جست‌وجوی استاد و پژوهشگر

Gary Nihanمشاهده پروفایل

دانشیار مهمان

• teacher evaluation
• curriculum design in physical education and health education
• instructional strategies
• +۳ مورد دیگر

Dr. Gary Nihan serves as a Visiting Associate Professor in the Department of Sport and Movement Science at Salem State University . With a 36-year career in public education, he previously held leadership roles including K-12 Director of Health and Physical Education in Danvers Public Schools and administrative positions in Reading Public Schools. His expertise spans curriculum design , standards-based assessment , and bullying prevention in athletics . Education: Doctorate in Education (Curriculum Leadership) from Northeastern University Current Responsibilities: Supervising teacher candidates and teaching courses like First Responder and Fundamentals of Fitness Grant Work: Provides technical assistance for Carol M. White Pep Grants in Massachusetts and Maine Dr. Nihan's research focuses on evidence-based approaches to bullying prevention , instructional strategies in physical education, and pre-service teacher training . His publications and presentations emphasize sequential K-12 curriculum development and student growth measurement through NASPE PE Metrics. He also explores the integration of physical activity into community education programs. Recent works highlight interdisciplinary connections between physical education, health promotion, and behavioral science. His editorial contributions address systemic gaps in physical education programming and youth driver education policies. Dr. Nihan collaborates with institutions on grant management and sustainability strategies, while maintaining active teaching roles in both academic and community settings. Personal interests include cycling, skiing, golf, and fiction reading.

Alexandra Papoutsakiمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Eye Tracking
• Shared Gaze for Remote Collaboration
• +۵ مورد دیگر

Alexandra Papoutsaki is an Associate Professor of Computer Science at Pomona College since 2017. Her research focuses on Human-Computer Interaction , particularly in webcam-based eye tracking and shared gaze for remote collaboration . Ph.D. in Computer Science from Brown University M.Sc. in Computer Science from Brown University B.Sc. in Computer Science from Athens University of Economics and Business Her work spans personal informatics , crowdsourcing methodologies , and remote usability testing , with recent projects examining collaborative drawing interfaces, baby tracking reflection, and digital health communities. Earlier contributions include computational biology research in genome-wide survival analysis and pan-cancer mutation networks. Key trends in her publications include: Remote collaboration tools enhanced by eye tracking Personal data systems for health and creative domains Foundational work in crowdsourcing quality control Interdisciplinary approaches combining computer science with psychology and medicine Scientific recognition includes: NSF CRII Grant (2020-2022) Wig Distinguished Professor Award (2020) Best Paper at RECOMB (2013) She has developed multiple open-source platforms including WebGazer for scalable eye tracking and Remotion for mobile usability testing. Her research team has published extensively in top venues like CHI, IMWUT, and IJCAI.

Dustin Tingleyمشاهده پروفایل

استاد

• international relations
• climate change
• data science
• +۶ مورد دیگر

Dustin Tingley is a Professor of Government at Harvard University and holds a joint appointment at the Harvard Kennedy School of Public Policy . He serves as Interim Vice Provost for Advances in Learning and directs the Data Science and Technology Group and the Harvard Initiative on Learning and Teaching . He earned a PhD in Politics from Princeton and a BA in political science and math from the University of Rochester. Key Roles : Deputy Vice Provost (past), Chair of Harvard's Standing Committee on Climate Education Research Focus : Climate change politics, data science, causal inference, and international political economy His recent work explores the political economy of climate transitions , public opinion on carbon policies , and machine learning applications in social sciences . He co-founded ABLConnect , a repository for active learning pedagogy, and organized conferences on causal mechanisms , teaching with AI , and equitable classrooms . Awards : Gladys M. Kammerer Award (2015) for co-authored book Sailing the Water’s Edge Notable Publications : Uncertain Futures: How to Unlock the Climate Impasse (2023, with Alex Gazmararian) The Political Economy of the Clean Energy Transition (2025)

John C. Doyleمشاهده پروفایل

استاد

• Control Theory
• Dynamical Systems
• Network Science
• +۴ مورد دیگر

John C. Doyle is the Jean-Lou Chameau Professor of Control and Dynamical Systems, Electrical Engineering, and BioEngineering at the California Institute of Technology (Caltech), where he holds appointments in the Division of Engineering and Applied Science with primary affiliation in the Control and Dynamical Systems Department. His research bridges theoretical foundations with applications across biological, technological, medical, and ecological networks. He earned a BS and MS in Electrical Engineering from MIT (1977) and a PhD in Mathematics from UC Berkeley (1984), followed by consultancy at Honeywell Systems and Research Center (1976-1990). MIT: BS & MS in Electrical Engineering (1977) UC Berkeley: PhD in Mathematics (1984) Doyle's research centers on universal laws and architectures in complex systems, emphasizing robustness-efficiency tradeoffs, speed-accuracy tradeoffs (SATs), diversity-enabled sweet spots (DeSS), bowtie/hourglass structures, and evolvability. His work pioneers System Level Synthesis (SLS) for control systems with sparse, local, saturating, delayed, noisy, quantized, and distributed (SLSDNQD) components, integrating control theory, computation, communication, and machine learning to address challenges from neural networks to infrastructure resilience. Key concepts include virtualization, horizontal transfer, and virality in multiscale systems. Analysis of his publication trends reveals consistent interdisciplinary impact across neuroscience (brain connectivity modeling), systems biology (metabolic oscillations), network science (internet topology), and physics (turbulence, earthquakes), with recurring themes of robust-efficiency limits and architectural principles governing complex networks. His work demonstrates exceptional translation from abstract theory to practical tools like the Matlab Robust Control Toolbox and Systems Biology Markup Language (SBML). His scientific recognition includes: 1990 IEEE Baker Prize (ranked among top 10 most important mathematics papers 1981-1993) Three IEEE Automatic Control Transactions Awards (1998, 1999, 2021) ACM Sigcomm Paper Prize (2004) and Test of Time Award (2016) IEEE Control Systems Field Award (2004) Multiple early-career honors including IEEE Centennial Outstanding Young Engineer (1984) Doyle has mentored generations of students whose contributions include foundational software tools adopted globally. His research has secured sustained funding from NSF, NIH, and other agencies supporting theoretical advances in control frameworks and their applications to biomedical systems, network infrastructure, and environmental modeling. The SBML initiative exemplifies his group's impact in standardizing computational biology research. He leads a highly collaborative research ecosystem at Caltech that integrates engineers, biologists, neuroscientists, and computer scientists to develop universal principles for complex networks. Current efforts focus on translating theoretical insights into health technologies, resilient infrastructure, and climate-responsive systems through the application of robust-efficiency frameworks to emerging challenges in cyber-physical and biological domains.

Irem Dikmenمشاهده پروفایل

استاد

• Construction Project Risk Management
• Climate Risk and Resilience in Built Environment
• Digital Construction Technologies
• +۵ مورد دیگر

Professor Irem Dikmen is a leading academic in Construction Engineering and Management at the University of Reading, where she serves as School Director of Internationalisation in the Chancellor's Building. Her research integrates engineering, management, and information sciences to advance construction project risk management, particularly focusing on climate resilience, digital technologies, and social value in infrastructure systems. PhD, MSc, and BSc in Civil Engineering from Middle East Technical University Her work leverages systems thinking, artificial intelligence, and digital tools to develop decision-support frameworks for megaprojects and climate adaptation. Recent publications highlight innovations in NLP contract analysis, energy performance ontologies, and risk visualization techniques. She supervises students on topics spanning IoT lifecycle management, ESG risks, and NLP defect detection. Key collaborations include the Climate and Finance Research Cluster and Walker Institute , with contributions to digital construction technologies and sustainability risk assessment. Teaching modules include Construction Risk Management, Economics, and Business Organisation.

Daniel M. Wolpertمشاهده پروفایل

استاد

• Motor Control
• Computational Neuroscience
• Sensorimotor Learning
• +۴ مورد دیگر

Daniel M. Wolpert is a Professor of Neuroscience at Columbia University and Principal Investigator at the Zuckerman Institute. His research focuses on computational models of movement, integrating sensory cues and cognitive elements to understand motor control, memory, and rehabilitation strategies for cerebellar disorders. Key Research Areas: Sensorimotor integration, probabilistic inference, reinforcement learning, predictive modeling of movement, and aging effects on motor learning. Selected Awards: Royal Society Fellow (2012), Minerva Golden Brain Award (2010), Fulbright Scholarship (1992-1995). Recent publications highlight his work on contextual learning, motor memory formation, and the computational basis of sensorimotor uncertainty. His lab develops robotic interfaces to study human motor behavior and collaborates on clinical applications for movement disorders. Current opportunities include postdoctoral fellowships in sensorimotor control and decision-making.

Chenming Zhangمشاهده پروفایل

پژوهشگر ارشد

• Hydrology
• Groundwater hydrology
• Environmental Sciences
• +۷ مورد دیگر

Dr. Chenming Zhang is an Advanced Queensland Industry Research Fellow at the School of Civil Engineering, The University of Queensland. His research focuses on hydrological processes in coastal and terrestrial groundwater systems, with particular emphasis on evaporation-driven mass and heat transport in soils and tailings, and hydrogeochemical dynamics in aquifers and mine waste systems. Specializes in IoT-based environmental monitoring Develops numerical models for coastal aquifer dynamics Conducts field and laboratory experiments on tailings behavior Research interests span coastal hydrology, groundwater modeling, mine waste management, and environmental monitoring. He works on contamination transport, aquifer protection, and climate impacts on water systems. Recent publications analyze: Iron curtain formation in subterranean estuaries Sea water intrusion mechanisms Salinity dynamics in tidal wetlands Smart sewer monitoring systems Scientific awards include the prestigious Advanced Queensland Industry Research Fellowship. He supervises multiple PhD projects on mine waste hydrology and coastal aquifer management, with notable collaboration on: Evolution Mining's gold tailings projects ARC Discovery Projects on coastal processes Grange Resources' PAF cell instrumentation His work combines field measurements, laboratory testing, and computational modeling to address critical environmental challenges in mining and coastal zones.

Yi Dingمشاهده پروفایل

استادیار

• AI/ML Systems
• Sustainable Computing
• Computer Systems
• +۳ مورد دیگر

Yi Ding is an Assistant Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University, where they lead the STYLE (Sustainable computing Systems and LEarning) Lab. Dr. Ding joined Purdue in August 2023 after completing a postdoctoral fellowship at MIT CSAIL as an NSF Computing Innovation Fellow, mentored by Michael Carbin. During their postdoc, they also held a visiting position at Meta Infra Data Center to improve server maintenance efficiency in hyperscale datacenters. They received their Ph.D. in Computer Science from the University of Chicago, advised by Henry Hoffmann. Dr. Ding's research focuses on computer systems, computer architecture, and AI/ML, with strong emphasis on applications in sustainability and healthcare. Their work spans sustainable computing, including energy efficiency in datacenters and LLM serving, as well as healthcare applications such as mental health prediction and EEG analysis. Their recent publications demonstrate a strong trend toward addressing environmental impacts of computing, particularly in datacenters and AI systems, while also exploring innovative healthcare applications. Their research bridges systems, sustainability, and health domains, creating novel solutions for pressing societal challenges. Dr. Ding has received notable recognition including the Seed Funding for High-Impact Review Papers (2024), the Meta Research Award (2021), and was selected as a Computing Innovation Fellow by CRA/CCC (2020). Seed Funding for High-Impact Review Papers (2024) with Inez Hua 1st Place in Research Talk in CoE at Fall 2024 Undergrad Research Expo (awarded to Gavin Fortwendel) 2020 Computing Innovation Fellow by CRA/CCC Meta Research Award on Statistics for Improving Insights, Models, and Decisions (2021) Dr. Ding is actively recruiting self-motivated Ph.D. students interested in AI/ML systems research. They have secured funding for undergraduate research projects through DUIRI, focusing on sustainable AI computing and energy use in training autonomous vehicles. Their lab collaborates with various institutions including MIT, Meta, and interdisciplinary partners at Purdue. The STYLE Lab under Dr. Ding's leadership is actively engaged in multiple research initiatives addressing sustainable computing and healthcare applications, with strong industry connections and funding support from both internal university sources and external partners.

Nigel Shadboltمشاهده پروفایل

استاد

• Artificial Intelligence
• Web Science
• Open Data
• +۷ مورد دیگر

Professor Sir Nigel Shadbolt is Principal of Jesus College Oxford and Professor of Computing Science at the University of Oxford. He is Chairman and Co-founder of the Open Data Institute which he established with Sir Tim Berners-Lee. His career spans multiple prestigious institutions including the University of Southampton and University of Nottingham, where he held leadership roles in AI research. He has served in significant government advisory positions including as Information Advisor to the UK Prime Minister and member of the Public Sector Transparency Board. Nigel Shadbolt earned his undergraduate degree in Philosophy and Psychology from the University of Newcastle (1st Class Honours, 1978) followed by a PhD in Artificial Intelligence from the University of Edinburgh. His academic journey includes positions as the Allan Standen Professor of Intelligent Systems at Nottingham and leadership of the Web and Internet Science Group at Southampton before joining Oxford. Shadbolt's research spans the interdisciplinary field of Web Science, which he helped originate, focusing on human-centered AI, social machines, open data, and ethical considerations in technology. His work examines how humans and computers integrate at web scale to create novel applications, with recent emphasis on children's digital autonomy and privacy. He has published over 500 articles exploring topics from cognitive psychology to computational neuroscience, Artificial Intelligence to the Semantic Web. His notable contributions include the development of data.gov.uk and leadership in establishing Oxford's Institute of Ethics in AI. His 2018 book 'The Digital Ape: how to live (in peace) with smart machines' has been described as a 'landmark book' in the field. Knighted in 2013 for services to science and engineering Fellow of The Royal Society (FRS) Fellow of the Royal Academy of Engineering (FREng) Fellow of the British Computer Society (FBCS) Technology Pioneer status by the Davos World Economic Forum UK national BT Flagship IT Award As an advisor, Shadbolt has supervised numerous PhD students who have gone on to positions at Google DeepMind, the World Bank, and other prestigious institutions. His research has been supported by multiple grants including SOCIAM, KOALA, and ReTiPS projects. He co-founded Garlik Ltd, which was acquired by Experian, demonstrating his commitment to translating research into practical applications that benefit society. Shadbolt leads the Web and Internet Science research group at Oxford, focusing on social machines - applications that succeed at web scale by integrating humans and computers in novel ways. His work on the KOALA Hero Toolkit and CHAITok system addresses critical challenges in children's data autonomy on social media platforms, reflecting his commitment to ethical technology design.

• Latent Variable Modeling
• Machine Learning
• Measurement Equivalence
• +۳ مورد دیگر

Dr. David Goretzko is an Assistant Professor in the Department of Methodology and Statistics at Utrecht University's Faculty of Social and Behavioural Sciences. He leads the Measurement and Machine Learning Lab and specializes in the integration of data science techniques with psychometric theory. His academic journey includes: Ph.D. in Psychological Methods from LMU Munich (2020) M.Sc. in Statistics from LMU Munich (2018) M.Sc. in Psychology from LMU Munich (2016) B.Sc. in Physics from LMU Munich (2015) B.Sc. in Psychology from LMU Munich (2014) Dr. Goretzko's research primarily focuses on the intersection of machine learning and psychometrics. His work addresses critical challenges in factor analysis, measurement invariance, and model fit assessment. He develops innovative methods that combine traditional psychometric approaches with modern data science techniques, particularly in the areas of exploratory factor analysis trees, regularized factor analysis, and cost-sensitive machine learning applications in psychological assessment. His research has significant implications for improving the validity and reliability of psychological measurements across diverse populations. His recent publications reveal a strong trend toward integrating machine learning methodologies with traditional psychometric approaches. A significant portion of his work focuses on factor analysis techniques, particularly addressing the challenge of determining the appropriate number of factors. His research also extensively covers measurement invariance testing across multiple covariates using tree-based approaches, and he has made notable contributions to evaluating model fit in confirmatory factor analysis. The interdisciplinary nature of his work spans psychology, statistics, and computer science. Dr. Goretzko serves as an Associate Editor for the European Journal of Psychological Assessment and is an active reviewer for numerous prestigious journals including Psychological Methods, Behavior Research Methods, and Structural Equation Modeling. He also reviews grant proposals for major funding agencies such as the German Research Foundation (DFG), National Science Foundation (NSF), and Dutch Research Council (NWO). He currently holds a Project Grant from the German Research Foundation (DFG GO 3499/1-1) since 2021. His research program focuses on developing and validating new methodologies for psychological assessment that incorporate machine learning techniques while maintaining psychometric rigor. His work has practical applications in educational measurement, clinical psychology, and organizational assessment. Dr. Goretzko leads the Measurement and Machine Learning Lab at Utrecht University, which focuses on developing innovative methodologies that bridge the gap between traditional psychometrics and modern data science. The lab's research has particular relevance for improving measurement practices in cross-cultural research, educational assessment, and clinical psychology settings where measurement invariance and factor structure validation are critical concerns.

Sibel Adaliمشاهده پروفایل

استاد

• Trust in Networks
• Social Networks
• Databases
• +۵ مورد دیگر

Sibel Adali is a Professor in the Department of Computer Science at Rensselaer Polytechnic Institute’s School of Science. She joined RPI in 1996 after earning her PhD from the University of Maryland. Her academic roles include Associate Head and Graduate Program Director of the Computer Science Department (2015-2018) and currently serving as Associate Dean of Science for Research and Graduate Studies at RPI. She teaches foundational Computer Science courses in problem-solving and databases. Education: PhD from University of Maryland. Adali’s research focuses on trust modeling, social networks, information retrieval, and semantic analysis. She has led cross-cutting projects addressing cognitive science intersections with network theory, including roles as ARL-lead CTA Trust Coordinator and SCRNARC Associate Director. Her work explores misinformation mitigation, semantic shifts in language, and expert identification in social media ecosystems. Recent publications highlight her contributions to fake news detection, semantic change modeling, and AI-driven misinformation interventions. Her research trends emphasize interdisciplinary approaches combining machine learning, computational linguistics, and behavioral studies. Scientific Awards: Trustees' Outstanding Teacher Award (2015), Rensselaer Polytechnic Institute’s highest teaching honor. Adali actively collaborates on grants and projects through research centers including MOCA, IDEA, SCNARC, and ARL CTA partnerships. She advises students on advanced computational research and participates in military communications technology initiatives.

Bridget Rubenkingمشاهده پروفایل

دانشیار

• Emotional Processing of Media
• Cognitive Processing of Media
• Persuasion
• +۵ مورد دیگر

Bridget Rubenking is an Associate Professor in the Nicholson School of Communication and Media at the University of Central Florida. Her research focuses on the dynamic emotional and cognitive processing of mediated content from an empirical, social science perspective, with recent work analyzing physiological and cognitive responses to disgust-eliciting entertainment media and second-screen viewing behavior. Emotional Processing of Media Cognitive Processing of Media Persuasion Biological & Motivational Individual Differences Attention, Learning & Memory Entertainment Content – TV, Film, Interactive Health Messaging, Campaigns Discrete Viewing Choices & Behavioral Outcomes of Viewing Her scholarly contributions have been published in Journal of Communication , Motivation & Emotion , and Media Psychology . She was awarded the Broadcast Education Association’s New Faculty Research Grant in 2014. Dr. Rubenking teaches courses on media and society, communication theory, and quantitative research methods.

George Yinمشاهده پروفایل

استاد

• Stochastic Optimization
• Stochastic Control
• Stochastic Systems Theory
• +۴ مورد دیگر

George Yin is a Professor in the Department of Mathematics at the University of Connecticut (since 2020). Previously, he held the position of Distinguished Professor at Wayne State University (2017–2020) and has been a faculty member there since 1988. He earned his Ph.D. in Applied Mathematics from Brown University in 1987, along with M.S. degrees in Applied Mathematics and Electrical Engineering, and a B.S. in Mathematics from the University of Delaware (1983). His research focuses on stochastic optimization, control theory, stochastic systems, and numerical methods, with applications to biology, finance, and engineering. He has held editorial roles at journals such as SIAM Journal on Control and Optimization and has received prestigious awards including SIAM Fellow (2015), IEEE Fellow (2002), and IFAC Fellow (2014–2017). Key funding includes continuous NSF support since 1989, grants from the Air Force Office of Scientific Research, and others. His work spans theoretical advancements in stochastic systems and practical applications in energy systems, control engineering, and data science. He has advised numerous students and maintains active collaborations internationally. Labs/Teams: Goldenson Center for Actuarial Research, Quantitative Learning Center. Grants: NSF, AFOSR, ARO, NSA, and multiple institutional grants.

Kamran Sedigمشاهده پروفایل

استاد

• Human-Computer Interaction
• Information Visualization
• Cognitive Technologies
• +۳ مورد دیگر

Dr. Kamran Sedig serves as a Professor in the Department of Computer Science and the Faculty of Information and Media Studies at Western University, where he directs the Insight Lab. His research focuses on designing interactive technologies to enhance human cognitive activities involving data and information, including decision making, problem solving, and learning across domains like healthcare, finance, and scientific discovery. His academic credentials include: Ph.D. in Computer Science (Human-Computer Interaction) from The University of British Columbia under Prof. Maria Klawe, with dissertation nominated for the Governor General’s Gold Medal M.Sc. in Computer Science (Artificial Intelligence) from McGill University under Prof. Renato De Mori B.Sc. in Computer Engineering and Science from Concordia University as Valedictorian with The Most Great Distinction Sedig’s research synthesizes computer science, information science, cognition theory, and game studies to develop frameworks for interactive visual tools (IVTs). He investigates human-data interaction, visual reasoning, and interactivity design to support complex cognitive tasks like medical diagnosis, financial analysis, and scientific exploration. His human-centered approach emphasizes how computational tools and humans form coordinated cognitive systems for optimal task execution. Analysis of his recent publications reveals dominant trends in health informatics applications (drug safety analytics, electronic health records) and foundational work on human-information interaction frameworks. His visual analytics systems consistently bridge theoretical models with practical tools for ontology exploration, document triage, and explainable AI, demonstrating strong interdisciplinary collaboration across medical and computational domains. Key recognitions include: Governor General’s Gold Medal nomination for doctoral research Valedictorian honors at Concordia University As Insight Lab director, Sedig mentors graduate students through courses like Human-Computer Interaction, Information Visualization, and Design of Digital Cognitive Games. His teaching philosophy emphasizes how cognitive technologies mediate human thinking processes in professional and private contexts. While specific grant details aren’t provided, his lab’s sustained output in health analytics and visual interfaces indicates robust research funding. The Insight Lab operates as a collaborative hub for developing and evaluating IVTs, with current projects including VICTORIOUS for document scoping reviews and VISEMURE for multimorbidity analysis. Sedig’s team prioritizes empirical validation of how interaction design affects cognitive load and task efficiency in real-world data-intensive environments.

David Whitneyمشاهده پروفایل

استاد

• Visual Perception
• Cognitive Neuroscience
• Ensemble Perception
• +۶ مورد دیگر

David Whitney is a Professor of Psychology at the University of California, Berkeley , with affiliations in Cognitive Science and Neuroscience . His research focuses on visual perception, particularly how humans process information in cluttered environments through mechanisms like ensemble perception , serial dependence , and perceptual crowding . He employs techniques such as psychophysics, fMRI, and TMS to study these phenomena. Whitney's recent work examines serial dependence in schizophrenia, emotion perception in crowds , and medical image analysis for dermatology and radiology. His studies reveal how the brain uses dynamic predictive templates and motion cues to stabilize perception despite neural processing delays. Publications span Current Biology , Nature Reviews Psychology , and PLoS ONE , with a strong emphasis on interdisciplinary applications of perceptual science. Scientific contributions include foundational studies on visuomotor control , blind spot filling-in , and holistic face processing . His lab investigates perceptual stability across eye movements, spatial localization, and cross-modal interactions. Whitney has received grants such as NIH EY018216 to support his research on motion-dependent visual coding. Detailed information about his work is available on the Whitney Lab website .