جست‌وجوی استاد و پژوهشگر

Joseph P. Havlicekمشاهده پروفایل

استاد

• Signal Processing
• Image Processing
• Video Processing
• +۷ مورد دیگر

Dr. Joseph P. Havlicek is the Gerald Tuma Presidential Professor in the Gallogly College of Engineering at the University of Oklahoma, where he has served since 1997. He directs the OU Center for Intelligent Transportation Systems and is a full member of the OU Institute for Biomedical Engineering, Science, and Technology. His extensive career spans both academic and professional realms, with significant contributions to signal processing, image analysis, and transportation systems. His educational background includes: BS in Electrical Engineering from Virginia Tech (1986) MS in Electrical Engineering from Virginia Tech (1988) PhD in Electrical and Computer Engineering from the University of Texas at Austin (1996) Dr. Havlicek's research spans multiple domains including signal, image, and video processing; modulation domain signal processing; target tracking; medical imaging; and intelligent transportation systems. His work bridges theoretical signal processing with practical applications in healthcare and transportation. He has pioneered techniques in AM-FM signal and image modeling, uncertainty measures, and developed innovative approaches for medical image analysis and infrared target tracking. Analysis of his recent publications reveals a strong interdisciplinary trend, with significant work at the intersection of signal processing and medical imaging, particularly in bone marrow assessment and cancer treatment monitoring using PET/CT imaging. His computer vision research focuses on infrared object detection and tracking, with recent work on dual-band infrared systems improving small object detection. The publications also demonstrate his continued theoretical contributions to signal processing, particularly in modulation domain techniques and entropy-based uncertainty measures. His scientific achievements have been recognized with numerous awards: University of Oklahoma Outstanding Faculty Advisor Award (2006) University of Oklahoma College of Engineering Brandon H. Griffith Faculty Award (2003) University of Oklahoma IEEE Favorite Instructor Award (1998, 2000) Department of the Navy Award of Merit for Group Achievement (1990) University of Texas Engineering Foundation Award for Exemplary Engineering Teaching (1992) Dr. Havlicek has been exceptionally successful in securing research funding, serving as PI or co-PI on more than 100 externally funded grants and contracts totaling over $25 million. His professional service includes editorial positions with IEEE Transactions on Image Processing and IEEE Transactions on Industrial Informatics, as well as leadership roles in major conferences including ICIP and ICASSP. He has chaired both graduate and undergraduate studies committees in the ECE department. He leads the OU Center for Intelligent Transportation Systems, which develops advanced technologies for traffic management and traveler information systems. His biomedical engineering work through the OU Institute focuses on medical image analysis, particularly for cancer treatment monitoring and bone marrow assessment. His research teams regularly collaborate with medical institutions to translate signal processing techniques into clinical applications.

Alessio Toraldoمشاهده پروفایل

دانشیار

• Cognitive Neuropsychology
• Unilateral Spatial Neglect
• Cognitive Neuroscience
• +۶ مورد دیگر

Alessio Toraldo is an Associate Professor of Cognitive Neuropsychology at the Department of Brain and Behavioural Sciences, University of Pavia, Italy, where he has been teaching Cognitive Neuropsychology and Statistics since 2004. He previously served as a Lecturer at the same institution from 2004 to 2015. Dr. Toraldo earned his Academic degree in Psychology from the University of Padova in 1996 with highest honors (110/110 summa cum laude). He completed his PhD in Psychology at the University of Pavia in 2000. As part of his doctoral research, he visited the Psychology Department at the University of St Andrews in 1999. Following his PhD, he was granted a post-doctoral position at the Cognitive Neuroscience Sector of the International School for Advanced Studies (SISSA-ISAS) in Trieste from 2000 to 2004. Dr. Toraldo's primary research focuses on cognitive processing involved in visual space perception, studying both normal subjects and patients with right hemisphere lesions, particularly those with neglect and/or hemianopia. His work also investigates neglect dyslexia mechanisms, encoding of stress position in Italian polysyllabic words, humor processing, and the development of statistical methods for neuropsychological diagnosis with particular attention to Information Criteria within a Bayesian approach. His research has led to the development of standardized procedures for diagnosing unilateral neglect and analyzing dissociations in neuropsychological single-case studies. Analysis of Dr. Toraldo's publication record reveals a consistent trajectory of methodological innovation in neuropsychological assessment. His early work focused on developing refined methods for analyzing the Landmark Task and Block Design test. Over time, his research has increasingly emphasized statistical approaches to neuropsychological diagnosis, culminating in his recent 2022 work on dissociations in single-case studies. A recurring theme throughout his career is the development of standardized, quantifiable methods for assessing cognitive deficits, particularly in spatial attention and perception. His work bridges theoretical cognitive neuroscience with practical clinical applications, providing clinicians with reliable tools for diagnosis and assessment. Dr. Toraldo has supervised numerous PhD students through the University of Pavia's Doctoral Programs in Psychology, Neuroscience and Data Science. His research has been supported by various grants enabling his work on neuropsychological diagnosis, humor processing, and measurement of visual space. He has collaborated extensively with researchers across Europe and maintains active research projects investigating cognitive processing in normal subjects and patients with neurological conditions. Dr. Toraldo leads research projects within the Department of Brain and Behavioural Sciences at the University of Pavia, focusing on developing and validating neuropsychological assessment tools. His team works on multiple fronts including theoretical modeling of cognitive processes, development of statistical approaches for diagnosis, and clinical validation of assessment methods. Current projects include "NEUROPSYCHOLOGICAL DIAGNOSIS," "HUMOUR," and "MEASUREMENT OF VISUAL SPACE," each investigating specific aspects of cognitive processing and their neural underpinnings.

• Oral Medicine
• Dentistry
• Biomedical Engineering
• +۶ مورد دیگر

Dileep Sharma is a researcher affiliated with James Cook University, focusing on interdisciplinary research at the intersection of oral health, biomedical engineering, and public health. His work spans biomaterials for dental implants, epidemiological studies on oral cancers, and the impact of medications such as bisphosphonates on bone health. He collaborates with international teams on topics like cannabinoid therapeutics for pain management and sustainability practices in dental clinics. Key research interests include: Oral cancer epidemiology and regional disparities Biomaterials for dental implants and their biocompatibility Impact of medications on oral health (e.g., bisphosphonate-related osteonecrosis) Sustainability in healthcare waste management His recent publications analyze trends in oral cancer across OECD countries, predict survival outcomes using nomograms, and investigate the efficacy of materials like xylitol against periodontal pathogens. He also explores virtual reality applications in dental education and patient management. Awards and grants are not explicitly listed in the provided texts, but his extensive publication record reflects sustained contributions to dental and biomedical research.

• Biostatistics
• Public Health
• Substance Use
• +۳ مورد دیگر

Eugenia Buta is a Research Scientist in Biostatistics at Yale School of Public Health (YSPH), affiliated with the Yale Center for Analytical Sciences (YCAS). She earned her PhD in Statistics from the University of Florida (2010) and collaborates with clinical investigators on biomedical and public health research, including studies of veteran pain management, patient experience surveys, and longitudinal substance use analysis. Her work emphasizes tobacco product epidemiology, particularly e-cigarette flavor impacts on youth and adults. Education: PhD in Statistics, University of Florida (2010) Research Interests: Biostatistical methodology for public health challenges Analysis of electronic health records (EHR) and randomized trials E-cigarette flavor influence on nicotine uptake Substance use trajectories among youth Health disparities in veteran populations Recent Article Themes: Over half of her recent work focuses on e-cigarette flavor dynamics and youth susceptibility, with additional emphases on veteran health (pain management, weight behaviors) and methodological innovations in longitudinal data analysis. Awards: McLaughlin Dissertation Fellowship (2010) University of Florida Statistics Faculty Award (2009) William Mendenhall Award (2005) Grants & Advising: No explicitly listed grants, but collaborates on federally funded projects like the Population Assessment of Tobacco and Health (PATH) study. No listed advisees but contributes to training through YSPH programs. Labs/Teams: Yale Center for Analytical Sciences (YCAS) Yale Tobacco Center of Regulatory Science

• Robotics
• Autonomous Vehicles
• Computer Vision
• +۳ مورد دیگر

Matthew Gadd is a Postdoctoral Research Assistant at the University of Oxford and a Junior Research Fellow at Kellogg College. He works in the Mobile Robotics Group (MRG) at the Oxford Robotics Institute (ORI), focusing on Robotics, Autonomous Vehicles, Computer Vision, and Machine Learning. His research addresses challenges in sensor systems, autonomous navigation, and robust place recognition in complex environments. He holds a DPhil in Engineering Science from Keble College, Oxford, and a BSc in Mechatronics Engineering from the University of Cape Town. Education: PhD (DPhil) in Engineering Science, Keble College, University of Oxford (20XX–20XX) BSc in Mechatronics Engineering, University of Cape Town, South Africa Research Projects: Sense Assess eXplain (SAX): Developing auditable autonomous vehicle systems Oxford Offroad Radar Dataset (OORD): Creating datasets for offroad navigation Autonomous biodiversity monitoring using long-term visual navigation Publications Highlights: Gadd’s recent work includes advancements in radar place recognition, uncertainty estimation, and LiDAR-based localization. His research often bridges theory and practice, with applications in autonomous vehicles and environmental robotics. Awards: 2013 FirstRand Laurie Dippenaar Scholarship Labs & Teams: Active contributor to the Oxford Robotics Institute and Mobile Robotics Group, collaborating with Prof. Paul Newman and international research networks.

Mia Pihlajamäkiمشاهده پروفایل

پژوهشگر

• Environmental Impact Assessment
• Eutrophication
• Climate Change
• +۳ مورد دیگر

Mia Pihlajamäki is a Postdoctoral Researcher at Aalto University's Department of Built Environment, specializing in water and environmental engineering. Her work bridges environmental science, social sciences, and transdisciplinary collaboration, focusing on sustainability governance, fisheries management, and climate change mitigation. Education: Doctoral Degree in Social Sciences, University of Tampere (2015) Master's Degree in Social Sciences, University of Tampere (2008) Bachelor's Degree in Natural Sciences, University of Southampton (2003) Research Interests: Transdisciplinary approaches to environmental challenges Water governance and eutrophication mitigation Scenario modeling for climate and land-use futures Collaborative decision-making in fisheries Human-water relationships and sensory ecology Publications (2007–2025): Mia has authored 30+ outputs, including articles on Baltic Sea eutrophication, climate change impacts, and participatory methods in environmental governance. Her work often integrates Bayesian networks, scenario analysis, and stakeholder engagement to address complex socioecological systems. Key Collaborations: Contributions to Baltic Sea governance frameworks Multi-year projects on reindeer herding and land-use futures Transdisciplinary research with artists and scientists Advisory roles in EU marine policy initiatives

• Artificial Intelligence
• Natural Language Processing
• Network Security
• +۳ مورد دیگر

Pedro Arruda Faustini is a Postdoctoral Research Associate at the School of Computing at Macquarie University. His research focuses on artificial intelligence, natural language processing, and network security. Macquarie University, School of Computing His work spans adversarial machine learning, privacy-preserving AI, and voice assistant technologies. He has contributed to semantic reformulation in spoken QA systems and applied reinforcement learning to network security. Recent research includes differential privacy in language models and reconstruction attack analysis in federated learning. Key article trends include adversarial text analysis , privacy metrics , voice assistant design , and secure machine learning . Collaborations highlight interdisciplinary work in network function virtualization and speech interfaces . Pedro's work has been published in venues like Computational Linguistics , ACL , and INTERSPEECH , with notable contributions to fake news detection and non-functional requirements estimation . Advising and Collaborations : Collaborated with researchers like Dr. Mark Dras, Dr. Shaday Moshe Tonni, and Dr. Shlomo Berkovsky. Collaborations span computational linguistics, embedded systems, and network security domains.

• Addiction Medicine
• Drug and Alcohol Treatment
• Applied Statistics
• +۷ مورد دیگر

Dr. Llew Mills is a researcher in Addiction Medicine at the University of Sydney's Central Clinical School, affiliated with the South Eastern Sydney Local Health District. His work focuses on drug and alcohol treatment, particularly exploring how beliefs influence withdrawal symptoms and advancing statistical methods in behavioral analysis. He leads projects like the Cannabis as Medicine Survey (CAMS) and has contributed to randomized trials evaluating treatments for cannabis and alcohol dependence. His statistical expertise spans mixed-effects models, Bayesian analysis, and machine learning. Education: Ph.D. in experimental psychology with focus on caffeine withdrawal mechanisms Roles: Statistical Consultant for DACRIN, Researcher at Langton Centre Key Projects: Nabiximols clinical trials, COQI Project, Exercise & Cannabis Withdrawal RCT Research interests include addiction causation, placebo/nocebo effects, and improving statistical rigor in behavioral research. His publications span addiction treatment outcomes, cannabis policy analysis, and psychopharmacology. Awards include the 2017 Society for Interdisciplinary Placebo Studies Travel Award and an Australian Postgraduate Award (2013-2016). Media engagements include ABC News, Healthline, and international radio discussions on caffeine withdrawal and medical cannabis trends. Technical skills include advanced R/Python programming and Redcap survey design.

Jason Chanمشاهده پروفایل

استاد

• Multisensory Integration
• Cognitive Neuroscience
• Autism Spectrum Disorder
• +۳ مورد دیگر

Jason Chan is a Professor in the Department of Applied Psychology at University College Cork (UCC), Ireland, where he leads research at the intersection of brain and behavior. His work utilizes advanced neuroimaging techniques including magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), and electroencephalography (EEG) to investigate multisensory integration and its applications in understanding neurological conditions. Dr. Chan earned his BA from California State University, Los Angeles, followed by a D.Phil in Experimental Psychology from the University of Oxford. Prior to joining UCC, he conducted post-doctoral research at Trinity College Dublin and Goethe University, gaining expertise in diverse research methodologies across international institutions. His primary research focus centers on multisensory integration (MSI), examining how perceptual training affects cortical connectivity and how these processes serve as biomarkers for neurological conditions including autism spectrum disorder and mild cognitive impairment in aging populations. Through seemingly simple behavioral tasks coupled with sophisticated neuroimaging, Chan's work provides critical insights into human perception and disorders. Analysis of his recent publications reveals a consistent trajectory in multisensory research, with increasing focus on aging populations, autism spectrum disorders, and the application of predictive coding frameworks to understand perceptual processing differences. His work spans both theoretical neuroscience and practical applications for cognitive rehabilitation. Dr. Chan has secured multiple research grants, including funding from Enterprise Ireland, HEA COVID Support, and the Health Research Board for projects examining fear of falling detection systems, community walking programs for older women, and the impact of chaotic home environments on emotional perception in autism. He actively contributes to the academic community through committee service on the Applied Psychology Ethics, Research, and Teaching Committees at UCC. His professional affiliations include the Federation of European Neuroscience Societies, American Association for the Advancement of Science, Society for Neuroscience, Neuroscience Ireland, and the Association for Psychological Science. Dr. Chan directs the Acme Lab (www.acmelab.science), which serves as the hub for his research team's investigations into brain-behavior relationships, providing a collaborative environment for advanced neuroimaging studies and perceptual research.

Aida Cuni Sanchezمشاهده پروفایل

پژوهشگر ارشد

• Tropical Forest Ecology
• Carbon Stocks
• Ethnobotany
• +۴ مورد دیگر

Aida Cuni Sanchez is a Research Fellow affiliated with the University of York (Department of Environment and Geography) and Colorado State University (Ecosystem Science and Sustainability). Her work bridges natural and social sciences, focusing on tropical forest ecology, carbon dynamics, and community-based conservation in Africa. She has held postdoctoral and research positions across institutions including the University of Copenhagen, University College London, and the University of Oxford, contributing to projects in over ten African countries. Her research emphasizes ecosystem services, socio-ecological resilience, and participatory approaches to forest management. Key projects include assessing carbon stocks in Central African forests and evaluating threats to montane ecosystems in Kenya and Cameroon. She advocates for science communication to local communities and policymakers, alongside capacity-building efforts through teaching and mentoring African PhD students. Notable contributions include studies on bushmeat hunting impacts, climate change adaptation strategies for pastoralists, and collaborative frameworks with networks like Mountain Sentinels and AfroMont. Her work integrates Bayesian modeling and stakeholder engagement to inform policy and conservation practices. Education: PhD in Environmental Sciences (University of Southampton), Biology (Barcelona University) Key Skills: Field ecology, biomass estimation, participatory research, multidisciplinary collaboration Current Projects: African montane forests' socio-ecological functioning and management strategies Publications emphasize carbon dynamics, ethnobotanical resource use, and community perceptions of ecosystem services, with a focus on policy-relevant outputs and open-access dissemination.

• Behavioral Sciences
• Computational Biology
• Hallucinations
• +۹ مورد دیگر

Albert Powers is an Associate Professor of Psychiatry at Yale University School of Medicine and serves as Medical Director and Associate Director of the Yale PRIME Psychosis Risk Clinic. His work bridges clinical practice and computational neuroscience, focusing on early psychosis intervention and the mechanisms underlying hallucinations. Dr. Powers' research centers on computational approaches to understanding perceptual dysregulation in psychosis. His work integrates behavioral experiments, computational modeling, and clinical assessment to investigate how sensory systems go awry to produce hallucinations and other psychotic symptoms. He has made significant contributions to understanding prior overweighting in perceptual processing, conditioned hallucinations, and the computational mechanisms of symptom emergence in clinical high-risk populations. His recent publications reveal a strong focus on collaborative large-scale initiatives like the Accelerating Medicines Partnership® Schizophrenia Program, where he contributes to developing standardized protocols for EEG, MRI, digital health technologies, and clinical assessments across international sites. His work spans theoretical computational psychiatry, clinical translation, and innovative intervention development, including his principal investigator role in the study 'Testing a Computationally-Informed, Personalized Intervention for Hallucinations.' Young Physician-Scientist Award (2022) from American Society for Clinical Investigation Carol and Eugene Ludwig Award for Early Career Research (2021) Second Prize, Yale Digital Pitchfest (2021) New Investigator Award (2018) from American Society of Clinical Psychopharmacology Dr. Powers leads the Powers Lab, which investigates the computational mechanisms of hallucinations and develops novel interventions based on these insights. His research bridges basic science and clinical application, with emphasis on translating computational findings into personalized treatment approaches for individuals experiencing psychosis spectrum symptoms. He maintains active collaborations with researchers across Yale and internationally, particularly within the schizophrenia research community.

Jeffrey Dorfmanمشاهده پروفایل

استاد

• Agricultural Economics
• Food Industry Management
• Public Policy Analysis
• +۴ مورد دیگر

Jeffrey Dorfman is the Hugh C. Kiger Distinguished Professor of Agricultural and Resource Economics at North Carolina State University. His roles include teaching, research in food industry economics, and extension work assisting growers, industry, and policymakers on pricing, marketing, and policy issues. Previously, he spent 34 years at the University of Georgia as a professor of economics and served as Georgia’s State Fiscal Economist for four years. He holds a fellowship in the Agricultural and Applied Economics Association and served as editor of the American Journal of Agricultural Economics (AJAE). Notably, his 2021 co-authored paper was awarded the Outstanding AJAE Article of the Year. His research spans agricultural economics, policy analysis, commodity markets, and applied econometrics, with over 100 scholarly articles and four books, including a textbook on food industry economics. Key research interests include food security policy, gender bias in time allocation, cattle market dynamics, and the economic impacts of agricultural policies. His work integrates Bayesian modeling, econometric analysis, and policy evaluation to address real-world challenges in food systems, environmental economics, and public policy. Dr. Dorfman has contributed to debates on topics ranging from cryptocurrency valuation to the effects of monetary policy on commodity prices. His interdisciplinary approach bridges microeconomic theory with applied policy analysis, emphasizing practical solutions for agricultural and food industry stakeholders.

Longhai Liمشاهده پروفایل

استاد

• Statistical Machine Learning
• Model Diagnostics
• Bioinformatics
• +۳ مورد دیگر

Prof. Longhai Li is a Professor at the University of Saskatchewan, specializing in statistical machine learning and model diagnostics. His research focuses on developing methods for analyzing high-throughput and complex data, particularly in bioinformatics and medical research. He holds a Ph.D. from the University of Toronto and a B.Sc. from the University of Science and Technology of China. Prof. Li teaches diverse statistics courses, including introductory and applied statistics, computational methods, and probability theory. His teaching emphasizes practical tools like R and R Markdown, and he involves undergraduates in research projects, such as developing real-time disease tracking websites and statistical packages. His research has been funded by agencies like NSERC, CFI, and MITACS. Notable projects include statistical methodologies for microbiome data, geospatial AI for wheat production analysis, and predictive modeling for high-dimensional datasets. He has developed R packages like HTLR for Bayesian logistic regression. Prof. Li has supervised 3 postdoctoral fellows, 23 graduate students, and 14 undergraduates. His work appears in journals such as the American Statistician and BMC Medical Research Methodology.

Cai Yutongمشاهده پروفایل

مدرس

• Transportation Engineering
• Operations Research
• Machine Learning
• +۳ مورد دیگر

Dr. Cai Yutong is a Lecturer at the Engineering Systems and Design (ESD) pillar of Singapore University of Technology and Design (SUTD). He holds a PhD in Civil Engineering (Transportation) from National University of Singapore (2022), an M.Sc. in Transportation Systems & Management (2017), and a B.Sc. in Shipping Management (2016). His work focuses on optimization, discrete choice modeling, and machine learning applications in sustainable mobility, active mobility, and maritime studies. Research interests include maritime risk assessment, transportation policy, and smart mobility solutions. Notable contributions include projects funded by Singapore's Ministry of Transport, Ministry of Home Affairs, and Singapore Maritime Institute. His research has been published in top-tier journals like Transportation Research Parts C/D/E , Applied Energy , and Transport Policy . Key achievements include the 2021 Best Student Paper Award at the International Symposium on Multimodal Transportation. His work spans transportation infrastructure design, electric vehicle systems, and agent-based simulations for bike-sharing dynamics. Current research emphasizes equitable urban cycling networks and maritime chokepoint resilience. Dr. Cai has collaborated on projects addressing vessel detention risk, AV adoption perceptions, and trade corridor route optimization. His interdisciplinary approach bridges operations research, data science, and policy analysis to address real-world transportation challenges.

Bernard Bayleمشاهده پروفایل

استاد

• Robotics
• Medical Robotics
• Human-Robot Interaction
• +۲ مورد دیگر

Bernard Bayle is a Professor at the University of Strasbourg and a member of the ICube Laboratory within the Robotics, Data Science, and Healthcare Technologies research group, which he headed from 2018 to 2023. He leads the HealthTech Interdisciplinary Institute that combines an interdisciplinary research cluster with a graduate school. His research focuses on the design, modeling, and control of robotic systems, particularly for healthcare applications including physical human-robot interactions and robot-assisted medical interventions. He teaches courses in Mechatronics and Haptics, Mobile Robotics, and Robot-Assisted Interventions at Télécom Physique Strasbourg. His research has resulted in over 100 scientific publications, 33 journal papers in top robotics and engineering venues, and 7 patent applications. His research primarily explores robotics applications in medical contexts, including surgical assistance, rehabilitation technologies, and diagnostic systems. Recent work focuses on haptic feedback systems, continuum robots, and autonomous medical intervention platforms. He has supervised 19 PhD students and led 5 research projects as principal investigator while participating in 11 others. His lab focuses on developing robotic solutions for healthcare challenges through interdisciplinary collaboration.