جست‌وجوی استاد و پژوهشگر

• Educational Psychology
• Gifted Education
• Primary Education
• +۳ مورد دیگر

Saskia Snikkers is a researcher at the University of Groningen specializing in educational psychology with particular expertise in gifted student engagement and autonomy development. Her work contributes to UN Sustainable Development Goals related to quality education. Her primary research interests include: Educational Psychology Gifted Education Primary Education Student Engagement Dynamics Autonomy in Learning Environments Special Educational Needs Analysis of her publications reveals consistent focus on qualitative exploration of how gifted students develop engagement through pedagogical relationships, with significant attention to teacher perspectives and alternative educational approaches like Waldorf schooling in the Netherlands. Her methodological approach combines in-depth interviews with statistical analysis, emphasizing autonomy as a critical factor in sustaining student engagement. Research collaborations with scholars like Mayo and Minnaert demonstrate active participation in educational psychology networks, with publications appearing in journals including Frontiers in Education and Forum for Education Studies .

• Database Systems
• Data Privacy
• Big Data Analytics
• +۳ مورد دیگر

Prof. Johann-Christoph Freytag is a faculty member at the Institute of Computer Science within Humboldt University of Berlin's Faculty of Mathematics and Natural Sciences. His academic profile demonstrates a unique interdisciplinary approach bridging core computer science with environmental research, particularly focused on Arctic systems and climate change analysis. His research spans multiple domains: Advanced database systems and query optimization techniques Data privacy frameworks for cooperative systems and safety applications Big data analytics for environmental monitoring Graph theory applications in landscape analysis Age-depth modeling for paleoenvironmental studies Computer vision approaches to permafrost monitoring Analysis of Prof. Freytag's recent publications reveals a strategic research trajectory that increasingly integrates computational methods with environmental science. His work shows consistent contributions to database theory while expanding into climate-related applications, particularly through projects involving Arctic lake systems, permafrost dynamics, and tundra landscapes. This interdisciplinary approach demonstrates how database technologies can address complex environmental challenges. Prof. Freytag has been actively involved in the German database research community, including participation in organizing the BTW (Database Systems for Business, Technology and Web) conference series, which represents a significant contribution to academic community building in his field.

• Instrumented indentation test
• Measurement uncertainty
• Nanoindentation
• +۷ مورد دیگر

Giacomo Maculotti is a Fixed-term Tenure-Track Assistant Professor at the Department of Management and Production Engineering (DIGEP) at Politecnico di Torino. He is actively involved in teaching and research activities related to surface characterization, manufacturing technologies, and metrology. College of Chemical and Materials Engineering (Invited member) College of Mechanical, Aerospace and Automotive Engineering (Member) His research focuses on instrumented indentation tests, nanoindentation, statistical process control, and technological surface characterization. He contributes to advanced manufacturing research through projects like ADAM (Digital-Metrological Twins) and DI-VISION (Traceable machine vision systems). Recent publications analyze directed energy deposition techniques for tool steel, antibiofilm dental coatings, and photogrammetry scaling. He holds patents in measurement apparatus design and wear trace characterization. Scientific disciplinary sector: IIND-04/A - Manufacturing Technologies and Systems ERC skills: Manufacturing engineering, Mechanical engineering, Metrology, Production technology Maculotti supervises PhD student Angelo Nicola Culotta and collaborates on quality control projects with Electrolux Italia S.p.A. He teaches courses in Mechanical and Topographical Characterization of Technological Surfaces and Experimental Statistics and Mechanical Measurement.

• Theoretical Atomic Physics
• Cold-Atom Physics
• Quantum Nonlinear Dynamics
• +۳ مورد دیگر

Professor Simon Gardiner is a faculty member in the Department of Physics at Durham University, serving as Deputy Executive Dean (Education) in the Faculty of Science. He has held this position since 2005, following postdoctoral work in Potsdam, Hannover, Oxford, and JILA (Colorado). Durham University Department of Physics (2005–present) Deputy Executive Dean (Education) in Faculty of Science Education: Originally from Hamilton, New Zealand, Gardiner studied Biology and Chemistry at the University of Waikato before shifting to Mathematics and Theoretical Physics. He completed his doctoral studies in theoretical physics at the Leopold-Franzens University of Innsbruck, Austria. Gardiner’s research focuses on theoretical atomic physics , cold-atom physics , and quantum nonlinear dynamics . His work includes: Quantum dynamics of bright matter-wave solitons Quantum resonance phenomena in laser-pulsed atomic systems Cooperative effects in atomic arrays Spin-orbit coupling in correlated atom systems Atomtronic circuitry Development of number-conserving models for Bose-Einstein condensates Recent publications (2019–2025) demonstrate his ongoing contributions to: Quantum soliton interferometry Photon correlations in thermal atomic ensembles High-energy physics simulation tools Machine learning applications in physics Atomic array optical properties Nonlinear quantum dynamics

Yen Huan Liمشاهده پروفایل

دانشیار

• Machine Learning
• Optimization
• High-dimensional Statistics
• +۶ مورد دیگر

Yen Huan Li is an Associate Professor in the Department of Computer Science and Information Engineering at National Taiwan University's College of Engineering. He leads the Learning Theory and Optimization Methods Laboratory and maintains an active research program in theoretical machine learning and optimization. His research expertise spans machine learning, convex optimization, high-dimensional statistics, and quantum information theory . Professor Li specializes in decision making under uncertainty with weak or no assumptions about reality, developing theoretical frameworks that bridge game theory and machine learning. His recent work focuses on Blackwell approachability, probability forecasting calibration, online prediction algorithms, and optimization methods for strongly convex problems. These theoretical contributions have implications for designing robust machine learning algorithms that perform well under minimal assumptions. Professor Li is actively recruiting students and research assistants interested in theoretical aspects of machine learning and optimization. Prospective students must demonstrate knowledge of relevant theory papers and be prepared to discuss them in depth. His laboratory work emphasizes rigorous mathematical analysis of learning algorithms, with applications spanning from basic theoretical questions to practical algorithm design considerations. The research environment combines deep theoretical investigation with attention to practical implications for machine learning systems.

Simon Shaolei Duمشاهده پروفایل

استادیار

• Machine Learning
• Deep Learning
• Representation Learning
• +۵ مورد دیگر

Simon Shaolei Du is an Assistant Professor at the Paul G. Allen School of Computer Science & Engineering, University of Washington. His research focuses on machine learning, spanning deep learning, representation learning, reinforcement learning, and data selection. He previously held postdoctoral positions at the Institute for Advanced Study of Princeton and has collaborated with major research labs including Meta, Google, and Microsoft. Ph.D. in Machine Learning, Carnegie Mellon University (2019) Co-advised by Aarti Singh and Barnabás Póczos Undergraduate study in EECS and EMS at UC Berkeley Du’s research addresses foundational questions in machine learning, including optimization guarantees for neural networks, sample complexity in reinforcement learning, and theoretical insights into preference learning frameworks like RLHF and DPO. His work bridges practical algorithm design with rigorous mathematical analysis. Recent publications highlight his expertise in reinforcement learning (e.g., policy-based trajectory clustering, latent state decoding), optimization theory (e.g., gradient descent dynamics, saddle point escape), and representation learning (e.g., overparameterized Gaussian mixtures). These span both theoretical and applied dimensions of machine learning. IEEE AI’s 10 to Watch, 2024 Schmidt Sciences AI2050 Early Career Fellow, 2024 Alfred P. Sloan Research Fellowship, 2024 Intel Rising Star Faculty Award, 2023 Samsung AI Researcher of the Year, 2022 NSF CAREER Award, 2022 Du’s affiliations include the NSF AI Institute for Societal Decision Making (AI-SDM) and the Simons Institute for Theoretical Computer Science. He actively mentors researchers and welcomes prospective students and postdocs via email submissions with CVs.

Yijie Xiongمشاهده پروفایل

استادیار

• Animal Housing Environmental Control
• Precision Livestock Management
• Applied Data Analysis in Agriculture
• +۳ مورد دیگر

Yijie Xiong is an Assistant Professor in Precision Animal Management at the University of Nebraska-Lincoln, split between Animal Sciences (75%) and Biological Systems Engineering (25%). His research focuses on optimizing livestock environments through engineering solutions, precision livestock management, and data-driven agricultural analysis. He holds a Ph.D. in Agricultural Engineering from the University of Illinois at Urbana-Champaign (2019), an M.S. from the same institution (2013), and a B.S. from China Agricultural University (2011). Key research areas include: Animal Housing Environmental Control: Developing systems to manage heat stress in poultry and swine Precision Livestock Management: Integrating real-time monitoring and data analysis for improved animal performance and welfare Applied Data Analysis: Leveraging statistical methods and visualization tools for agricultural decision-making Recent work emphasizes innovative technologies like cooled perch systems for poultry, 3D imaging for livestock weight estimation, and virtual fencing for cattle management. His studies on EPA emission models and greenhouse gas fluxes reflect a growing focus on sustainability and environmental impact. Notable awards include the Graduate College Dissertation Completion Fellowship (2019) and Excellence for Oral Presentation at the Poultry Sciences Association (2018). Professional memberships span ASABE, PSA, and ASHRAE. His interdisciplinary approach bridges engineering, animal science, and data analytics to address modern agricultural challenges.

Kelian Dascher-Cousineauمشاهده پروفایل

استادیار

• Earthquake Forecasting
• Fault Mechanics
• Data Science
• +۳ مورد دیگر

Kelian Dascher-Cousineau is an Assistant Professor in the Department of Geosciences at Utah State University. Their research focuses on earthquake physics, fault mechanics, and data science, with emphasis on earthquake forecasting and real-time aftershock analysis. They hold a NESRC Alexander Graham Bell fellowship and a NASA FINNEST fellowship. Research interests include understanding aftershock dynamics linked to mainshock attributes (e.g., depth, stress drop), real-time b-value analysis for seismic hazard assessment, and fault smoothing through cumulative offset studies. Current projects involve neural-temporal point processes for earthquake forecasting frameworks and fault-landscape interactions using remote sensing and landscape evolution models. Grants include NESRC and NASA funding. They are actively recruiting graduate students starting Fall 2025. Professional activities include presenting at SCEC plenary talks and maintaining a Google Scholar profile.

Rowan Candyمشاهده پروفایل

استاد

• Visual Development
• Amblyopia
• Strabismus
• +۵ مورد دیگر

Professor Rowan Candy serves as Executive Associate Dean for Academic Affairs and Professor of Optometry and Vision Science at Indiana University School of Optometry, with adjunct appointments in Psychological and Brain Sciences and membership in IU's Neuroscience and Cognitive Science programs. Appointed interim dean in July 2023, she leads academic affairs while maintaining an active NIH-funded research program. Ph.D. in Vision Science, University of California, Berkeley (1997) Membership of the British College of Optometrists (1990) B.Sc. in Optometry, University of Wales, Cardiff (1989) Dr. Candy's research focuses on visual development mechanisms, particularly how infants and children coordinate vision through ocular motor responses to prevent conditions like amblyopia and strabismus. Her work integrates optics, neuroscience, and experimental psychology to develop models of natural visual behavior in young children. She mentors graduate students, postdocs, and undergraduates in her laboratory, with continuous NIH funding since 2003. Her publication record demonstrates consistent contributions to understanding hyperopia-related strabismus risks, binocular vision in natural environments, and infant visual development mechanisms. Her scientific contributions have earned her recognition as a Fellow of the Association for Research in Vision and Ophthalmology. She remains active in the Vision Sciences Society and contributes to advancing clinical understanding of pediatric vision disorders through both laboratory research and academic leadership. Dr. Candy's mentoring extends to graduate students and postdoctoral researchers through her NIH-funded laboratory. Her work has significant implications for clinical interventions in pediatric optometry, with research directly informing practices for preventing vision disorders in children. She maintains strong interdisciplinary connections through her adjunct appointments in Psychological and Brain Sciences and Neuroscience programs. Her laboratory focuses on developing technical methods to understand how the developing brain coordinates visual experience through ocular motor responses, with recent work emphasizing natural environmental tasks for infants and young children.

• Neuroscience
• Visual Perception
• Neurophysiology
• +۳ مورد دیگر

Jason Samonds is a Research Fellow at the Center for Perceptual Systems, part of the College of Liberal Arts at the University of Texas at Austin. His work focuses on understanding neural mechanisms underlying visual perception, particularly binocular depth perception, disparity processing in the visual cortex, and the interplay between neural activity and behavioral outcomes. His research integrates experimental neurophysiology, computational modeling, and behavioral analysis to explore how sensory information is encoded and processed in the brain. Key research themes include the role of cooperative neural interactions in stereopsis, the impact of internal states on neural-behavioral covariations, and species-specific adaptations in visual processing. Samonds has contributed significantly to understanding how visual cortical circuits (e.g., V1) integrate binocular cues to construct 3D representations of the environment. His studies often involve rodent and macaque models to investigate fundamental principles of visual neuroscience. His publications from 2025–2012 reveal a sustained focus on topics such as disparity tuning deficits, neural coverage of visual scenes, and functional connectivity in V1 circuits. While no formal awards are listed, his extensive publication record reflects a deep engagement with cutting-edge questions in visual systems neuroscience. Samonds collaborates widely, employing methods like spike train analysis, computational modeling (e.g., Boltzmann machines), and behavioral assays to dissect neural coding mechanisms. His work bridges gaps between cellular-level responses and higher-order perceptual phenomena, contributing to both basic science and potential applications in neuroprosthetics or computational vision systems.

Yefeng Meiمشاهده پروفایل

استادیار

• Quantum Optics
• Nonlinear Optics
• Atomic Physics
• +۸ مورد دیگر

Yefeng Mei is an Assistant Professor in the Department of Physics and Astronomy at Washington State University (WSU), affiliated with the College of Arts and Sciences. His research focuses on trapped neutral atomic arrays, Rydberg states, and their applications in quantum optics, nonlinear optics, and quantum information processing. He holds a PhD from the Hong Kong University of Science and Technology (2020) and completed a postdoctoral fellowship at the University of Michigan. Research Interests: His work explores atomic, molecular, and optical (AMO) physics, including quantum optics, cavity QED, Rydberg-mediated interactions, many-body physics, and quantum simulation. He develops scalable quantum networks and quantum photonics technologies, emphasizing fault-tolerant architectures. Recent Contributions: His articles address topics like superatom dynamics, quantum coherence in phase-matched systems, and cold-atom-based quantum devices. Key themes include quantum entanglement, collective atomic excitations, and non-Hermitian optical phenomena. Professional Background: No scientific awards explicitly listed, though his academic trajectory suggests active engagement in high-impact research. Advising and grants details are currently unavailable, but his affiliation with WSU’s Department of Physics and Astronomy indicates participation in institutional research initiatives. Labs/Teams: His research group likely focuses on experimental AMO physics, leveraging optical lattices and cavity systems to advance quantum technologies, though specific lab names are not mentioned.

• Computational Biology
• Population Genetics
• Statistical Genetics
• +۴ مورد دیگر

Christoph Leuenberger is a Lecturer at the University of Fribourg, holding positions in the Department of Informatics and the Department of Physics, while also serving in the Dean's Office of the Faculty of Science and Medicine. His work bridges computational methods, population genetics, and ecological modeling. He specializes in statistical inference techniques, particularly Bayesian methods applied to genomic data and evolutionary processes. His research focuses on analyzing population trends, genetic diversity, and evolutionary dynamics across species. Key research interests include computational biology, population genetics, and the development of statistical tools for analyzing large-scale genomic datasets. He has contributed to studies on lactase persistence evolution, ancient DNA analysis, and predator population dynamics. His interdisciplinary approach integrates methods from computer science, mathematics, and ecology to address complex biological questions. Recent articles highlight his work in ecological monitoring, Bayesian inference for sex chromosome analysis, and evolutionary jump modeling in phylogenies. These studies underscore his expertise in bridging theoretical frameworks with practical data analysis in genetics and environmental science. No scientific awards or grants are explicitly mentioned in the provided information. He advises no students listed here but actively contributes to teaching and academic administration within the Faculty of Science and Medicine. Labs and teams associated with his work are not specified in the available data. His location is at PER 21 bu. C321, Bd de Pérolles 90, 1700 Fribourg, with contact details via email and ORCID.

Mary L Kraftمشاهده پروفایل

استاد

• Biomedical Engineering
• Chemical Engineering
• Cell Biology
• +۴ مورد دیگر

Mary L. Kraft is a Professor of Chemical and Biomolecular Engineering and Chemistry at the University of Illinois Urbana-Champaign, holding the Chien Family Professorial Scholar title. She also serves as Co-Chair of the Micro and Nanotechnology Lab and on the Institutional Biosafety Committee and Office of the Vice Chancellor for Research and Innovation. Her research focuses on combining engineering principles with advanced imaging technologies like NanoSIMS and Raman spectroscopy to study cell composition and biological function, particularly in biomedical applications. Key areas include stem cell differentiation for tissue engineering, drug delivery, and influenza virus replication mechanisms. Her work integrates computational statistics with chemical imaging for quantitative analysis at the single-cell level. Notable contributions include developing tools for non-invasive cell analysis and understanding lipid distributions in cellular membranes. She has received awards such as the AVS Prairie Chapter Early Career Research Award (2015) and the Walter A. Shaw Young Investigator Award (2014). Recent research trends emphasize lipid dynamics, membrane organization, and viral interactions with cellular membranes. Her publications span high-impact journals like ACS Nano and Biointerphases , with a focus on advancing analytical techniques for biomedical insights. Her lab, part of the College of Engineering, collaborates internationally and contributes to both applied and fundamental research in nanotechnology and cell biology.

• Fluid Mechanics
• Wind Energy
• Urban Flows
• +۷ مورد دیگر

Marco Placidi is Senior Lecturer in Experimental Fluid Mechanics at the University of Surrey's School of Mechanical Engineering Sciences, part of the Faculty of Engineering and Physical Sciences. He holds Chartered Engineer (CEng) status and is a Fellow of the Higher Education Academy (FHEA). His affiliations include the EnFlo Laboratory, Centre for Aerodynamics and Environmental Flow, and the Institute for Sustainability. Education: BEng (Aerospace Engineering) and MEng (Aeronautical Engineering) from Sapienza University of Rome (2006, 2010), followed by a PhD in Engineering Sciences from the University of Southampton (2015). Research focuses on urban flows, atmospheric stratification, wind power aerodynamics, and turbulent boundary layers. Key projects include the £1.8M EPSRC-funded FUTURE project on urban tall-building clusters and the NERC-funded ASSURE project on urban environmental flows. Collaborations span institutions like Imperial College London, University of Reading, and Transport for London. Teaching roles include leading the Aerodynamics and Flight Mechanics module and contributing to courses on renewable energy and wind power. Leadership roles: Head of Area 8 Health & Safety Forum, Sustainability Cluster Research Lead, and National Flying Laboratory Centre Coordinator. Member of the Royal Aeronautical Society and American Physical Society. Research highlights: Developed models for wind turbine wakes, explored cyclist pollutant exposure in urban settings, and advanced understanding of roughness-induced turbulence in boundary layers.

Hans-Georg Müllerمشاهده پروفایل

استاد

• Functional Data Analysis
• Fréchet Analysis
• Longitudinal Studies
• +۳ مورد دیگر

Hans-Georg Müller is a Distinguished Professor of Statistics at the University of California, Davis. His work focuses on functional data analysis, Fréchet analysis of random objects, and applications in longitudinal studies, brain imaging, and aging research. He has contributed to foundational methodologies such as Fréchet regression and Wasserstein-based statistical models. Key research interests include the statistical analysis of non-Euclidean data, covariance structures in high-dimensional spaces, and temporal dynamics of complex systems. Müller has published extensively in top-tier journals like the Annals of Statistics and IEEE Transactions on Information Theory. Awards: 2022 Rietz Lecture & Award (IMS), 2017 Humboldt Research Award, and multiple fellowships from prestigious societies. Advising: Recognized with the 2020 Graduate Program Advising & Mentoring Award at UC Davis. Publications: Over 200 papers, including influential works on Fréchet regression, Cox process regression, and longitudinal brain development studies. His research bridges theoretical statistics with applied domains, particularly in understanding neurodevelopmental processes and the statistical mechanics of aging biomarkers.