, Nova Southeastern University, 2000 Postdoctoral Fellowship, PTSD Assessment and Treatment, Medical University of South Carolina, 2002 Research Interests: Cyberpsychology, internet addiction, fear of missing out (FOMO), digital mental health, and behavioral addictions. Affiliations: Anxiety and Stress Lab, University of Toledo; Elhai Psychological Consultants, LLC. Students: Advises graduate students on theses and dissertations, with a focus on technology use and mental health. Notable advisees include Elyse Hutcheson, Rachel Bond, and Caleb Hallauer. Collaborations: Works with global researchers including Ahmad Alghraibeh (King Saud University), Cherie Armour (Queen’s University Belfast), and Christian Montag (University of Macau). Teaching: Courses include abnormal psychology, psychological assessment, and R programming for data analysis. Dr. Elhai’s 400+ publications span cyberpsychology and PTSD research. He occasionally serves as a forensic expert witness in legal cases involving PTSD diagnoses. His work appears in journals like Journal of Affective Disorders and Emerging Trends in Drugs, Addictions, and Health . Personal interests include Mandarin language learning, travel (e.g., China, Europe), and collecting mechanical watches.

John Kouniosمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Insight and Creativity
• Problem Solving
• +۱ مورد دیگر

Dr. John Kounios is Professor of Psychology at Drexel University and author of the bestselling book The Eureka Factor: Aha Moments, Creative Insight, and the Brain . A Fellow of the Association for Psychological Science and Psychonomic Society, he researches the cognitive neuroscience of insight, creativity, and problem solving. Research Focus: Kounios investigates neural predictors of insight solutions, cognitive differences between analytic and insight problem solving, and reward mechanisms in creative breakthroughs. His work identifies pre-problem neural activity patterns that predict solution approaches. Key Discoveries: Demonstrated that insight solutions are more likely correct than analytic solutions; identified neural precursors to 'aha' moments; revealed reward system activation during insight; showed positive mood facilitates insight while negative mood promotes analytical thinking. Publications: Recent work examines EEG predictors of problem-solving outcomes, flow states in creativity, individual differences in insight phenomenology, and brain-age estimation methods. Research featured in BBC documentaries, The New York Times, and Chicago's Museum of Science and Industry.

• Artificial Intelligence
• Computer Vision
• Digital Agriculture
• +۳ مورد دیگر

Ferdous Sohel is a Professor of Information Technology at Murdoch University and inaugural lead of the Agricultural Technologies program. His research spans AI, computer vision, and digital agriculture, with applications in medical imaging and environmental monitoring. He received the Mollie Holman Doctoral Medal and Vice Chancellor's Early Career Research Award. Research Impact: Developed innovative AI models for aquaculture oxygen prediction, 3D object tracking, quantum neural networks, and prohibited item detection. His work advances precision agriculture through hyperspectral classification frameworks and irrigation decision systems. Professional Service: Associate Editor for IEEE Transactions on Multimedia and senior IEEE member. Current projects include adversarial robustness for LiDAR systems and lightweight dormitory security networks.

Paul Nuyujukianمشاهده پروفایل

استادیار

• Motor Systems Neuroscience
• Neuroengineering
• Brain-Machine Interfaces
• +۴ مورد دیگر

Paul Nuyujukian serves as an Assistant Professor of Bioengineering and Neurosurgery, with courtesy appointment in Electrical Engineering at Stanford University. He is a Faculty Scholar of the Wu Tsai Neurosciences Institute, directing the Brain Interfacing Laboratory where his team develops neural interface technologies for clinical applications in stroke and epilepsy. Education: MD, Stanford University (2014) PhD in Bioengineering, Stanford University (2012) BS, UCLA (2006) Dr. Nuyujukian's research integrates motor systems neuroscience with neuroengineering to decode brain activity during movement and recovery from injury. His laboratory pioneers brain-machine interface (BMI) platforms that translate neural signals into communication and control systems, with particular emphasis on intracranial EEG recording and real-time neural decoding. Current work focuses on developing clinically viable BMI solutions for neurological conditions through both preclinical models and human trials, advancing our understanding of neural population dynamics in health and disease. Recent publications reveal strong trends in intracranial EEG acquisition systems, seizure detection algorithms using information theory, and closed-loop BMI applications for ambulatory neuroscience. His work bridges fundamental neuroscience with clinical translation, particularly in epilepsy monitoring, chronic pain management, and neural prosthetics for paralysis. A notable emphasis exists on creating scalable, minimally invasive recording platforms that reduce clinical burden while maintaining high-fidelity neural data. Scientific Awards: No specific awards listed in provided materials As director of the Brain Interfacing Laboratory, Dr. Nuyujukian mentors students and collaborators in neural engineering research while securing grant funding for BMI development. His group maintains active collaborations with Stanford's Department of Neurosurgery and Neurology for clinical translation, with current projects including real-time decision-state decoding and personalized network mapping for pain management. The laboratory operates advanced facilities for both animal and human neural recording, emphasizing seamless integration of engineering innovation with clinical neuroscience. The Brain Interfacing Laboratory comprises multidisciplinary scientists and engineers developing next-generation neural interfaces. Current initiatives include the LiCoRICE platform for ambulatory neuroscience, seizure detection systems using compression-enabled entropy estimation, and ketamine's effects on hippocampal connectivity. The team actively participates in clinical trials for BMI applications in stroke rehabilitation and epilepsy, with strong partnerships across Stanford's medical and engineering schools to accelerate technology translation.

Pengyi Yangمشاهده پروفایل

دانشیار

• Computational Systems Biology
• Stem Cell Biology
• Bioinformatics
• +۴ مورد دیگر

Pengyi Yang is an Associate Professor and University of Sydney Robinson Fellow at the School of Mathematics & Statistics, University of Sydney. He leads the Computational Systems Biology group at the Charles Perkins Centre and holds a conjoint appointment as Unit Head of Computational Systems Biology at the Children's Medical Research Institute (CMRI). His research focuses on computational approaches to understand trans-regulatory networks in stem cells and their applications in regenerative medicine. Yang holds a Ph.D. and has been recognized with awards such as the National Stem Cell Foundation Metcalf Prize (2021). His research spans computational systems biology, machine learning for bioinformatics, and spatial/single-cell omics analysis. Key projects include modeling pluripotency transitions, developing stem cell-derived organoids, and creating computational tools for phosphoproteomics and multi-omics integration. Collaborations include international initiatives like the Laboratory of Data Discovery for Health (InnoHK). Yang advises multiple PhD students and leads grants on topics like stem cell-derived brain organoids and embryonic development modeling. His lab develops tools like Cepo, PhosR, and CiteFuse for omics data analysis. He teaches data science and molecular systems biology at the University of Sydney.

Douglas A. Nitzمشاهده پروفایل

استاد

• Spatial Cognition
• Episodic Memory
• Hippocampal Function
• +۳ مورد دیگر

Douglas A. Nitz is Professor and Chair of Cognitive Science at UC San Diego. His research program explores neural mechanisms underlying spatial navigation, memory formation, and decision-making processes across cortical and hippocampal circuits. Research Approach: Combines electrophysiological recordings, behavioral analysis, and computational modeling to decipher how distributed brain networks represent spatial information and support memory-guided behaviors. Current Focus: Neural coding principles in parietal-hippocampal networks during navigation tasks, with emphasis on path integration, landmark encoding, and route planning mechanisms.

Diogo Almeidaمشاهده پروفایل

دانشیار

• Neurolinguistics
• Language Processing
• Cognitive Science
• +۳ مورد دیگر

Diogo Almeida is an Associate Professor of Psychology and Global Network Associate Professor of Psychology at New York University Abu Dhabi. His research focuses on neurolinguistics and language processing, employing methodologies such as MEG/EEG, fMRI, and cross-linguistic studies. He holds an MSc in Cognitive Science from the Ecole des Hautes Etudes en Sciences Sociales and an PhD in Linguistics from the University of Maryland, College Park. Prior to NYU Abu Dhabi, he held positions at the University of California, Irvine, and Michigan State University. Almeida’s research explores perceptual processes underlying language understanding, including syntactic structure processing, agreement phenomena, and the neural bases of lexical access. His work integrates behavioral experiments with neuroimaging techniques to investigate how linguistic structures are represented in the brain. Key areas include sentence processing selectivity in Broca’s area, cross-linguistic differences in agreement encoding, and the role of phonological and morphological features in real-time language comprehension. His publications span topics like masked priming effects, sociolinguistic influences on speech perception, and the reliability of experimental syntax methods. He leads the Language, Mind and Brain research group at NYU Abu Dhabi, focusing on interdisciplinary approaches to language cognition. Almeida has contributed to debates on empirical rigor in syntax, advocating for robust experimental designs and large-scale data collection to validate theoretical claims.

Philbert Tsaiمشاهده پروفایل

عضو هیئت علمی

• Quantitative Biology
• Neurovascular Imaging
• Biomedical Engineering
• +۳ مورد دیگر

Philbert Tsai is an Associate Teaching Professor in the Department of Physics at the University of California, San Diego (UCSD). He has held roles as QBio Lab Coordinator/Project Scientist (2015–Present) and Associate Project Scientist (2011–2015), overseeing advanced laboratory setups and bio-imaging research projects. His work focuses on neurovascular systems, microscopy techniques, and cortical blood flow dynamics. Education: Ph.D., Physics, UC San Diego, 2004 Research Interests: Quantitative analysis of cortical microvascular networks Development of ultra-high-resolution imaging systems (e.g., STED, two-photon microscopy) Neurovascular coupling mechanisms and their impact on brain oxygen supply Biomedical engineering applications in neuroscience research Lab & Projects: QBio Lab: Advanced instrumentation including confocal microscopes, 3D printers, and wet-lab equipment Developed vectorized models of mouse brain vasculature and ultra-wide-field multiphoton imaging systems Grants & Awards: No specific awards listed in provided text Collaborations: Worked extensively with colleagues like Dr. David Kleinfeld and Dr. Berislav Zlokovic on neurovascular projects.

Svetlana Yanushkevichمشاهده پروفایل

استاد

• Biometric Technologies
• Machine Learning
• Signal Processing
• +۳ مورد دیگر

Dr. Svetlana Yanushkevich is a Professor in the Department of Electrical and Software Engineering at the Schulich School of Engineering, University of Calgary. She is also a Full Member of the Hotchkiss Brain Institute and the Mathison Centre for Mental Health Research and Education. Her research focuses on biometric technologies, decision support systems, biomedical applications, and computational intelligence. She leads the Biometric Technologies Laboratory, developing strategies for risk assessment in biometric systems and healthcare monitoring through machine reasoning and signal processing. Education : BSc/MSc in Electrical Engineering (1989), State University of Informatics and Radioelectronics, Minsk PhD in Electrical Engineering (1992), same institution Dr. Habilitated in Technical Sciences (1999), Warsaw University of Technology Research Interests : Dr. Yanushkevich’s work spans biometric system design (e.g., gait analysis, facial attributes), decision support via probabilistic models (Bayesian networks, causal inference), biomedical applications (stroke rehabilitation, wearable sensors), and computational intelligence for data science. She emphasizes fairness, bias mitigation, and trustworthiness in AI systems, particularly in healthcare and accessibility contexts. Recent Research Trends : Her recent publications address causal modeling for accessibility barriers, UAV operator cognitive workload, and medical device optimization in radiation therapy. She explores AI ethics, stress contagion in human-robot teams, and cross-spectral biometric systems. Awards & Recognition : 2024 FEIC Fellow (Engineering Institute of Canada) 2019 Research Excellence Award (Schulich School of Engineering) 2001 Senior IEEE Membership Advising & Grants : She coordinates courses like ENCM 509 (Biometric Systems Design) and ENEL 610 (Biometric Technologies). Her research is supported by grants focusing on healthcare AI, accessibility technologies, and computational epidemiology. Labs & Collaborations : Her Biometric Technologies Lab collaborates with institutions like Hokkaido University and the IEEE Computational Intelligence Society. Projects include wearable health monitoring, decision support platforms, and AI-driven epidemiological modeling.

Sharmistha Guhaمشاهده پروفایل

استادیار

• Bayesian Methods
• High-Dimensional Regression
• Causal Inference
• +۴ مورد دیگر

Sharmistha Guha is an Assistant Professor in the Department of Statistics at Texas A&M University, part of the College of Arts & Sciences. Her research focuses on Bayesian methods for analyzing complex, high-dimensional data, with applications in neuroscience, network security, and social sciences. She develops techniques for supervised network data analysis, causal inference, and data privacy preservation. Education: Ph.D. in Statistical Science (Duke University, implied by dissertation recognition). Research Interests: Bayesian high-dimensional regression, object-oriented regression, causal inference in randomized trials, probabilistic record linkage, Bayesian nonparametric mixture models, and integration of heterogeneous data types like networks and functional data. Her work addresses challenges in neuroimaging (dMRI/fMRI) and big data analytics. Recent Contributions: Her articles span Bayesian methodologies for network analysis, differential privacy in treatment effect estimation, and applications in environmental health (e.g., PM2.5 exposure studies). Notable trends include leveraging Bayesian hierarchical models for complex data structures and advancing causal inference frameworks. Awards: 2022 Blackwell-Rosenbluth Award (ISBA) 2021 Savage Award Honorable Mention 2024 NSF-DMS Grant 2413721 Grants & Advising: Secured NSF funding for heterogeneous data integration research. Mentored students like Jose Rodriguez-Acosta (NSF GRFP Fellow) and Jacob Pagel (NIH-funded CoSIBS participant). Lab/Team: Leads a research group integrating statistical method development with domain collaborations in neuroscience and network security. Active in organizing workshops and serving on panels to foster academic engagement.

Marina Vannucciمشاهده پروفایل

استاد

• Bayesian statistics
• Variable selection
• Graphical models
• +۵ مورد دیگر

Marina Vannucci is the Noah Harding Professor of Statistics at Rice University, with an adjunct appointment at the UT MD Anderson Cancer Center. She holds a Ph.D. and Laurea in Mathematics from the University of Florence, Italy. Her research focuses on Bayesian statistical methods for complex problems in genomics, neuroimaging, and engineering. She has supervised 31 Ph.D. students and 13 postdocs, published over 185 papers, and received prestigious awards including the Mitchell Prize, Zellner Medal, and Don Owen Award. She has served as Editor-in-Chief of Bayesian Analysis and co-Editor of the Journal of the American Statistical Association. Education: Ph.D. in Statistics (University of Florence, 1996), Laurea in Mathematics (University of Florence, 1992). Research Interests: Bayesian statistics, variable selection, graphical models, statistical computing, applications in genomics, neuroscience, and engineering. Awards: Includes Fellowships from ASA, IMS, AAAS, ISBA, and the 2020 Zellner Medal. Recent recognitions include the 2025 Don Owen Award for excellence in research and contributions to the statistical community. Grants/Advising: Over 30 Ph.D. students and 13 postdocs trained. Key roles include Department Chair (2014–2019) and President of the International Society for Bayesian Analysis (2018). Labs/Teams: Affiliated with Rice Neuroengineering, Ken Kennedy Institute, and the W.M. Keck Center for Interdisciplinary Bioscience Research.

• Computer Vision
• Medical Image Analysis
• Retinal Image Analysis
• +۷ مورد دیگر

Emanuele (Manuel) Trucco is a Professor of Computing and holds the NRP Chair of Computational Vision in the School of Science and Engineering at the University of Dundee. He is also an Honorary Clinical Researcher at NHS Tayside and previously served as an Adjunct Professor at the Chinese Academy of Sciences (2018–2021). His research is centered on computational vision and medical image analysis, particularly in retinal imaging and its applications in systemic disease detection. PhD, Electronic Engineering, University of Genoa (1990) MSc, Electronic Engineering, University of Genoa (1984) Manuel Trucco's research focuses on computer vision and medical image analysis , with a strong emphasis on retinal image analysis for early detection of diseases such as diabetes, cardiovascular conditions, stroke, dementia, and neurodegenerative disorders. He co-directs the VAMPIRE (Vessel Assessment and Measurement Platform for Images of the Retina) initiative, a collaborative effort between the Universities of Dundee and Edinburgh. This platform enables automated, multi-modal analysis of retinal images and has been used in biomarker studies across the UK and internationally. His work integrates deep learning , artificial intelligence , and biomedical engineering to develop non-invasive, scalable diagnostic tools. Industrial collaborations include Canon Medical, OPTOS plc, NIDEK, and Epipole plc, while institutional partners include the Royal College of Ophthalmologists and the UK Biobank Eye and Vision Consortium. Recent publications highlight a strong trend in using AI and deep learning to extract clinical insights from retinal images, including predicting cardiovascular outcomes in diabetic patients, estimating biological age, and analyzing retinal vasculature changes under physiological stress. His work bridges computer science, ophthalmology, and public health, contributing to precision medicine and health equity. His scientific contributions have been recognized through fellowships: FRSA (Fellow of the Royal Society of Arts) FIAPR (Fellow of the International Association for Pattern Recognition) Trucco has led or co-led major research projects, including a £7M NIHR grant on precision medicine for diabetes (Dundee-Chennai), a £1.1M EPSRC grant on vascular dementia biomarkers (PI), the 3M-Euro ITN "REVAMMAD", and several PhD studentships sponsored by OPTOS, NIDEK, SINAPSE, and Toshiba. He has served on the organizing and program committees of major international conferences such as MICCAI and the European Conference on Computer Vision. He is a key member of the VAMPIRE research team and the UK Biobank Eye and Vision Consortium , contributing to large-scale data analysis efforts in vision and systemic disease. His work is at the forefront of AI-driven healthcare innovation, with real-world applications in early disease detection and personalized medicine.

• Medical Education
• Primary Care
• Women in Medicine
• +۷ مورد دیگر

Rebecca Berman, MD , is a Professor in the School of Medicine at the University of California, San Francisco (UCSF) , where she serves as the Internal Medicine Residency Program Director. She plays a national leadership role in medical education and residency training reform. Education: AB in African-American Studies, Harvard College, 1999 MD, Harvard Medical School, 2005 Primary Care Internal Medicine Residency, Brigham and Women's Hospital, 2008 Diversity, Equity, and Inclusion Champion Training, UCSF, 2018 Research and Professional Interests: Dr. Berman’s work focuses on medical education , primary care innovation , diversifying the physician workforce , curricular design , negotiation skills training , women in medicine , and care for the underserved . She has pioneered initiatives to improve equity and leadership opportunities for underrepresented groups in medicine. Publication Trends: Her scholarly work spans over 15 years and includes key contributions to residency education, gender equity, health disparities (particularly in prostate cancer), and innovative teaching models. Recent publications emphasize pandemic recovery in medical training, bias reduction in residency selection, and leadership challenges for women in medicine. Scientific Awards and Honors: Inducted into the Haile T. Debas Academy of Medical Educators, UCSF (2022) Kanu Chatterjee, MD Medicine Residency Endowed Chair, UCSF (2024) Leadership and Teaching: Dr. Berman is a national leader in residency education, serving as a Councilor for the Association of Program Directors in Internal Medicine (APDIM), co-founding its Primary Care Program Director Group, and editing the widely used Primary Care Toolkit. She teaches negotiation skills to promote equity in academic medicine. She led the overhaul of UCSF’s internal medicine residency curriculum to enhance individualized training and resident well-being, especially during the pandemic. Labs and Teams: She founded the Crimson Care Collaborative (CCC) during her tenure at Harvard/Mass General, a student-faculty network providing primary care to underserved populations while offering interprofessional training. At UCSF, she leads one of the nation’s premier internal medicine residency programs, shaping the next generation of physicians.

Marie Carlénمشاهده پروفایل

استاد

• Neuroscience
• Cognitive Neuroscience
• Prefrontal Cortex
• +۱۶ مورد دیگر

Marie Carlén is a Professor of Neuronal Networks at the Department of Neuroscience, Karolinska Institutet, where she leads the Neural Circuits of Cognition research group. Her work focuses on the prefrontal cortex (PFC), a brain region central to cognitive functions such as attention, decision-making, working memory, and goal-directed behavior. She employs cutting-edge techniques including optogenetics, large-scale electrophysiology, calcium imaging, and circuit tracing in rodent models to unravel the cellular and circuit mechanisms underlying cognition and their disruption in psychiatric disorders. Her academic journey began with a Ph.D. in medicine from Karolinska Institutet in 2005, followed by postdoctoral training at MIT’s Picower Institute under Professor Li-Huei Tsai. She returned to Karolinska Institutet in 2010 and was promoted to full Professor in 2022. She is also a Docent (2017) and has held prestigious fellowships including ERC Starting Grant and Wallenberg Scholar (2019, 2024). Marie Carlén's research spans systems and cellular neuroscience, with a strong emphasis on inhibitory interneurons (especially parvalbumin-expressing cells), neural oscillations, and PFC-striatum interactions. Her recent publications reveal a consistent focus on decoding prefrontal circuit dynamics, the role of specific neuron types in cognition, and comparative brain architecture. She collaborates extensively with her partner, Konstantinos Meletis, also a KI researcher. She has been recognized with numerous scientific honors: Member, Nobel Assembly at Karolinska Institutet (2025–) Member, The Royal Swedish Academy of Sciences (2024–) Wallenberg Scholar (2024, 2019) ERC Starting Grant (2013) Wallenberg Academy Fellow (2012) NARSAD Young Investigator Awards (2010, 2008) She actively mentors students and researchers, with open applications welcomed to her lab. Her work is supported by major grants, including from the Knut and Alice Wallenberg Foundation, enabling high-risk, high-reward research in brain function and disease. Her lab investigates the functional definition of the prefrontal cortex across species, develops novel tools for neural recording, and explores circuit imbalances in conditions like autism and schizophrenia. She is a strong advocate for ethical animal research and promotes gender equality in science.

Katrin Vogtمشاهده پروفایل

پژوهشگر

• Behavioral Neuroscience
• Neural Circuits
• Sensory Processing
• +۷ مورد دیگر

Katrin Vogt is a Group Leader at the University of Konstanz and an Affiliated Scientist at the Max Planck Institute of Animal Behavior. She serves on the IMPRS Board and Faculty, focusing on behavioral neuroscience in Drosophila larvae. Her research explores how social context and internal states (e.g., hunger) modulate neural circuits and behavior, utilizing genetic tools like optogenetics, RNAi, and CRISPR. Key Research Areas: Behavioral flexibility under internal state changes Neural integration of sensory and state signals in the antennal lobe Role of serotonin (CSD neuron) in modulating output pathways Computational modeling of state-dependent circuit dynamics Notable Achievements: Discovered state-dependent olfactory valence switching (e.g., geranyl acetate shifts from aversion to attraction under food deprivation) Elucidated glutamatergic inhibition mechanisms in picky local interneurons Identified 5-HT7 receptor's role in upregulating uniglomerular projection neuron activity Recent Publications: 2025: PLoS Biology on multimodal sensory neurons 2024: Current Biology commentary on behavioral neuroscience 2023: Current Biology on multisensory memory merging Academic Affiliations: University of Konstanz (Group Leader, Department of Collective Behavior) Max Planck Institute of Animal Behavior (Affiliated Scientist) IMPRS for Organismal Biology (Faculty Member) Scientific Awards: DFG Research Fellowship (Project No. 345729665) Students & Collaborators: PhD students: Hari P. Narayanan, Akhila Mudunuri Research assistants: Nora Tutas, Julius Klein, Constantin Dyroff DAAD summer student: Élyse Zadigue-Dubé Recent graduates: Amelie Edmaier (BSc 2023), Constantin Dyroff (BSc 2023)