جست‌وجوی استاد و پژوهشگر

Sheila McIlraithمشاهده پروفایل

استاد

• Artificial Intelligence
• AI Safety
• AI Alignment
• +۹ مورد دیگر

Sheila McIlraith is a Professor in the Department of Computer Science at the University of Toronto, holding the Canada CIFAR AI Chair at the Vector Institute and serving as Associate Director and Research Lead at the Schwartz Reisman Institute for Technology and Society. Her research spans AI safety, ethics, reinforcement learning, and knowledge representation, with a focus on human-compatible AI and long-term societal impacts. Her career includes six years as a Research Scientist at Stanford University and a year at Xerox PARC. McIlraith’s work has been recognized through ACM and AAAI fellowships, as well as prestigious awards like the SWSA 10-Year Award (2011) and the CAIAC Lifetime Achievement Award (2024). Research Interests: AI Safety and Alignment Human-Compatible AI Reinforcement Learning with Ethical Constraints Semantic Web Services Cognitive Robotics and Diagnostic Systems Probabilistic and Logical Reasoning Recent Contributions: Her work emphasizes ethical AI integration, such as the Embedded Ethics Education Initiative (E3I), and addresses challenges in long-term AI risks, multi-agent systems, and interpretable decision-making frameworks. Awards and Honors: ACM Fellow AAAI Fellow 2023 IJCAI-JAIR Best Paper Prize 2024 CAIAC Lifetime Achievement Award Labs and Teams: McIlraith leads initiatives at the Schwartz Reisman Institute and contributes to the Vector Institute, focusing on societal and ethical dimensions of AI technology.

• Learning Sciences
• Technology-Enhanced Learning
• Collaborative Learning
• +۴ مورد دیگر

Professor Nancy W. Y. Law is a leading scholar in Learning Sciences and Technology at the University of Hong Kong's Faculty of Education . She has served as Founding Director of the Centre for Information Technology in Education (CITE) (1998-2013) and currently holds the Chair of Learning Sciences and Technology . Her career spans over 25 years of international comparative studies, policy analysis, and large-scale educational innovation. Current roles: Associate Dean (Strategic Development), HKU Key affiliations: Sciences of Learning Strategic Research Theme (co-convener) Research Expertise Her work focuses on technology-enhanced learning , digital literacy , knowledge building communities , and multilevel educational change . She pioneered network models of teacher innovation and socio-technical frameworks for sustainable pedagogical transformation, particularly in STEM education and Cyberbullying prevention . Scientific Leadership With over 25 major research grants (2000-2023) exceeding HK$50 million, she leads projects like: Learning and Assessment for Digital Citizenship Jockey Club Self-directed Learning in STEM Design-Aware Learning Analytics A Fellow of the International Society of Learning Sciences and recipient of the HKSAR Humanities and Social Sciences Prestigious Fellowship , she has supervised numerous international comparative studies including SITES 2006, ICILS 2013, and longitudinal digital citizenship research (2019-2021).

Aleksandar Jeremicمشاهده پروفایل

دانشیار

• Biomedical Signal Processing
• Statistical Signal Processing
• Biometrics
• +۷ مورد دیگر

Aleksandar Jeremic is an Associate Professor in both the Electrical & Computer Engineering department and the McMaster School of Biomedical Engineering at McMaster University. His research focuses on biomedical signal processing, statistical signal processing, and biometrics, with applications in healthcare and biomedical systems. He holds a Dipl. Ing. from the University of Belgrade, and an M.S. and Ph.D. from the University of Illinois at Chicago. His expertise spans physiological signal analysis (e.g., ECG/EEG), medical imaging, and machine learning for biomedical applications. He has authored over 50 technical articles and two book chapters, and has been recognized with a teaching award from the McMaster Electrical and Computer Engineering Society (2018). He supervises graduate students in both theoretical and applied research areas. Dr. Jeremic teaches advanced courses such as Biomedical Signal Modeling and Processing and Advanced Probability and Random Processes , emphasizing practical applications of signal processing in healthcare. His work includes clinical implementations like neonatal seizure monitoring software and microwave imaging for breast cancer detection.

Belkis Ezgi Arikanمشاهده پروفایل

پژوهشگر

• Cognitive Neuroscience
• Neurophysiology
• Psychology
• +۴ مورد دیگر

Belkis Ezgi Arikan is a researcher at Justus Liebig University Giessen , affiliated with the Department of Psychology and Sports Science . Her work focuses on sensorimotor integration, tactile suppression, and neural mechanisms underlying action-outcome monitoring. She collaborates with Prof. Dr. Fiehler and Dr. Voudouris on project A4 (Predictive somatosensory processing during voluntary movements). Department: Psychology and Sports Science Collaborators: Dr. Dimitris Voudouris, Prof. Dr. Katja Fiehler Her research investigates: How the brain processes self-generated vs. externally generated sensory feedback Neural correlates of tactile suppression networks Role of cerebellum and angular gyrus in temporal recalibration Modulation of BOLD responses during action monitoring Recent publications reveal trends in predictive coding , sensorimotor recalibration , and neural suppression mechanisms across tactile, visual, and multisensory domains. Her work employs neuroimaging techniques like fMRI and behavioral paradigms to study self-motion perception and feedback processing. She contributes to understanding how the brain distinguishes self-initiated from external sensory events, with implications for motor learning and perceptual timing mechanisms.

Ji Zhuمشاهده پروفایل

استاد

• Statistical Machine Learning
• Statistical Network Analysis
• Health Sciences
• +۳ مورد دیگر

Ji Zhu is the Susan A. Murphy Collegiate Professor of Statistics at the University of Michigan, Department of Statistics. He holds affiliations with the Michigan Institute for Data Science (MIDAS) and the Michigan Integrated Center for Health Analytics and Medical Prediction (MiCHAMP). His research focuses on statistical machine learning, network analysis, and health science applications. Education: B.Sc. in Physics (Peking University, 1996), M.Sc. and Ph.D. in Statistics (Stanford University, 2000 and 2003). Notable awards include the NSF CAREER Award (2008), Fellowships from the ASA (2013) and IMS (2015), and recognition as a Web of Science Highly Cited Researcher (2014–2020). Research interests span statistical methodologies for networks, survival analysis, and high-dimensional data. He co-authored influential papers on community detection, network cross-validation, and latent space models. Current editorial roles include Editor-in-Chief of the Annals of Applied Statistics and Action Editor for the Journal of Machine Learning Research. Advising: Supervised over 50 students and postdocs, many now in academia and industry. Notable former advisees include Tianxi Li (University of Minnesota), Yuan Zhang (Ohio State University), and Weijing Tang (Carnegie Mellon University). Labs/Teams: Active in interdisciplinary projects at MIDAS and MiCHAMP, focusing on healthcare analytics and predictive modeling for diseases like hepatitis and cardiovascular outcomes.

Christopher Weidlichمشاهده پروفایل

استادیار بالینی

• Psychiatric Nursing
• Mental Health Disorders
• Healthcare Provider Well-being
• +۳ مورد دیگر

Christopher Weidlich is an Assistant Professor of Clinical in the School of Nursing and Health Studies at the University of Miami. His academic focus includes psychiatric nursing, mental health education, and healthcare provider well-being. He is involved in research addressing simulation-based education, mental health disorders in occupational groups such as fire investigators, and interventions to improve resilience among healthcare providers. His research interests span simulation modalities in psychiatric nursing education, organizational stigma's impact on mental health service utilization, and substance abuse trends like xylazine adulteration. He has also contributed to studies on military healthcare, including resilience programs for providers and PEMF therapy for chronic pain. Dr. Weidlich’s work is supported by his affiliation with the University of Miami’s School of Nursing and Health Studies, leveraging resources such as the Simulation Hospital Advancing Research and Education (S.H.A.R.E.®) facility. His research emphasizes practical applications in clinical settings and improving patient outcomes through innovative educational and therapeutic approaches.

Nancy M. Wellsمشاهده پروفایل

استاد

• Environmental Psychology
• Human-Environment Interactions
• Nature and Health
• +۷ مورد دیگر

Nancy M. Wells is a Professor in the Department of Human Centered Design and serves as the Senior Associate Dean for Research and Graduate Education in the College of Human Ecology at Cornell University. Her work bridges environmental psychology and public health, examining how built and natural environments impact human health and behavior across the lifespan. Dr. Wells received a joint PhD in Psychology and Architecture from the University of Michigan and completed National Institute of Mental Health (NIMH) post-doctoral training at the University of California, Irvine. Her educational background uniquely positions her to investigate the intersection of physical environments and human wellbeing through both psychological and architectural lenses. Her research focuses on how environmental contexts—from homes to neighborhoods to schools—affect health outcomes, cognitive functioning, and resilience. A central theme examines nature's role in human resilience, particularly how natural environments buffer against adversity and challenge. She has conducted influential work on school gardens and their effects on children's physical activity, dietary habits, and learning. More recently, she has pioneered research on nature and autism, conducting a randomized controlled trial examining natural environments' effects on autistic youth wellbeing. Analysis of Dr. Wells' recent publications reveals consistent focus on nature's health benefits, with strong emphasis on experimental methodologies including randomized controlled trials and natural experiments. Her work spans environmental psychology, public health, and education, with particular attention to vulnerable populations including low-income communities and children of color. NSF Funding for environmental health research USDA Funding for school garden studies Robert Wood Johnson Foundation Funding MacArthur Foundation Funding Senior Associate Editor of Environment and Behavior (4 years) Research Advisory Board of Children and Nature Network Board of Directors for reDirect Dr. Wells actively mentors undergraduate and graduate students through the Wells Lab, involving them in all research stages from data collection to publication. Her research has been supported by multiple significant grants examining housing quality effects on mental health, neighborhood design impacts on physical activity, and school garden interventions. She leads interdisciplinary research teams that integrate perspectives from environmental psychology, public health, landscape architecture, and education. The Wells Lab operates as an integrated research-teaching-outreach unit that develops practical yet rigorous studies to assess causal relations between environment and health, creates valid measurement tools, and identifies causal pathways. Current projects include examining nature's effects on autistic youth wellbeing in partnership with The Center for Discovery in New York, and investigating multi-sensory design in urban public spaces.

Jenna Wiensمشاهده پروفایل

دانشیار

• Machine Learning
• Artificial Intelligence
• Healthcare Data Analytics
• +۵ مورد دیگر

Jenna Wiens is an Associate Professor of Computer Science and Engineering at the University of Michigan's College of Engineering. She serves as Associate Director of the Artificial Intelligence Lab and co-Director of AI & Digital Health Innovation. Leading the MLD3 research group, her work focuses on machine learning and AI applications for healthcare data. PhD from MIT (2014) under John Guttag NSF CAREER Award recipient (2016) Humboldt Foundation Carl Friedrich von Siemens Award (2024) Her research addresses four key technical thrusts: Time-series analysis for predicting clinical outcomes Robust machine learning against spurious correlations Decision-making with causal inference and offline reinforcement learning Human-AI collaboration frameworks Notable methodological contributions include the FIDDLE preprocessing pipeline for clinical time-series data, foundational work on survival analysis, and novel approaches to model selection in healthcare reinforcement learning. Her work has led to real-world AI deployments in infection prevention and patient risk stratification. Scientific honors include: Forbes 30 Under 30 (2015) MIT Tech Review 35 Innovators Under 35 (2017) Sloan Research Fellowship in Computer Science (2020) Sarah Goddard Power Award (2023) Wiens collaborates with clinicians across disciplines, emphasizing clinician-in-the-loop AI systems and ethical implementation in healthcare workflows.

Albert Prestoمشاهده پروفایل

استاد پژوهشی

• air quality
• atmospheric particle studies
• climate resilience
• +۷ مورد دیگر

Albert Presto is a Research Professor in the Department of Mechanical Engineering at Carnegie Mellon University with a courtesy appointment in Civil and Environmental Engineering. He serves as Director of the Center for Atmospheric Particle Studies (CAPS) and is a Faculty Affiliate at the Steinbrenner Institute for Environmental Education and Research. His work spans multiple interdisciplinary collaborations across environmental science, engineering, and public health domains. Department of Mechanical Engineering, College of Engineering Center for Atmospheric Particle Studies (CAPS) Steinbrenner Institute for Environmental Education and Research Africa Clean Air Network Advisory Council Health Effect Institute's Energy Review Committee Presto's research focuses on pollutant emissions from energy extraction and consumption and their subsequent atmospheric transformations. His work examines how gas and oil wells emit methane, how vehicles emit carbon monoxide and particulate matter, and how these pollutants undergo oxidation in the atmosphere to create secondary pollutants like ozone and secondary particulate matter. His approach combines ambient measurements, laboratory experiments, source testing of pollution sources, and atmospheric models to provide a holistic view of pollutant emissions and transformations. His recent publications reveal a strong emphasis on air quality monitoring technologies, particularly low-cost sensor networks deployed internationally. There's a clear trend toward studying air pollution in African cities (especially Nairobi, Kampala, and Addis Ababa), examining spatial and temporal variability of particulate matter, and investigating the health impacts of air pollution exposure. His work increasingly integrates machine learning approaches for pollution forecasting and leverages international collaborations to address global air quality challenges. Member of Africa Clean Air Network Advisory Council Collaborator with US embassies worldwide on air quality data collection Quoted in The Guardian on inequality of air pollution exposure, specifically noting how people of color are more likely to be exposed to harmful air pollution Collaborated on research regarding chemicals released during the Ohio train derailment Presto actively collaborates with medical professionals to develop neighborhood-by-neighborhood studies of pollutant exposure and to understand relationships between emissions and health effects like childhood asthma. His work includes investigating racial-ethnic exposure disparities to airborne pollutants and examining how proximity to pollution sources like fast-food restaurants affects pediatric asthma outcomes. He has received seed funding from the Scott Institute for Energy Innovation for research in clean hydrogen production, AI hardware efficiency, and decarbonizing transportation. As Director of CAPS, Presto leads a research team focused on atmospheric particle studies with applications ranging from local Pittsburgh air quality to global monitoring initiatives. His lab develops and deploys advanced air quality monitoring technologies, including low-cost sensor networks that have been implemented in multiple cities across Africa. The CAPS research group works at the intersection of environmental engineering, atmospheric science, and public health to address critical air quality challenges worldwide.

Marina Agranovمشاهده پروفایل

استاد

• Experimental Economics
• Behavioral Economics
• Political Economy
• +۳ مورد دیگر

Marina Agranov is Professor of Economics at the California Institute of Technology (Caltech), affiliated with the Division of Humanities and Social Sciences. She directs research through the Ronald and Maxine Linde Institute of Economic and Management Sciences, Center for Social Information Sciences (CSIS), and Center for Theoretical and Experimental Social Sciences (CTESS), and serves as Research Associate at the National Bureau of Economic Research (NBER). Her academic credentials include a B.A. from St. Petersburg State Technical University (1999), M.A. from Tel Aviv University (2004), and Ph.D. from New York University (2010). She joined Caltech as Assistant Professor in 2010 and was promoted to full Professor in 2017. Agranov's research pioneers experimental and behavioral economics, focusing on strategic decision-making in bargaining games, social learning environments, network interactions, and information dynamics. Her work examines how individuals form beliefs and navigate tensions between personal goals and collective outcomes, often using controlled laboratory experiments to test theoretical predictions about human behavior under uncertainty. Her recent publications reveal a consistent methodological approach: blending game-theoretic models with experimental validation to investigate communication effects, randomization preferences, and institutional design. Key trends include analyzing how uncertainty impacts committee negotiations, how complexity influences egalitarian outcomes in legislative bargaining, and how information structures shape social learning on networks. Her scientific recognition includes: Associated Students of Caltech (ASCIT) Teaching Award (2017-18) Professor Agranov's research has secured significant institutional support through Caltech centers and NBER affiliation, with findings featured in major economics journals and Caltech news coverage including "Decision by Committee: How Uncertainty Shapes Negotiations" (December 2024) and "Experimental Economics in Theory and Practice" (July 2023). Her work on committee decision-making under uncertainty has direct implications for institutional design in political and corporate governance. She actively contributes to Caltech's research ecosystem through CSIS and CTESS, which facilitate interdisciplinary collaborations in social sciences and experimental methodology development.

Janna Parkerمشاهده پروفایل

استاد

• Retailing
• Digital Marketing
• Advertising
• +۴ مورد دیگر

Janna Parker is a professor in the Department of Marketing at James Madison University, specializing in digital marketing, retailing, and nonprofit marketing. With a career transition from political campaigns, she focuses on social media's role in personal and professional branding. Her research examines work-personal social media boundaries, employer governance policies, and volunteerism in nonprofit contexts. Education: Bachelor's in History (California State University Sacramento), Master's (Cameron University), Doctorate (Louisiana Tech) Teaching Interests: Digital marketing education, social media strategy, nonprofit marketing Her scholarly work spans social media governance, volunteer engagement, and retail dynamics, with recent emphasis on digital marketing pedagogy and cancel culture implications. Parker has contributed to academic journals through empirical studies and conceptual commentaries. Key article trends include: Digital marketing education evolution (2024) Social media governance in corporate and nonprofit contexts (2024) Online teaching satisfaction in higher education (2022) Volunteer brand community dynamics (2020) Consumer behavior frameworks (2019) Her media appearances include expert commentary on holiday retail strategies and social media research, reflecting practical applications of her academic work.

Lyle Ungarمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Natural Language Processing
• +۱۵ مورد دیگر

Lyle Ungar is a Professor at the Department of Computer and Information Science at the University of Pennsylvania . He is affiliated with multiple graduate groups, including Genomics and Computational Biology in the School of Medicine , Operations, Information and Decisions in the Wharton School , and Psychology in the School of Arts and Sciences . His research focuses on explainable machine learning , deep learning , and natural language processing for psychology and medical research , analyzing social media and sensor data to understand well-being, empathy, and stress. His work spans bioinformatics , applied economics , and group decision-making . Recent publications examine LLM-based tutoring , cross-cultural translation , and AI in palliative care , showing trends in reinforcement learning , mobile health , and health data analytics . He has contributed to Google Scholar , PubMed , and DBLP with over 15 papers since 2023. Scientific Awards : 2019 Alan I. Leshner Leadership Institute Public Engagement Fellow His students include Vitoria Aquino Guardieiro , Yihao Li , and co-advised researchers like Shreya Havaldar with Eric Wong. He leads projects at interdisciplinary centers such as the Annenberg Public Policy Center , Center for Cognitive Neuroscience , and Institute for Translational Medicine .

Wei Xiangمشاهده پروفایل

استادیار

• Economics
• International Economics
• Macroeconomics
• +۳ مورد دیگر

Wei Xiang is an Assistant Professor of Economics at the University of Michigan's Department of Economics, housed within the College of Literature, Science, and the Arts. He earned his Ph.D. in Economics from Yale University in 2024, focusing on international trade, macroeconomics, and environmental economics. His research bridges economic theory with applied analyses, addressing global trade dynamics, macroeconomic policies, and environmental sustainability. Education: Ph.D. in Economics, Yale University (2024). Research Interests: His work explores the intersection of international trade policies, macroeconomic stability, and environmental regulations. He examines how trade agreements influence economic growth and environmental outcomes, with a focus on empirical methodologies to assess policy impacts. Additionally, he investigates macroeconomic models to understand global economic fluctuations and their implications for sustainable development. Publications: His recent articles highlight contributions to vehicle communication systems, signal processing, and wireless technologies, reflecting interdisciplinary engagement with engineering applications. These include real-time prediction models for GPS errors and beamforming optimization in vehicular networks. Labs/Teams: Not explicitly stated, but his research collaborations likely involve interdisciplinary teams in economics, engineering, and environmental science.

Christopher Kananمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Deep Learning
• Continual Learning
• +۵ مورد دیگر

Christopher Kanan is a tenured Associate Professor of Computer Science at the University of Rochester, leading the AI Initiative within the Hajim School of Engineering & Applied Sciences. He holds secondary appointments in Brain and Cognitive Sciences, the Goergen Institute for Data Science and AI (GIDS-AI), and the Center for Visual Science. His research focuses on deep learning systems for artificial general intelligence (AGI), including continual learning, medical computer vision, and visual question answering. Previously, he was an Associate Professor at RIT’s Carlson Center for Imaging Science and a leader at Paige.AI, contributing to the FDA-cleared Paige Prostate system. Kanan earned his PhD from UC San Diego, completed postdoctoral work at Caltech, and worked at NASA JPL. Education: PhD in Computer Science, UC San Diego MS in Computer Science, University of Southern California Bachelor’s in Philosophy and Computer Science, Oklahoma State University Research Interests: Kanan’s work spans foundational AI capabilities like continual learning, medical imaging (pathology and radiology), multi-modal reasoning, and cognitive science-inspired models. His lab develops bias-robust AI systems and applies deep learning to healthcare and fusion research. Articles Trends: His recent work emphasizes out-of-distribution generalization, foundation models in pathology, and stability in continual learning. Key themes include AI applications in healthcare, model robustness, and neuroscience-inspired algorithms. Awards: NSF CAREER Award Senior Member, AAAI and IEEE DoE and NSF grants totaling $5M+ DARPA/ARL awards Advising & Grants: Mentored over 10 PhD students, including Robik Shrestha and Usman Mahmood. Secured grants for AI in nuclear fusion and medical imaging. Led RIT’s Center for Human-aware AI (CHAI) as Associate Director. Labs & Teams: Heads the University of Rochester AI Initiative, collaborates with Paige.AI, and leads teams advancing AI in pathology and robotics. His lab’s KLab (klab.cis.rit.edu) focuses on vision and learning systems.

Sebastian Raischمشاهده پروفایل

استاد

• Strategic Management
• Organizational Ambidexterity
• Artificial Intelligence in Organizations
• +۷ مورد دیگر

Sebastian Raisch is a Full Professor of Strategic Management at the Geneva School of Economics and Management (GSEM), University of Geneva, where he also serves as Director of the Executive MBA program. He is affiliated with the Institute of Management and holds a Ph.D. from the University of Geneva. His academic work is deeply rooted in understanding how organizations balance stability and change, particularly in the face of digital transformation. Research Interests: His primary areas of expertise include strategic management, organizational ambidexterity, organizational paradox, artificial intelligence in organizations, and digital transformation. His research investigates the dynamics of corporate growth and decline, strategic renewal, and the integration of human and artificial intelligence in organizational decision-making. He is especially interested in how firms navigate tensions between competing demands such as exploration and exploitation, automation and augmentation, and stability and innovation. Publications and Trends: His recent publications (2023–2025) show a strong shift toward the role of artificial intelligence in management, with a focus on hybrid human-AI systems, ethical AI, and the strategic implications of AI adoption. Earlier works center on ambidexterity, paradox theory, and corporate turnaround, establishing him as a leading scholar in these domains. Scientific Awards: Strategic Management Society’s Best PhD Paper Award Emerald Publishing Group’s Citation of Excellence Award Journal of Management’s Scholarly Impact Award Editorial and Professional Service: Sebastian Raisch serves as Associate Editor at the Academy of Management Review and sits on the editorial boards of the Academy of Management Journal and the Strategic Management Journal . He has advised numerous doctoral students and supervised research projects on organizational innovation and digital strategy, though specific names are not listed in the provided materials. He has not received explicit mention of research grants, but his extensive publication record suggests active research funding. Labs and Research Teams: While no formal lab is mentioned, Raisch leads or contributes to research initiatives within the Institute of Management at GSEM, particularly in strategic management and digital innovation. He collaborates with scholars across Europe and the U.S., including notable co-authors like J. Schad, S. Krakowski, and M. Tushman.