جست‌وجوی استاد و پژوهشگر

J. Michael Ruohoniemiمشاهده پروفایل

استاد

• Space Physics
• Ionospheric Physics
• Electromagnetics
• +۵ مورد دیگر

J. Michael Ruohoniemi is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. His research focuses on space physics, ionospheric dynamics, and HF radar technology. He leads the Virginia Tech SuperDARN group, managing radar sites like Blackstone and Fort Hays to study magnetosphere-ionosphere coupling. His work contributes to understanding space weather phenomena like geomagnetic storms and traveling ionospheric disturbances. Education: Ph.D., University of Western Ontario (1986); B.S., University of King's College and Dalhousie University (1981). Research Interests: Ionospheric physics, HF radar development, magnetosphere-ionosphere coupling, space weather monitoring, and MSTID dynamics. His group collaborates internationally via the SuperDARN network funded by NSF. Recent Research Trends: Recent articles emphasize MSTID analysis, solar flare impacts, geomagnetic storm effects, and machine learning applications. Key topics include ionospheric conductivity, Joule heating, and global circulation models. Affiliations: Virginia Tech SuperDARN Group, HamSCI collaboration, and international radar networks. Operates radar sites in North America and Antarctica.

• Cognitive Neuroscience
• Functional Neuroimaging
• Brain Mapping
• +۳ مورد دیگر

Sabrina Pitzalis is an Associate Professor at the University of Rome 'Foro Italico', Department of Human Motor Sciences and Health. She serves as Delegate for Gender Budget and Head of the SACS (Student Counselling and Help Desk). Her research focuses on cognitive neuroscience, functional neuroimaging, and brain mapping, with specializations in neural mechanisms of perception, sensorimotor functions, and brain plasticity induced by motor activity. She leads projects like the 2019 study on neuromuscular electrical stimulation effects. Her work integrates neuroimaging techniques to explore topics such as anticipatory brain activity and motion perception. Pitzalis teaches courses in sport psychology, neuroscience, and pedagogy, emphasizing the interplay between cognitive and motor systems. Her research highlights neural adaptations to sensory and motor interventions, including multifocal contact lenses and exoskeleton-assisted rehabilitation. Research Themes: Neural basis of perceptual and sensorimotor functions Brain plasticity and motor learning Anticipatory neural processing during action preparation Integration of visual and motor signals in spatial navigation Recent Contributions: Her articles (2022–2025) reveal insights into how brain circuits process self-motion, adapt to sensory interventions, and modulate during complex cognitive-motor tasks. These studies use advanced neuroimaging and electrophysiological methods to map functional brain dynamics. Ongoing work explores neurocognitive trade-offs in dual-task scenarios and the role of parietal cortex in visuomotor integration. Teaching and Leadership: Pitzalis contributes to degree programs in Sports Sciences (L22), Preventive Motor Activities (LM67), and Sports Technology (LM68). She promotes interdisciplinary approaches, combining neuroscience with sport pedagogy. Her leadership roles emphasize institutional quality assurance and student support initiatives. Labs/Teams: Collaborates within university labs specializing in motor neuroscience and neuroimaging, contributing to projects on neural adaptation mechanisms and clinical applications in rehabilitation.

Alexander Kirpichمشاهده پروفایل

استادیار

• Biostatistics
• Infectious Disease Epidemiology
• Molecular Epidemiology
• +۳ مورد دیگر

Dr. Alexander Kirpich is an Assistant Professor in the Department of Population Health Sciences at Georgia State University's School of Public Health. With a Ph.D. in Biostatistics from the University of Florida (2015) and prior postdoctoral experience in infectious disease modeling, he specializes in biostatistical analysis and epidemiological forecasting. Since joining Georgia State in 2019, his work integrates viral genomics, public health surveillance, and computational modeling to address emerging disease threats. Ph.D. in Biostatistics, University of Florida (2015) Master of Statistics, University of Florida (2011) Specialist Degree in Mathematics, Belarusian State University (2006) His research focuses on infectious disease modeling , including COVID-19 , HIV , mpox , and cholera , employing techniques like epidemic forecasting , genomic analysis , and statistical modeling . He also develops computational tools (e.g., StatModPredict) for public health applications and contributes to interdisciplinary projects on food security, smoking cessation, and pediatric health outcomes. Dr. Kirpich's recent work demonstrates trends in Integrating internet search data with traditional epidemiological models Applying machine learning to genomic datasets Developing agent-based stochastic models for disease transmission Quantifying excess mortality in politically constrained settings Contact: akirpich@gsu.edu | Office: Urban Life Building, Suite 407, Atlanta, GA

• Economic Theory
• Behavioral Economics
• Mechanism Design
• +۷ مورد دیگر

Shengwu Li is a Professor of Economics at Harvard University, specializing in economic theory and behavioral economics. His research focuses on designing simple and transparent economic systems, particularly addressing computational complexity challenges. He has contributed to mechanism design, auctions, and market design, emphasizing cognitive simplicity and bounded rationality. Key research interests include obviously strategy-proof mechanisms, cursed equilibrium extensions, and the effects of salary benchmarking. His work spans dynamic matching markets, fairness in bargaining, and the ethical dimensions of market design. Awards: Aliprantis Prize (2017), Exeter Prize (2018), EC'18 SIGecom Best Paper Award Notable Projects: Salary benchmarking studies, cursed equilibrium dynamics, and fair bargaining norms Literature Contributions: Maintains a curated page on obviously strategy-proof mechanisms and related literature His research integrates theoretical insights with empirical data, addressing real-world applications in labor markets, auctions, and negotiation systems.

Manuel J. Rodriguezمشاهده پروفایل

استاد

• Drinking Water Quality Management
• Land Use Planning
• Climate Change Adaptation
• +۳ مورد دیگر

Manuel J. Rodriguez is a Full Professor at the École supérieure d'aménagement du territoire et de développement régional (School of Land Use Planning and Regional Development) at Université Laval, Canada. Holder of the NSERC Industrial Research Chair in Drinking Water Quality Management and Monitoring, he specializes in integrated water quality management from watersheds to urban distribution systems. His work addresses source protection, spatio-temporal water quality analysis, and decision-support tools for municipalities. BSc in Civil Engineering MSc in Land Use Planning and Regional Development PhD in Environmental Engineering Postdoctoral work in England and France His research program emphasizes climate change adaptation, land use planning impacts, and machine learning applications for predicting water quality parameters. Recent publications focus on disinfection byproduct (DBP) management, contamination monitoring, and computational tools for water security. He has supervised over 80 doctoral, master's, and postdoctoral students. Professor Rodriguez has received the 2013 Université Laval Teaching Excellence Award and leads collaborations with entities like the City of Quebec, Canada First, and WaterShed Monitoring. His 2024-2025 articles highlight trends in climate-water interactions, DBP control, and AI-driven water quality assessment. NSERC Industrial Research Chair Active in 2025 publications Teaching excellence laureate He has held administrative roles including Director of CRAD, ÉSAD, and doctoral/master programs in Land Use Planning. His work spans 200+ peer-reviewed articles and 400+ conference presentations, addressing global water challenges from Arctic communities to tropical basins.

Marinko Sarunicمشاهده پروفایل

استاد مدعو

• Biomedical Imaging
• Optical Coherence Tomography
• Microscopy
• +۲ مورد دیگر

Marinko Sarunic is an Adjunct Professor at the School of Engineering Science , Simon Fraser University . He holds a PhD in Biomedical Engineering from Duke University and has been recognized as a Michael Smith Foundation for Health Research Scholar . His research focuses on biomedical imaging , particularly optical coherence tomography (OCT) , microscopy , and low-coherence interferometry , with applications in diabetic retinopathy , Alzheimer’s disease , and age-related macular degeneration . Dr. Sarunic's work spans adaptive optics , deep learning , and sensorless OCT systems , emphasizing clinical translation and open-source software development (e.g., OCTAVA ). His Google Scholar publications highlight multimodal imaging , vascular heterogeneity analysis , and AI-driven diagnostics for retinal diseases. His contributions include the Michael Smith Foundation for Health Research Scholar award. Though not currently teaching courses, his collaborations and leadership in retinal imaging and medical device innovation are pivotal for advancing non-invasive diagnostics in neurodegenerative and diabetic conditions .

Petros Dellaportasمشاهده پروفایل

استاد

• Bayesian Statistics
• Machine Learning
• Financial Econometrics
• +۷ مورد دیگر

Petros Dellaportas holds dual appointments as a Professor of Statistical Science at University College London (UCL) and a Professor of Statistics at the Athens University of Economics and Business (AUEB). His research focuses on Bayesian statistics, machine learning, financial econometrics, and dynamic pricing. He leads projects on topics such as Poisson processes for cybersecurity, reservoir computing for macroeconomic forecasting, and probabilistic fault detection in wind parks. His recent publications emphasize advancements in Bayesian methods, variational autoencoders, and spatio-temporal point processes. Dellaportas has supervised over 20 PhD students, contributing to areas like stochastic volatility models and inverse reinforcement learning. He co-founded Thales and Friends, an organization bridging mathematics and cultural activities, and organizes the Greek Stochastics workshop series on topics ranging from causal learning to computational statistics. Key projects include anomaly detection in VAT networks and scalable Gaussian process models. His work often integrates statistical theory with applications in finance, sports analytics, and environmental science. Dellaportas maintains active collaborations with institutions globally, advancing interdisciplinary research and methodological innovations in statistical science.

• Information Management
• Data Security
• Scientific Databases
• +۵ مورد دیگر

Marianne Winslett is a Professor at the University of Illinois' Siebel School of Computing and Data Science, affiliated with the Department of Computer Science since 1987. Her research focuses on data security, information management, and privacy in cyber-physical systems. She co-led the TrustBuilder project, advancing access control and authentication in open computing environments, and directed the Advanced Digital Sciences Center (ADSC) in Singapore from 2009–2013, addressing challenges in data analytics and smart grids. Her work includes pioneering methods to ensure privacy in biomedical data analysis. Education: Earned her doctorate in Computer Science from Stanford University and worked at Bell Labs before joining Illinois. Awards: ACM Fellow (2006), NSF Presidential Young Investigator (1989), University Scholar, and Stanley H. Pierce Award for advising. She has supervised 24 PhD theses and mentored numerous graduate students, particularly supporting female scholars. Research Interests Secure data management in distributed systems Privacy-preserving techniques for biomedical data Adversarial attack detection in cyber-physical systems like smart grids Elastic resource scheduling in cloud environments Query optimization under differential privacy constraints Key Contributions Developed frameworks for self-supervised learning in smart grid cybersecurity Pioneered causal mechanism transfer networks for mechanical system domain adaptation Advanced auto-scaling strategies for real-time stream processing (DRS/Elasticutor systems) Labs & Teams Former Director of the Advanced Digital Sciences Center (ADSC), a University of Illinois research outpost in Singapore focusing on data analytics and IoT applications.

• Neural Oscillations
• Computational Neuroscience
• EEG/MEG Analysis
• +۳ مورد دیگر

Thomas Donoghue is a researcher in the Department of Cognitive Science at the University of California, San Diego, specializing in neural oscillations and computational neuroscience methods. His work focuses on developing rigorous approaches for analyzing brain signals, particularly EEG and MEG data. Dr. Donoghue's research interests center on understanding the methodological considerations for studying neural oscillations, with particular emphasis on verifying the presence of oscillations, validating oscillation band definitions, and accounting for concurrent non-oscillatory aperiodic activity. His work addresses critical issues in the field such as temporal variability, waveform shape of neural oscillations, and separating spatially overlapping rhythms. His publication record demonstrates expertise in developing computational tools for neural signal processing, including contributions to the NeuroDSP software package. His research bridges theoretical neuroscience with practical methodological considerations for interpreting neural data. Dr. Donoghue has received funding support from the Halıcıoğlu Data Science Institute Fellowship, National Science Foundation (BCS-1736028), and National Institute of General Medical Sciences (R01GM134363-02). His collaborative work extends across multiple research groups at UCSD, including the Neurosciences Graduate Program, Halıcıoğlu Data Science Institute, and Kavli Institute for Brain and Mind.

Grant Van Hornمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Robotics
• +۲ مورد دیگر

Grant Van Horn is an Assistant Professor at the University of Massachusetts Amherst, affiliated with the College of Information and Computer Sciences. He specializes in computer vision and machine learning, focusing on applications in biodiversity and conservation. His work underpins popular tools like iNaturalist, Seek, and Merlin Bird ID. Prior to UMass, he held roles at AWS and the Cornell Lab of Ornithology. Education: PhD in Computer Science, California Institute of Technology (2019) MS in Computer Science, University of California San Diego (2014) BS in Computer Science, University of California San Diego (2012) Research Interests: Grant’s research bridges computer vision and machine learning to create systems that integrate human expertise and large datasets for environmental conservation. Key areas include wildlife species identification, acoustic monitoring, and ecological modeling. His work emphasizes leveraging technology for public engagement and scientific impact. Articles & Trends: Recent publications focus on audio geolocation, species range estimation, and satellite imagery analysis, reflecting his commitment to advancing tools for biodiversity conservation. His work often combines citizen science data with machine learning innovations. Awards: Computing Research Association Outstanding Undergraduate Researcher Honorable Mention (2012) Ben P.C. Chou Doctoral Prize (2019) Fast Company’s 2021 Recognition Advising & Labs: Grant advises students in computer science and conservation technology through the Computer Vision Research Laboratory. He has collaborated on projects like the iWildCam dataset and systems for salmonid counting in sonar data.

Simone Baumann-Pickeringمشاهده پروفایل

استاد

• Acoustic Ecology
• Marine Mammal Biology
• Deep-Sea Biology
• +۵ مورد دیگر

Simone Baumann-Pickering is a Professor of Biological Oceanography at the Marine Physical Laboratory, part of the Scripps Institution of Oceanography at UC San Diego. Her research focuses on acoustic ecology, marine mammal behavior, and conservation, with an emphasis on using passive acoustics to study species distribution, habitat utilization, and ecosystem dynamics. She leads the Scripps Acoustic Ecology Laboratory , which develops innovative methods for long-term acoustic monitoring and species classification. Education: PhD in Biology, Eberhard-Karls-Universität Tübingen, Germany M.S. in Biology, Eberhard-Karls-Universität Tübingen, Germany B.S. in Biology, Eberhard-Karls-Universität Tübingen, Germany B.S. in Media Engineering, Stuttgart Media University, Germany Research Interests: Acoustic ecology, adaptive strategies in changing environments, conservation management, habitat modeling, and species discrimination through sound. Her work bridges technology and ecology, leveraging machine learning and hydrophone arrays to address conservation challenges. Recent Research Trends: Her articles emphasize the integration of acoustic data with environmental variables (e.g., oceanographic conditions, climate fluctuations) to understand species behavior and distribution. Key themes include sperm whale demographics, beaked whale habitat utilization, and the impacts of vessel noise on marine ecosystems. Grants & Projects: She leads initiatives like SanctSound , which builds data systems for marine management decisions. Her work often involves collaboration with federal agencies and conservation organizations to inform policy. Labs & Teams: The Scripps Acoustic Ecology Laboratory develops tools such as Where’s Whaledo to advance array-based localization of marine animal vocalizations, enhancing conservation and research capabilities.

Tesca Fitzgeraldمشاهده پروفایل

استادیار

• Interactive Robot Learning
• Cognitive Robotics
• Human-Robot Interaction
• +۴ مورد دیگر

Tesca Fitzgerald is an Assistant Professor in the Department of Computer Science at Yale University. Her research focuses on interactive robot learning, enabling robots to adapt to novel situations through human-guided learning. She holds a Ph.D. from Georgia Institute of Technology (2020) and a B.S. from Portland State University. Her research interests include cognitive robotics, human-robot interaction, transfer learning, and active learning. She emphasizes robots' ability to reason about novel objects, tasks, and interactions by leveraging human teachers' domain knowledge. Key areas include structuring human-robot interactions to meet learning goals and modeling training data derived from these interactions. Notable honors include the National Science Foundation Graduate Research Fellowship (2014-2017), IBM Ph.D. Fellowship (2017), and Georgia Tech GVU Center Foley Scholars Award (2017). Her work has been presented at top conferences like IJCAI, AAMAS, and HRI. Fitzgerald’s research lab, the IQR Lab, explores inquiry-based methods for robot learning. Prior to Yale, she was a postdoc at Carnegie Mellon University, collaborating with Henny Admoni, Reid Simmons, and Aaron Steinfeld. She has organized workshops on learning and interaction at IROS and served on conference committees, including HRI 2021.

• Disaster Management
• Sustainability
• Globalization
• +۷ مورد دیگر

Roby Rajan is a Professor of Quantitative Methods in the Business Department at the University of Wisconsin-Parkside. He holds a B.S. in Mechanical Engineering from the Birla Institute of Technology and Science (India), an M.A. in Economics, and a Ph.D. in Industrial Engineering and Operations Research from Virginia Tech. His research spans interdisciplinary areas including disaster management, sustainability, globalization, corporate governance, and knowledge management. Dr. Rajan has published extensively across academic disciplines, with notable contributions to postcolonial theory, economic critique, and institutional reform. His work frequently integrates quantitative methods with cultural and political analysis. Education: B.S., Mechanical Engineering, Birla Institute of Technology and Science, India M.A., Economics, Virginia Tech Ph.D., Industrial Engineering and Operations Research, Virginia Tech Research interests emphasize systemic approaches to global challenges, including planetary-scale disaster management frameworks and critiques of neoliberal economic policies. His recent work explores intersections between cultural studies and economic systems, particularly in postcolonial contexts. Earlier publications address corporate ethics, environmental management, and institutional knowledge systems. Advising and grants: No formal advisees listed. His research funding sources are not detailed in available records. Labs/teams: No specific research groups or laboratories mentioned in profile.

Rachael Z. DeLueمشاهده پروفایل

استاد

• Environmental Humanities
• Indigenous studies
• History of art and visual culture
• +۶ مورد دیگر

Rachael Z. DeLue is the Christopher Binyon Sarofim ’86 Professor in American Art at Princeton University, serving as Chair of the Department of Art and Archaeology and Director of the Princeton Humanities Initiative. She is jointly appointed in the Effron Center for the Study of America and affiliated with the High Meadows Environmental Institute, Native American and Indigenous Studies Initiative, and Program in Media and Modernity. Education: B.A. from Swarthmore College, Ph.D. from Johns Hopkins University Prior Positions: Taught at University of Chicago and University of Illinois, Urbana-Champaign DeLue’s research sits at the crossroads of American/transatlantic art history, science, and knowledge theory. Her work interrogates contested geographies of identity, transcultural representations of America, and the visual history of scientific illustration and data visualization. Current projects focus on climate, landscape, and the ontological challenges of visualizing abstract/conceptual phenomena. Recent publications reveal trends in ecocritical art (e.g., Shoreline Landscapes and the Edges of Empire ), scientific illustration (e.g., Darwin’s Diagram ), and identity/politics in visual culture (e.g., Measuring Native America ). Scientific Awards: Behrman Award for the Humanities As an educator, DeLue pioneered museum-based courses with fieldwork components, including a Princeton Battlefield excavation with Nathan Arrington and a Great Salt Lake field seminar on Robert Smithson’s Spiral Jetty. She has served on editorial boards of The Art Bulletin and American Art , and currently advises the Archives of American Art Journal.

• Population Genetics
• Conservation Biology
• Ecology
• +۵ مورد دیگر

Janet Loxterman is a Professor and Department Chair in Biological Sciences at Idaho State University. Her research integrates population genetics with conservation biology and ecology, focusing on molecular techniques to address conservation challenges in both aquatic and terrestrial ecosystems. Ph.D. in Biology (Conservation Genetics), Idaho State University (2001) M.S. in Biology, Virginia Commonwealth University (1995) B.S. in Behavioral Neuroscience, Lehigh University (1992) Her work emphasizes combining ecological and genetic data to understand population structure, critical for conservation strategies like species protection, reintroduction programs, and habitat restoration. Key areas include fish genetics, hybridization analysis, and wildlife biogeography. Recent publications highlight advancements in fish identification, DNA extraction methods, climate adaptation frameworks, and hybridization studies in trout. Her lab at Life Sciences 434 addresses watershed evolution, human impacts, and genetic diversity trends across species like cutthroat trout, dwarf mistletoe, and pumas.