جست‌وجوی استاد و پژوهشگر

• Human-Computer Interaction
• Learning Sciences
• Educational Technology
• +۲ مورد دیگر

Jennifer Olsen, PhD, is an Assistant Professor of Computer Science at the University of San Diego since 2020. She holds a PhD, MS, and BS in Human-Computer Interaction and Cognitive Science from Carnegie Mellon University, followed by postdoctoral research at the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. Her research focuses on the intersection of human-computer interaction, cognition, and education, emphasizing collaborative learning and educational technology design from both learner and instructor perspectives. Education: PhD in Human-Computer Interaction, Carnegie Mellon University MS in Human-Computer Interaction, Carnegie Mellon University BS in Cognitive Science, Carnegie Mellon University Research Interests: Dr. Olsen explores how collaboration supports learning, designs technologies to enhance educational practices, and investigates gaze-based metrics for understanding collaborative problem-solving. Her work spans gamified robotics, AI-driven orchestration systems, and virtual reality applications in vocational training. She emphasizes learner-centered design and the integration of social robots and virtual agents in pedagogical settings. Grants/Advising: While no specific grants or advisees are listed, her prolific publication record indicates active involvement in educational technology research and development. Her work addresses challenges in classroom orchestration, multimodal data analysis, and accessibility in educational robotics. Labs/Teams: Collaborates with interdisciplinary teams focused on educational technology, human-robot interaction, and adaptive learning systems. Her research leverages tools like FROG orchestration graphs and eye-tracking technologies to develop practical classroom solutions.

• Robotics
• Robot Learning
• Machine Learning
• +۷ مورد دیگر

Lerrel Pinto is an Assistant Professor of Computer Science at the Courant Institute of Mathematical Sciences at New York University (NYU), where he leads the General-purpose Robotics and AI Lab (GRAIL) as part of the CILVR research group. His work bridges the gap between theoretical machine learning and practical robotics applications, with a focus on enabling robots to generalize and adapt in real-world environments. Dr. Pinto received his undergraduate degree from IIT Guwahati, followed by a PhD from the Robotics Institute at Carnegie Mellon University (CMU). He then completed a postdoctoral fellowship at the University of California, Berkeley before joining NYU as faculty. His research program centers on robot learning and decision making, with several key thrusts that demonstrate his innovative approach to robotics. Pinto's work emphasizes large-scale learning techniques that leverage both extensive data and sophisticated model architectures. A significant portion of his research focuses on representation learning for sensory data, particularly developing methods that enable robots to make sense of visual, tactile, and auditory inputs. His lab has made notable contributions to reinforcement learning algorithms that allow robots to adapt to new scenarios with minimal retraining. Pinto also champions open-source robotics , developing affordable robot platforms that democratize access to robotics research. Analysis of Pinto's recent publications reveals a strong trend toward multimodal perception in robotics, integrating visual, tactile, and auditory information to create more robust robot systems. His work increasingly focuses on zero-shot and few-shot learning capabilities, enabling robots to handle novel situations without extensive retraining. There's also a clear progression toward general-purpose robotics , moving away from task-specific solutions toward more flexible systems that can handle diverse real-world challenges. Dr. Pinto's scientific contributions have been recognized with several prestigious awards: Sloan Research Fellowship (2025) NSF CAREER Award (2024) RAL Early Career Award (2024) Best Student Paper Award at ICRA (2016) Outstanding Paper Award at MFM-EAI workshop at ICML (2024) Best Paper Award at NGSM workshop at ICML (2024) Best Student Paper Award at RSS (2023) As an advisor, Pinto has mentored numerous students who have gone on to impactful careers in both academia and industry. His former PhD student Denis Yarats co-founded Perplexity.AI, while Mahi Shafiullah became a postdoc at UC Berkeley and Meta AI. Many of his Masters students have pursued PhDs at top institutions like CMU, MIT, and Stanford, or joined leading robotics companies including 1X, Fauna Robotics, and NVIDIA. Pinto's lab has secured significant research funding, including the NSF CAREER award and likely other grants supporting his robotics research program. The General-purpose Robotics and AI Lab (GRAIL) that Pinto leads brings together a diverse team of researchers working on cutting-edge robotics challenges. The lab maintains strong collaborations with industry partners and other academic institutions, facilitating technology transfer and real-world impact. GRAIL's research spans multiple robotics platforms and focuses on developing algorithms that enable robots to learn from diverse experiences and generalize across environments.

Maja J Matarićمشاهده پروفایل

استاد

• Socially Assistive Robotics
• Human-Robot Interaction
• Assistive Technology
• +۷ مورد دیگر

Maja J Matarić is the Chan Soon-Shiong Chaired and Distinguished Professor of Computer Science at the University of Southern California's Viterbi School of Engineering, with courtesy appointments in Neuroscience and Pediatrics. She serves as founding director of the USC Robotics and Autonomous Systems Center, co-director of the USC Robotics Research Lab, and Principal Scientist at Google DeepMind. Previously, she held leadership roles as USC's interim Vice President of Research (2020-2021) and Vice Dean for Research (2006-2019). Her educational background includes: PhD in Computer Science and Artificial Intelligence from MIT (1994) MS in Computer Science from MIT (1990) BS in Computer Science from University of Kansas (1987) Matarić pioneers Socially Assistive Robotics (SAR) , a field her lab named, focusing on human-robot interaction that provides assistance through social rather than physical support. Her research targets critical health and wellness challenges including post-stroke rehabilitation, autism spectrum disorder therapy, cognitive exercises for Alzheimer's patients, ADHD academic support, and mental health interventions. She develops systems modeling user engagement, personality, and motivation, with extensive real-world deployments in schools, rehabilitation centers, and homes. Analysis of her recent publications reveals dominant themes in cognitive health robotics (2025 CHI paper on LLM-powered elder care), pediatric assistive technology (2025 IDC speech therapy review), and adaptive preference modeling (2025 HRI contrastive learning work). Her research consistently bridges machine learning with human-centered design for vulnerable populations. Major scientific recognition includes: ACM Athena Lecturer Award (2024) ACM Eugene L. Lawler Humanitarian Award (2024) ACM Fellow (2020) Presidential Mentoring Award (2011) Multiple society fellowships (AAAS, IEEE, AAAI) As a dedicated mentor, Matarić has championed underrepresented groups through CRA-W, placing numerous women in faculty positions. She leads USC Viterbi's K-12 STEM Outreach Program serving low-income Los Angeles schools and authored The Robotics Prime for student education. Her research has secured significant funding enabling real-world technology transfer, with documented impact in rehabilitation centers and homes through deployable SAR systems. Her Robotics Research Lab at USC drives innovation in embodied AI, with current projects spanning LLM-integrated elder care robots, ADHD academic companions, and autism therapy systems. The lab emphasizes co-design with end-users and rigorous real-world validation across diverse populations.

Alexandra Horowitzمشاهده پروفایل

دانشیار مدعو

• Dog Cognition
• Canine Behavior
• Olfactory Experience
• +۳ مورد دیگر

Alexandra Horowitz is a Senior Research Fellow and Adjunct Associate Professor at Barnard College. She has been teaching since 2004, specializing in dog cognition and olfactory research. Her academic roles span the Departments of English and Psychology, reflecting her interdisciplinary focus on animal behavior and human-animal interactions. Education: M.S. and Ph.D. in Cognitive Science from UC San Diego; B.A. in Philosophy from the University of Pennsylvania. Research interests include naturalistic observations of dog social play, testing anthropomorphic assumptions, and characterizing canine olfactory abilities. She has authored influential books like Inside of a Dog and Being a Dog , exploring how dogs perceive the world. Her work frequently appears in top journals and media outlets, including the New York Times and TED-Ed. Recent articles highlight studies on dog navigation, play behavior, and olfactory perception. She has been recognized as among the Top 2% of Cited Authors globally. Her presentations and lectures span academic conferences, museums, and public forums, emphasizing science communication.

Manolis Savvaمشاهده پروفایل

دانشیار

• Computer Graphics
• Computer Vision
• Robotics
• +۴ مورد دیگر

Roles & Affiliations: Manolis Savva is an Associate Professor at Simon Fraser University's School of Computing Science and holds a Canada Research Chair in Computer Graphics. He leads research in 3D scene understanding, with applications in graphics, vision, and robotics. Previously, he was a researcher at Facebook AI and Princeton University. Education: Ph.D. in Computer Science (2016), Stanford University, advised by Pat Hanrahan B.A. in Physics and Computer Science (2009), Cornell University Research Interests: His work focuses on analyzing, organizing, and generating 3D content, particularly for holistic scene understanding. Key areas include articulated objects, embodied AI, and datasets like ScanNet , Matterport3D , and Habitat . His methods drive applications in robotics, autonomous agents, and virtual environments. Publications Trends: Recent work emphasizes generative models (e.g., SINGAPO for articulated object parts), embodied AI benchmarks (Habitat), and multimodal scene analysis. His papers often address challenges in scalability, realism, and cross-modal fusion for 3D environments. Awards: CHCCS Early Career Researcher Award (2022) ICLR 2023 Outstanding Paper Award ICCV 2019 Best Paper Nomination (Habitat) Advising & Grants: Supervised over 15 graduate students, many advancing to top PhD programs and tech companies. Active in grants for embodied AI, scene understanding, and robotics. Labs/Teams: Leads the 3DLG (3D Learning Group) and GrUVi (Graphics and Vision) groups at SFU. Collaborates extensively with industry (e.g., Meta, NVIDIA) on AI-driven 3D research.

• Urban Planning
• Land-Use Regulation
• Urban Development
• +۷ مورد دیگر

Raphaël Fischler is a Full Professor and former Dean of the Faculty of Urban Planning and Landscape Architecture at the University of Montreal. He holds dual expertise in urban planning theory, history, and practice, with a focus on North American urban development, land-use regulation, and governance. His academic roles include teaching at McGill University and serving as Dean from 2018–2023, during which he led strategic initiatives like the Quartier de l’Innovation and addressed urban challenges such as housing affordability and metropolitan governance. **Education:** PhD in Urban Planning, UC Berkeley (1993) Master of City Planning, MIT (1987) Master of Science in Architecture, MIT (1987) Bachelor of Engineering, Eindhoven University of Technology (1984) **Research Interests:** Fischler’s work explores urban planning’s historical foundations, particularly zoning’s evolution, and integrates reflective practice into pedagogy. He advises on municipal projects and contributes to policy debates on density, public participation, and sustainable urbanism. His research bridges academia and practice, emphasizing ethical planning and community engagement. **Articles Trends:** His recent publications analyze zoning’s historical role, social justice in urban redevelopment, and governance challenges in Montréal. He critiques systemic issues like housing affordability and advocates for equitable urban policies. **Awards & Recognition:** Fellow of the Canadian Institute of Planners (2020) Émérite Member, Order of Quebec Urban Planners (2014) McGill Principal’s Excellence in Teaching Award (2013) **Grants & Teams:** He collaborates with institutions like the Centre de recherche interdisciplinaire en études montréalaises (CRIEM) and advises public agencies on metropolitan development. His work spans academic leadership, professional practice, and public advocacy, addressing urban challenges through interdisciplinary approaches. **Labs/Teams:** Affiliated with the CRIEM , focusing on Montréal’s urban history and contemporary planning issues. He mentors students in urban policy and design through studio courses and thesis supervision.

Alexander Mathisمشاهده پروفایل

استادیار

• Computational Neuroscience
• Machine Learning
• Sensorimotor Control
• +۶ مورد دیگر

Alexander Mathis is an Assistant Professor at the École Polytechnique Fédérale de Lausanne (EPFL) in the Brain Mind Institute (School of Life Sciences). His research bridges computational neuroscience and machine learning to decode sensorimotor behaviors and develop AI tools for behavioral analysis. Pure Mathematics MSc, Ludwig Maximilians University Munich PhD in Computational Neuroscience, Ludwig Maximilians University Munich His work focuses on understanding how the brain generates behavior through computational models and algorithms. Key contributions include the DeepLabCut toolbox, hBehaveMAE , and other frameworks for pose estimation, action segmentation, and brain-inspired AI. His group also explores proprioception, motor control, and neural coding theories. Recent publications include unsupervised hierarchical behavior modeling via masked autoencoders (ECCV 2024), synthetic basketball benchmarks (Shot7M2), and extensions of BABEL into hBABEL. These works highlight his interest in temporal hierarchies in behavior and scalable AI solutions for neuroscience. Scientific Honors Robert Bing Prize (2024) Eric Kandel Young Neuroscientists Prize (2023) Frontiers of Science Award (2023) Marie Skłodowska-Curie Postdoctoral Fellowship Studienstiftung des deutschen Volkes scholarship He advises PhD candidates in neuroscience and life sciences, leads courses on brain-like computation and software engineering for life sciences , and collaborates across AI4Science initiatives. His group actively participates in competitions, such as NeurIPS' MyoChallenge, where brain-inspired reinforcement learning algorithms have won awards.

Damien Charrierasمشاهده پروفایل

دانشیار

• Cultural Studies
• Media Theory
• Digital Arts
• +۷ مورد دیگر

Dr. Damien Charrieras is an Associate Professor at the School of Creative Media , City University of Hong Kong, where he serves as Program Leader for the Master of Art in Creative Media and deputy program leader for the PhD in Creative Media. His work bridges cultural studies, new media theory, and the intersection of financial technologies with artistic practices through the ACIM Laboratory for Interventions in Speculative Finance . Doctoral research on digital artists' trajectories in Montreal FRQSC Postdoctoral Fellowship at McGill University Research spans game engine design , datafication of creativity , blockchain in art , and post-anthropocentric creative processes . With over HK$3.14M in grants as Principal Investigator, he explores situated digital creativity in urban contexts, critical worldbuilding pedagogy , and the mediation of technical systems in cultural production. His publications in Cities , Organized Sound , and Human Relations analyze the reconfiguration of artistic practices through software infrastructures and automation paradigms. Scientific awards include: FRQSC Postdoctoral Fellowship

Karin Allor Pfeifferمشاهده پروفایل

استاد

• Physical Activity Measurement
• Childhood Obesity Prevention
• Exercise Physiology
• +۳ مورد دیگر

Karin Allor Pfeiffer is a Professor in the Department of Kinesiology at Michigan State University (MSU) and Director of the Institute for the Study of Youth Sports. She holds additional membership in the Center for Physical Activity and Health. With a Ph.D. from MSU, her research focuses on physical activity measurement methodologies and population health interventions, particularly among children and adolescents. Her work addresses obesity prevention, environmental design impacts on activity levels, and sociocultural factors influencing youth sport participation. Education: Ph.D. in Kinesiology from Michigan State University Her research interests emphasize: - Quantitative methods for physical activity assessment - Schoolyard redesign strategies and their health impacts - Cardiometabolic risk factors in pediatric populations - Longitudinal tracking of physical fitness and health outcomes Recent work explores accelerometer fragmentation metrics, GPS-linked activity tracking, and disparities in sedentary behavior across demographic groups. She has pioneered interdisciplinary approaches integrating spatial analysis, wearable technology, and policy evaluation. Key contributions include developing the Observational System for Recording Physical Activity in Children and advancing consensus methods for accelerometer data interpretation. Her studies frequently highlight socioeconomic and environmental determinants of health behaviors. Dr. Pfeiffer collaborates with public health agencies and urban planners to translate research into actionable policies. Her lab focuses on scalable interventions for underserved communities, leveraging community-engaged methods to address greenspace accessibility and safety concerns.

Aleksander Madsenمشاهده پروفایل

پژوهشگر

• Social stratification
• Segregation
• Intergenerational mobility
• +۵ مورد دیگر

Aleksander Madsen is a Researcher at the University of Oslo (UiO), affiliated with the Department of Sociology and Human Geography under the Faculty of Social Sciences. His primary research interests include social stratification, immigrant assimilation in labor markets, welfare state policies, and statistical methods. He holds a PhD from Oslo Metropolitan University and an MA from UiO. Education: PhD in Sociology, Centre for the Study of Professions, Oslo Metropolitan University (2014–2018) MA in Sociology, University of Oslo (2013) His research explores labor market integration of immigrants, gender disparities in male-dominated workplaces, and the impact of education-occupation mismatch on health outcomes. He has conducted longitudinal studies on long-term sickness absence and labor market trajectories using sequence analysis. Dr. Madsen has held postdoctoral and research positions at UiO and NIFU, and was a visiting scholar at Stanford University's SCANCOR (2024) funded by the Fulbright Foundation. His work spans interdisciplinary collaborations, including projects on workplace diversity, ethnic stratification, and policy evaluations. Awards: U.S. - Norway Fulbright Foundation Grant (2023–2024) His research group affiliations include the Social Inequalities and Population Dynamics team and the ORGMIGRANT project, investigating work organizations and immigrant assimilation. Recent publications address residential networks among immigrants, workplace ethnic diversity, and women’s attrition from male-dominated sectors.

Allen J. Scottمشاهده پروفایل

استاد پژوهشی

• Urban geography
• Regional development
• Globalization
• +۳ مورد دیگر

Allen J. Scott is a Distinguished Research Professor at the University of California, Los Angeles, with a joint appointment in the Department of Public Policy (School of Public Affairs) and Department of Geography. He has held prestigious positions at UCLA since 1994 and previously at the University of Toronto (1969–1994). His career spans over five decades, focusing on urban geography, regional development, and cultural economy. Education : BA (1961) from Oxford University; MA and PhD (1962, 1965) from Northwestern University. Research Interests include: Creative cities and cognitive-cultural capitalism Political economy of urbanization and globalization Industrial clusters and labor-intensive economies Human capital distribution in metropolitan areas Cultural landscapes and peripheral development Publication Trends (2005–2014) emphasize: Globalization's impact on low-technology industries Cognitive-cultural capitalism in urban contexts Human capital dynamics in metropolitan hierarchies Celebrity culture and urban glamour Creative field theories and urban policy implications Scientific Awards : 1986 Guggenheim Fellow 2003 Vautrin Lud Prize 2005 Meridian Book Prize 1999–2013: Chaires d’Excellence, Fellowships, and Doctor Honoris Causa 2008 Carol and Bruce Mallen Lifetime Achievement Award 2003 ISI Highly Cited Author

Megan S. Ryersonمشاهده پروفایل

استاد

• Transportation Planning
• Aviation
• Demand Forecasting
• +۴ مورد دیگر

Megan S. Ryerson holds the UPS Chair of Transportation and serves as Associate Chair of City and Regional Planning at the University of Pennsylvania's Stuart Weitzman School of Design. Previously, she was Associate Dean for Research (2018–2023), demonstrating sustained leadership in academic administration while maintaining an active research profile focused on transportation systems integration. Her educational credentials include: Ph.D. in Civil and Environmental Engineering, University of California, Berkeley (2010) B.Sc. in Systems Engineering, University of Pennsylvania (2003) Ryerson's research pioneers the integration of intercity transportation into urban planning frameworks, with foundational work in aviation infrastructure planning , airline demand forecasting , and transportation resilience . She investigates airport competition dynamics across megaregions, airline disaster recovery protocols, and fuel-efficient flight planning methodologies. Her scholarship actively bridges civil engineering and urban planning disciplines to design transportation systems that are inherently safe , efficient , and resilient against disruptions. Analysis of her 15 most recent publications reveals a pronounced shift toward transportation equity since 2022, particularly examining driver education accessibility ('driver training deserts') and bikeshare infrastructure allocation. This equity focus coexists with continued aviation research, while pandemic-era studies on transportation behavior (2020–2023) demonstrate methodological adaptability through quasi-experimental designs and real-world crisis response analysis. Her scientific recognition includes: UPS Chair of Transportation (prestigious endowed professorship) Dr. Ryerson has significantly expanded urban planning pedagogy by incorporating megaregional transportation systems into core curricula. Her leadership as former Associate Dean for Research reflects active engagement with funding agencies and research administration, though specific grant details aren't documented in source materials. Current work emphasizes translating research into equitable policy frameworks, particularly for vulnerable transportation populations.

Mark Leeمشاهده پروفایل

استاد مدعو

• Human Factors Engineering
• Healthcare Safety
• Data Analytics in Manufacturing
• +۳ مورد دیگر

Mark Lee is an Adjunct Professor in the People Analytics department at NYU’s Tandon School of Engineering, specializing in Technology Management and Innovation. He holds a Ph.D. in Engineering Psychology from Georgia Institute of Technology (1996). Currently, he serves as Head of Research, Analytics, and Business Development at UL ComplianceWire, focusing on pharmaceutical and medical device manufacturing training. His research leverages large datasets to improve healthcare safety through regulatory compliance and best practices. Courses taught include Human Factors Engineering, Workplace Design, and Predictive Analytics. Education: Ph.D. in Engineering Psychology, Georgia Tech (1996) Key Roles: Adjunct Professor, Head of Research at UL ComplianceWire Research Focus: Human Factors, Training Systems Design, Healthcare Compliance His work spans auditory display systems for aviation (e.g., 3D audio cockpit interfaces) and ergonomic design for industrial products. Recent projects emphasize data-driven solutions for regulatory challenges in life sciences. Publications highlight studies on visual search strategies, age-related cognitive performance, and application of signal detection theory in decision-making. He actively collaborates with industry and government entities, exemplified by the FDA-UL Cooperative Research Agreement.

Johan P Larssonمشاهده پروفایل

مدرس

• Economic geography
• Regional science
• Urban economics
• +۱ مورد دیگر

Dr. Johan P Larsson serves as a Lecturer in Economics and Public Policy within the Department of Land Economy at the University of Cambridge, concurrently holding a Fellowship and Director of Studies position in Land Economy. His academic profile bridges theoretical and empirical research in spatial economic phenomena, with emphasis on policy-relevant investigations of regional competitiveness and urban dynamics. His educational foundation includes: PhD from Jönköping University Dr. Larsson's research program centers on economic geography and regional science, specializing in urban economics and entrepreneurship. He examines how historical industrial structures, neighborhood effects, and policy interventions shape economic integration and innovation ecosystems. Methodologically, he combines quantitative analysis of large-scale datasets with natural experiments (e.g., pandemic-induced remote work) to isolate causal mechanisms in spatial economic processes. His recent publication trajectory (2021-2025) reveals consistent focus on three interconnected domains: evaluation of place-based policies (e.g., City Deals), analysis of the entrepreneurial state's role in innovation, and investigation of immigrant integration dynamics. These works predominantly utilize Scandinavian and English case studies while generating globally applicable theoretical insights, demonstrating methodological sophistication through spatial econometrics and policy counterfactuals. Recognition for his scholarly contributions includes: The JIBS Student Association’s Pedagogical Prize (2017) The Martin Beckmann Award from Regional Science International (2015) Jan Wallander scholar designation (2015) His teaching portfolio spans Microeconomics, Macroeconomics, Urban economics, and Applied statistics, reflecting his interdisciplinary expertise. While doctoral advisees aren't explicitly listed, his Director of Studies role indicates active undergraduate supervision within Cambridge's collegiate system. Current research appears focused on post-pandemic labor geography and mission-oriented innovation policy evaluation, though dedicated laboratories or formal research teams aren't mentioned in available materials.

Ranjay Krishnaمشاهده پروفایل

استادیار

• Computer Vision
• Natural Language Processing
• Robotics
• +۳ مورد دیگر

Ranjay Krishna is an Assistant Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington, where he co-directs the RAIVN lab and leads the computer vision team at the Allen Institute for AI (Ai2). His research intersects computer vision , natural language processing , robotics , and human-computer interaction . PhD in Computer Science from Stanford University (2021) Bachelor's and Master's degrees from Stanford and Cornell His work has received best paper , outstanding paper , and orals at top conferences like CVPR, ACL, CSCW, NeurIPS, UIST, and ECCV. Media outlets including Science , Forbes , and PBS NOVA have covered his research. He has been supported by grants from Google , Apple , NFS , and others. Ranjay advises a diverse group of 15 PhD and postdoctoral researchers , including Jieyu Zhang, Benlin Liu, and Cheng-Yu Hsieh. His teams have developed benchmarks like MemoryBench and The Colosseum , and his PathFinder framework achieved 74% accuracy in skin melanoma diagnosis—surpassing human experts by 9%. Notable contributions include: Perception Tokens for visual reasoning in MLMs SAM2Act for robotic manipulation with memory Synthetic Visual Genome dataset with 5.6M relationships