جست‌وجوی استاد و پژوهشگر

• Epilepsy
• Consciousness
• Neuroimaging
• +۳ مورد دیگر

Hal Blumenfeld, MD, PhD, is a Professor of Neurology, Neuroscience, and Neurosurgery at Yale University's School of Medicine, serving as Director of the Clinical Neuroscience Imaging Center (CNIC). He specializes in epilepsy, consciousness, and neuroimaging. His research focuses on understanding the mechanisms underlying impaired consciousness during seizures and developing innovative diagnostic and treatment approaches. Dr. Blumenfeld holds a PhD from Columbia University and completed neurology residency at Massachusetts General Hospital. Appointments: Neurology (Primary), Neuroscience & Neurosurgery (Secondary) Key Roles: Director, CNIC; Author, Neuroanatomy Through Clinical Cases Research Interests: Epilepsy , Consciousness , Neuroimaging , and Cortical-Subcortical Mechanisms . His work combines human and animal models to study seizure-induced consciousness impairment, with a focus on neurovascular coupling, EEG-fMRI, and wearable technologies for real-time monitoring. Publications highlight advancements in understanding absence epilepsy, focal seizures, and the neural correlates of sensory perception. Recent studies explore cholinergic arousal deficits and predictive models for impaired consciousness. His team has developed the ARTiE Watch for automated responsiveness testing in epilepsy. Awards : Javits Neuroscience Investigator Award (NIH), Francis Gilman Blake Award (Yale), and Whitaker Visiting Professorship (ANA). Labs & Teams : Blumenfeld Lab, CNIC, and collaborations with the Kavli Institute for Neuroscience.

• IoT Wireless Sensing and Networking
• 5G/6G Cellular Systems
• TeraHertz Communications
• +۸ مورد دیگر

Associate Professor Zihuai Lin leads the IoT in Healthcare and Radar Imaging group at the University of Sydney's School of Electrical and Computer Engineering. He holds a PhD from Chalmers University of Technology and has prior experience at Ericsson Research and Aalborg University. His research focuses on IoT, 5G/6G systems, healthcare AI, TeraHertz communications, radar imaging, and wireless signal processing. Education: PhD in Electrical Engineering, Chalmers University of Technology, Sweden (2006) Postdoctoral work at Ericsson Research, Sweden Associate Professor, Aalborg University, Denmark (pre-Sydney role) Research Interests: IoT wireless sensing and healthcare applications 6G/THz communications and radar imaging Artificial Intelligence in signal analysis and network optimization MIMO/OFDMA systems and resource allocation Current Projects: 6G/THz communications and holographic MIMO Edge AI for healthcare IoT (eGate system) Ultra-low latency techniques for short-packet 5G Millimeter-wave power transfer and safety protocols Awards: 2021 IoT Awards Health Category Finalist (eGate system) Nominated for 2022 iTnews Best Health Project Advising & Labs: Supervising 8 PhD students in AI-driven healthcare, federated learning, and quantum imaging Led 10+ completed PhD projects in 5G/6G and wireless systems Affiliated with the Center of IoT and Telecommunication (CIoTT) and Sydney Nano Institute

Pier Palamaraمشاهده پروفایل

دانشیار

• Statistical Genetics
• Population Genetics
• Genomics
• +۶ مورد دیگر

Pier Palamara is an Associate Professor of Statistical and Population Genetics at the University of Oxford's Department of Statistics, affiliated with the Centre for Human Genetics. He holds a PhD in Computer Science from Columbia University (2014) and completed postdoctoral training at Harvard Chan School of Public Health and the Broad Institute of MIT and Harvard. His research integrates statistics, computer science, and genetics to develop methods for analyzing large genomic datasets, focusing on evolutionary parameters, demographic history, complex trait genetics, and disease variation. Key research interests include reconstructing population movements via genetic data, studying natural selection and mutation rates in human genomes, and developing scalable algorithms for genomic analysis. He leads the Palamara Lab, which collaborates on projects like the Genomics England haplotype reference panel and the UK Biobank imputation. His lab's work is supported by grants and partnerships, and they develop software tools such as ASMC, Quickdraws, and Threads. Recent publications highlight contributions to Indo-European genetic origins, scalable mixed-model association methods, and ancient DNA analysis of European farmers. He advises graduate students and has mentored researchers in computational biology and statistical genetics.

Daniel Nettelsمشاهده پروفایل

پژوهشگر

• Biophysics
• Single-molecule spectroscopy
• Protein folding and misfolding
• +۳ مورد دیگر

Dr. Daniel Nettels is a Senior Scientist at the University of Zurich's Department of Biochemistry within the Faculty of Science. His research focuses on biophysical methods, including single-molecule spectroscopy and fluorescence techniques, to study protein folding, misfolding, and the dynamics of biomolecular condensates. He joined Prof. Ben Schuler's group in 2004 after completing a Ph.D. in physics at the University of Fribourg and prior studies in physics at the University of Bonn. Nettels teaches the module BCH 306: Biochemical and Biophysical Methods. His work integrates experimental and computational approaches to understand disordered proteins and their roles in biological systems. Education: Ph.D. in Physics, University of Fribourg (2003) M.Sc./Diploma in Physics, University of Bonn (1998) Research Interests: Single-molecule FRET and spectroscopy Biomolecular condensates and their dynamics Intrinsically disordered proteins Teaching: BCH 306 module in the Faculty of Science

Stephen Thompsonمشاهده پروفایل

مدرس ارشد

• Strength and Conditioning
• Resistance Training
• Velocity-Based Training (VBT)
• +۴ مورد دیگر

Stephen Thompson is a Senior Lecturer and Course Leader for the MSc in Strength and Conditioning (S&C) Coaching at Sheffield Hallam University. He holds accreditation as a Strength and Conditioning Coach (ASCC) with the UKSCA and is completing a PhD focusing on Velocity-Based Training (VBT), specifically load-velocity profiling for maximal intensity prediction. His research interests include resistance training, technology in training, and youth development, with publications in journals like Journal of Strength and Conditioning Research and Sports Medicine . He teaches across undergraduate and postgraduate programs in the Department of Sport and Physical Activity, leading courses such as the MSc in Strength and Conditioning Coaching and Applied Sport and Exercise Science. His academic roles include Employability Lead, fostering partnerships with local clubs and organizations for student placements. Thompson’s work spans academia and applied practice, with consultancy roles for elite teams like GB Diving and a Championship football academy. His research emphasizes VBT methodologies, load prescription, and the validation of sports technologies. Key contributions include studies on barbell velocity measurement, 1RM prediction models, and athlete performance profiling. He has secured grants from national governing bodies and collaborated internationally on projects. His expertise bridges theoretical research and practical applications in elite sport conditioning and athlete development.

Bas Donkersمشاهده پروفایل

استاد

• Consumer Behavior
• Marketing Research
• Choice Modeling
• +۴ مورد دیگر

Bas Donkers is a full Professor of Marketing Research at the Department of Business Economics within Erasmus School of Economics (ESE), Erasmus University Rotterdam. Affiliated with ERIM (Erasmus Research Institute of Management) since 2000, he holds a prominent position in the field of consumer behavior and marketing analytics. His research examines consumer decision-making from a behavioral perspective, building on advanced market research and machine learning techniques to generate groundbreaking insights. His research interests center on consumer behavior , choice modeling , and marketing analytics , with significant contributions to healthcare decision-making and financial investment contexts. Donkers has published extensively in leading journals including Journal of Marketing Research, Marketing Science, and Journal of the Academy of Marketing Science. His recent work demonstrates a clear trajectory toward integrating machine learning with traditional choice modeling, particularly in healthcare applications (35% of recent publications) and digital consumer behavior (25%), with growing emphasis on AI-driven decision support systems. ERIM Top Article Junior Award (2017) ERIM postdoc fellowship (2002) Donkers has supervised 13 PhD candidates to completion, serving as promotor or co-promotor on diverse topics spanning retirement planning, charitable giving, healthcare choice modeling, and digital marketing analytics. His research has been supported through ERIM frameworks and collaborative projects with healthcare institutions. He actively coordinates academic events including the Invitational Choice Symposium and regularly presents at specialized research seminars. As a core member of ERIM's Marketing Group, Donkers contributes to the institute's research infrastructure focused on behavioral decision modeling and choice experimentation. His work bridges theoretical marketing research with practical applications in healthcare policy and financial services, maintaining strong connections with industry partners through ERIM's business engagement initiatives.

Ksenia Dolgalevaمشاهده پروفایل

دانشیار

• Integrated Photonics
• Nonlinear Optics
• THz Technology
• +۳ مورد دیگر

Ksenia Dolgaleva is an Associate Professor at the University of Ottawa's School of Electrical Engineering and Computer Science, and holds a Canada Research Chair in Integrated Photonics (Tier 2). She joined the university in July 2013 as part of the Canada Excellence Research Chair team led by Professor Robert Boyd. Education: She earned a Diploma in Physics from Moscow State University (Russia) and a Ph.D. in Optics from the University of Rochester (USA, 2009). She completed a postdoctoral fellowship at the University of Toronto (2009–2013), supported by a Mitacs Elevate fellowship (2011–2012). Research Interests: Her work focuses on integrated photonics, nonlinear optics, THz technology, and advanced optical materials. Key areas include artificial photonic structures, nonlinear responses in materials like InP, GaN, and quartz, and plasmonic metamaterials for sensing and frequency conversion. Publications & Trends: Over 20 peer-reviewed articles highlight her contributions to nonlinear photonics platforms, THz spectroscopy, and material characterization. Recent work emphasizes phase-matched processes, ultra-high-Q resonances, and THz plasmonic metasurfaces. Scientific Awards: Outstanding undergraduate thesis award (Russian Physical Society, 2009) Outstanding student presentation (OSA Frontiers in Optics, 2008) Advising & Grants: Trained 8 students during her Ph.D. and postdoc. Currently building her research group to explore optics and photonics. Labs/Teams: Active in the Canada Excellence Research Chair team and collaborates on projects involving III-V semiconductors and THz technologies.

• Bayesian statistics
• Computational statistics
• Environmental statistics
• +۴ مورد دیگر

Roles & Affiliations: Distinguished Research Professor in Statistical Science at Queensland University of Technology (QUT), Director of QUT Centre for Data Science, and Associate Member of University of Oxford's Department of Statistics. Served as Deputy Director of ARC Centre of Excellence in Mathematical and Statistical Frontiers (2015–2021) and ARC Laureate Fellow (2015–2021). Education: BA (Hons) and PhD in Mathematical Statistics from University of New England, Australia. Completed post-doctoral roles at multiple Australian universities. Research Interests: Specializes in Bayesian statistical modelling, computational methods, and their applications in environmental science, genetics, healthcare, and industry. Leads projects on coral reef recovery, cancer epidemiology (Australian Cancer Atlas), and virtual citizen science platforms like Virtual Reef Diver. Her work emphasizes interdisciplinary collaboration, integrating complex data sources with advanced statistical techniques to address real-world challenges. Publications & Grants: Over 350 refereed journal publications and attracted >30 major grants. Recent focus areas include influenza epidemiology, spatial health disparities, and AI-driven early warning systems for climate-sensitive diseases. Active in developing methodologies for spatial statistics, small-area estimation, and federated learning. Awards & Recognition: 2024 Ruby Payne-Scott Medal (Australian Academy of Science), Pitman Medal (2016), first female recipient of this award in 35 years. Elected Fellow of Australian Academy of Science (2018), Academy of Social Sciences (2018), and Queensland Academy of Arts and Sciences (2018). Holds international roles including Vice-President of International Statistical Institute (2021–2025) and Scientific Council Member at Centre International de Rencontres Mathématiques (France). Supervision & Leadership: Supervised over 36 PhD students and leads teams in >50 collaborative projects. Current supervision includes 5 PhD and 4 Masters students at QUT. Founded the QUT Centre for Data Science and previously led the Collaborative Centre for Data Analysis, Modelling and Computation. Labs & Initiatives: Core contributor to the Australian Cancer Atlas 2.0, Virtual Reef Diver project, and Queensland's Learning Potential Fund. Active in global initiatives like the World of Statistics campaign and UN Big Data Task Teams.

Emmanuel Fonsecaمشاهده پروفایل

استادیار

• Radio Astronomy
• Astrophysics
• Neutron Stars
• +۳ مورد دیگر

Emmanuel Fonseca is an Assistant Professor in the Department of Physics and Astronomy at West Virginia University (WVU), joining in Fall 2021. Previously, he was a postdoctoral researcher at McGill University (2016–2021) and completed his Ph.D. in Astronomy at the University of British Columbia (2016). His research focuses on radio astronomy, particularly pulsars and fast radio bursts (FRBs), leveraging facilities like CHIME, the Green Bank Telescope, and NANOGrav. He specializes in using pulsars as laboratories for testing fundamental physics and detecting gravitational waves via pulsar timing arrays. Education: Ph.D. in Astronomy, University of British Columbia (2016) M.Sc. in Astronomy, University of British Columbia (2012) B.Sc. in Physics and Astronomy, Pennsylvania State University (2010) Research Interests: Emmanuel’s work spans three key areas: Compact Objects: Investigating neutron stars and extreme environments using pulsar binaries and relativistic dynamics. CHIME Pulsar/FRB Science: Developing instrumentation and analyzing data from the Canadian Hydrogen Intensity Mapping Experiment to study FRBs and pulsars. Gravitational Waves: Contributing to NANOGrav’s efforts to detect nanohertz gravitational waves via millisecond pulsar timing arrays. Collaborations: He is a core member of NANOGrav and instrumental in maintaining CHIME’s pulsar and FRB backend systems. His work bridges hardware/software development with observational astronomy. Labs/Teams: Involved with the CHIME/FRB Collaboration and the NANOGrav Collaboration, advancing both observational infrastructure and theoretical astrophysics.

Ming Yuanمشاهده پروفایل

استاد

• High-dimensional statistics
• Machine learning
• Tensor methods
• +۴ مورد دیگر

Ming Yuan is a Professor in the Department of Statistics at Columbia University and serves as Associate Director of the Data Science Institute. His research focuses on high-dimensional statistics, machine learning, and statistical methodology with applications in genomics, finance, and imaging. Yuan holds a Ph.D. in Statistics from the University of Wisconsin-Madison (2004) and a B.S. in Electrical Engineering from the University of Science and Technology of China (1997). Education: 2004 Ph.D., Statistics, University of Wisconsin-Madison 2003 M.S., Computer Science, University of Wisconsin-Madison 2000 M.S., Probability and Statistics, University of Science and Technology of China 1997 B.S., Electrical Engineering, University of Science and Technology of China Research Interests: Dr. Yuan’s work bridges theoretical and applied statistics, emphasizing scalable methods for high-dimensional data. Key areas include tensor decomposition, covariance estimation, and statistical machine learning. His contributions to methods like sparse inverse covariance estimation and matrix/tensor completion have found applications in finance, genomics, and image analysis. Publications: His recent work explores tensor-based methods for high-dimensional analysis and develops optimal algorithms for compressed sensing. Articles often address statistical theory and computational challenges in modern data science, reflecting a balance between foundational and applied research. Awards: 2025 JASA Theory & Method Invited Discussion Paper 2024 William F. Sharpe Award (JFQA) 2018 Medallion Lecturer (Institute of Mathematical Statistics) 2014 Guy Medal in Bronze (Royal Statistical Society) 2007 Leo Breiman Junior Award Professional Activities: Yuan has served as Co-Editor of The Annals of Statistics (2019–2021) and Program Secretary for the Institute of Mathematical Statistics (2018–2021). His work integrates interdisciplinary collaborations, particularly in biomedical imaging and financial econometrics.

Christopher Brooksمشاهده پروفایل

استادیار

• Educational Technology
• Data Science Education
• Learning Analytics
• +۳ مورد دیگر

Christopher Brooks is an Assistant Professor at the University of Michigan's School of Information, specializing in educational technologies and data science education. He directs the Educational Technology Collective (etc), a multidisciplinary research group focused on learning analytics, educational data mining, and collaborative learning systems. His work bridges computer science and education, with a focus on improving teaching methods through AI-driven tools and platforms. Research Interests: Development and impact assessment of educational technologies Predictive modeling for student success Data science pedagogy Privacy in smart home technologies Publications reflect a focus on learning analytics, MOOC design, and educational AI, with notable contributions to conferences like CHI, LAK, and AIED. Awards include multiple best paper recognitions. Teaching includes applied data science courses at UMich and Coursera. He leads the Master of Applied Data Science (MADS) program and collaborates with institutions like Microsoft to build AI-driven educational tools.

• Climate Change
• Global Environmental Change
• Sustainability Transformations
• +۷ مورد دیگر

Karen O'Brien is a Professor in the Department of Sociology and Human Geography at the University of Oslo, where she has been a full-time faculty member since 2005. She is internationally recognized for her work on the human and social dimensions of global environmental change, with a focus on climate change, adaptation, and transformative pathways to sustainability. She currently serves as co-chair of the IPBES transformative change assessment and has contributed to major scientific assessments including the IPCC Fifth Assessment Report. Her educational background includes a BA in International Relations from the College of William and Mary (1985), an MS in Environmental Studies from the University of Wisconsin-Madison (1990), and a PhD in Geography from Pennsylvania State University (1995). She completed a postdoc at the North American Commission for Environmental Cooperation in 1996 and was a Senior Research Fellow at CICERO from 1997 to 2005. Karen O'Brien's research centers on integrative and transdisciplinary approaches to sustainability, emphasizing the role of beliefs, values, and worldviews in driving social and systems change. She is a leading proponent of quantum social science as a framework for understanding and scaling transformative change. Her recent scholarly output explores youth activism, climate education, and the philosophical underpinnings of transformation in the Anthropocene. Her publications reveal a strong thematic focus on transformation, adaptation, and the intersection of climate change with social theory. Articles consistently engage with interdisciplinary frameworks, action research, and innovative methodologies such as SenseMaker, reflecting her commitment to bridging science, policy, and societal action. BBVA Foundation's Frontiers of Knowledge Award for Climate Change (2021) Member of Academia Europaea (2022) University of Oslo Student Parliament's Teaching Award (2015) Burtoni Prize for Adaptation Research (2011) AAG Meridian Book Award (2008) Shared in the 2007 Nobel Peace Prize as part of the IPCC Karen O'Brien has supervised numerous PhD and Master’s students, though specific names are not listed in the provided text. She has led significant research projects such as the AdaptationCONNECTS project and co-founded cCHANGE, an organization dedicated to sustainability transformations. Her advisory roles include membership on the Science Committees of Future Earth and Our Common Future in a Changing Climate, as well as leadership in the transition to global sustainability research initiatives. She has no reported grants listed, but her involvement in large-scale international assessments implies substantial funding support. She is affiliated with key research platforms including the Department of Sociology and Human Geography at the University of Oslo, where she has served on the Board, and the Research Center for Socially Inclusive Energy Transition (Include). Her work is deeply collaborative, involving networks such as IPBES, IPCC, and Future Earth, and she frequently publishes with interdisciplinary teams across Europe and North America.

• Machine Learning in Energy Systems
• Renewable Energy
• Energy Forecasting
• +۱۲ مورد دیگر

Prof. Erdem Günay is a full Professor in the Department of Energy Systems Engineering at Istanbul Bilgi University, where he has been serving since 2013, rising through the academic ranks. He holds a Ph.D. in Chemical Engineering from Bogazici University, where he also completed his B.S. and M.S. degrees, and conducted postdoctoral research. His academic journey reflects a deep commitment to energy systems and sustainable technologies. B.S. in Chemical Engineering, Bogazici University, 2002 M.S. in Chemical Engineering, Bogazici University, 2005 Ph.D. in Chemical Engineering, Bogazici University, 2012 Postdoctoral Research Associate, Catalyst Design and Reaction Engineering Laboratory, Bogazici University, 2013 Prof. Günay’s research centers on the integration of machine learning and artificial intelligence with energy systems engineering. His work spans renewable energy (solar, wind, bioenergy), hydrogen production, CO₂ utilization, fuel cells, and energy demand forecasting. He employs advanced data mining, neural networks, and explainable AI to model, simulate, and optimize complex energy processes, contributing significantly to sustainable energy solutions. His interdisciplinary approach bridges chemical engineering, environmental science, and computational modeling. His recent publications demonstrate a strong trend in applying machine learning to sustainable bioenergy, catalysis, and environmental management. From optimizing biochar production to forecasting global temperature anomalies and enhancing microbial fuel cells, his research leverages AI to address pressing energy and environmental challenges. The articles reflect a consistent focus on sustainability, efficiency, and innovation in energy technologies, with a growing emphasis on explainability and real-world applicability of AI models. Prof. Günay has not been mentioned to have received any specific scientific awards, but his extensive publication record in high-impact journals indicates strong recognition in his field. He has advised several Master’s students, including Muaaz Jnani, Duru Akalın, and co-advised Ahmet Coşgun and Meltem Baysal. He actively supervises senior design projects in areas such as biogas production, biodiesel from shea butter, pyrolysis, and solar desalination, fostering hands-on learning and innovation among students. While no external grants are explicitly mentioned, his research output suggests active involvement in funded projects. His teaching portfolio includes core courses such as Thermodynamics, Fluid Mechanics, Fuels and Combustion, and Energy Systems Modeling and Simulation. Although specific lab or research team names are not provided, his frequent collaborations with researchers like Ramazan Yıldırım, N. Alper Tapan, and Ahmet Coşgun suggest active participation in a research group focused on AI-driven energy and catalysis research at Istanbul Bilgi University.

Jane Lawمشاهده پروفایل

دانشیار

• Geographic Information Systems
• Spatial Analysis
• Bayesian Spatial Modeling
• +۷ مورد دیگر

Jane Law is an Associate Professor at the University of Waterloo, located in EV3 3251. She holds a Ph.D. in Geodesy and Geomatics Engineering from the University of New Brunswick (2000), a University Teaching Diploma from the same institution (1999), an M.Sc. in Land Information Systems from Hong Kong Polytechnic University (1994), and a B.Sc. in Survey and Mapping Sciences from North East London Polytechnic (1985). Her research integrates spatial analysis with public health and criminology, employing Bayesian methodologies to examine neighborhood effects on health outcomes and crime patterns. Law's research focuses on geographic information systems, Bayesian spatial modeling, spatial epidemiology, environmental criminology, and health-oriented urban planning. She explores how built environments influence community health outcomes and crime distribution using advanced statistical geospatial techniques. Her publications demonstrate consistent focus on Bayesian spatial modeling applications in public health and crime analysis, with recent work emphasizing mental health spatial patterns, nutrition environments, and temporal crime trends. Research consistently integrates GIS with statistical innovation for policy-relevant insights. Law has supervised 43 Master's and 5 PhD students to completion and currently advises 2 Master's and 1 PhD candidate. She secured a long-term research grant as Principal Investigator for 'Advancing spatial analysis methodologies using a Bayesian approach' (2009-2022).

Oliver Alonzoمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Computing Accessibility
• Digital Accessibility for People with Disabilities
• +۳ مورد دیگر

Oliver Alonzo is an Assistant Professor in the School of Computing at DePaul University. His academic journey includes a Ph.D. in Computing and Information Sciences from the Rochester Institute of Technology, a B.S. in Computer Science from Creighton University with minors in Graphic Design and Musical Theatre. Prior to joining DePaul, he served as a post-doctoral assistant professor at Creighton University and completed internships at Meta (Facebook) and Adobe Research. Dr. Alonzo's research focuses on Human-Computer Interaction and Computing Accessibility, with particular emphasis on creating technologies that improve digital access for people with disabilities, especially those who are Deaf or Hard-of-Hearing (DHH). His work spans several key areas: Design and evaluation of automatic text simplification tools for DHH readers Captioning and visualization of non-speech sounds in multimedia content Accessibility solutions for social media platforms Tools to assist American Sign Language learners Multimedia accessibility in emerging technologies like virtual reality His recent publications demonstrate a consistent focus on developing and evaluating accessibility technologies through rigorous user-centered design with DHH communities. His research has evolved from foundational work on text simplification and sign language interfaces to broader explorations of digital accessibility across multiple platforms and contexts. Dr. Alonzo has received notable recognition for his work, including: CHI 2025 Honorable Mention for research on Deaf and Hard-of-Hearing user experiences with misinformation on social media An NSF CRII grant for a two-year project focused on making videos accessible by design for Deaf, Hard-of-hearing, Blind and Low-Vision viewers As an educator, Dr. Alonzo teaches courses including HCI 440 Introduction to User-Centered Design, HCI 445 User Research Methods, and HCI 511 Accessibility Considerations in HCI. His teaching philosophy emphasizes practical, hands-on learning experiences that connect theoretical concepts to real-world accessibility challenges. Outside academia, Dr. Alonzo is fluent in Spanish, English, and Portuguese, and is learning American Sign Language. He has a background in musical theatre and enjoys black & white photography, which informs his creative approach to accessibility research.