جست‌وجوی استاد و پژوهشگر

Michael Hornمشاهده پروفایل

استاد

• Educational Technology
• Computational Literacy
• Interactive Learning Environments
• +۳ مورد دیگر

Michael S. Horn is a Professor at Northwestern University with a joint appointment in Computer Science and the Learning Sciences. He directs the Tangible Interaction Design and Learning (TIDAL) Lab and coordinates the Learning Sciences PhD Program. His work focuses on leveraging interactive technology to design innovative learning experiences, such as tangible programming languages (e.g., Tern) and music-coding platforms (e.g., TunePad). He holds a PhD from Tufts University and has collaborated with institutions like the California Academy of Sciences and the Museum of Science, Boston. Education: PhD in Computer Science, Tufts University MS in Computer Science, Tufts University BS in Computer Science, Brown University Research Interests: Dr. Horn explores how emerging technologies can create engaging learning environments. His projects include museum exhibits (e.g., DeepTree, Build-a-Tree), educational tools for computational literacy (e.g., TunePad, Strawbies), and collaborative design with educators. Recent work emphasizes integrating music and coding to foster computational thinking. Publications: His recent work addresses computational thinking in STEM education, AI-driven qualitative analysis, and hybrid music-coding practices. Themes include equitable participation, teacher professional development, and immersive AR/VR tools for learning. Awards: Recipient of the 2018 Edith Ackermann Award for innovative work in child-computer interaction. His research has led to commercial products like Osmo Coding and Kibo Robotics. Grants & Labs: Principal investigator on NSF grants (e.g., #1612619, #1451762) and collaborator with labs like the Center for Connected Learning (CCL) and the Collaborative Technology Laboratory (CollabLab).

David Mimnoمشاهده پروفایل

دانشیار

• Natural Language Processing
• Machine Learning
• Computational Social Science
• +۴ مورد دیگر

David Mimno is an Associate Professor and Chair of the Department of Information Science at Cornell University. He holds a PhD from the University of Massachusetts Amherst and previously worked at the Perseus Project and Princeton University. His research focuses on computational social science, natural language processing, and historical text analysis. Mimno is known for developing the MALLET toolkit, a widely used Java-based platform for machine learning in text processing. He teaches courses such as INFO 4940: How LLMs Work and INFO 6150/CS 6788: Advanced Topic Modeling. His work has been supported by the Sloan Foundation, NEH, and NSF. Mimno advises PhD students in Information Science and Computer Science, emphasizing interdisciplinary research at the intersection of computing and humanities/social sciences. He also contributes to initiatives like AI for Humanists, making large language models accessible for text-as-data research. Bachelor’s degree: Not explicitly stated in text PhD: University of Massachusetts Amherst Research Interests: Mimno explores large language models, topic modeling, cross-lingual semantics, and ethical AI applications in humanities and legal domains. His recent work addresses data curation practices for language models, LLM memorization of poetry, and generative AI’s societal impacts. He co-authored reports on generative AI in academic research and education. Grants & Collaborations: His projects include the Text as Data (TADA) conference and collaborations on generative AI law workshops. Mimno’s MALLET toolkit supports document classification, clustering, and topic modeling, with applications in cultural analytics and computational historiography.

Peter Gordonمشاهده پروفایل

دانشیار

• Language Acquisition
• Developmental Neuroscience of Language and Cognition
• Cross-cultural Studies of Numerical Cognition
• +۳ مورد دیگر

Peter Gordon is an Associate Professor of Neuroscience and Education and Cognitive Science in Education at Teachers College, Columbia University. He directs the Language and Cognitive Neuroscience Lab and holds affiliations with Biobehavioral Sciences, Human Development, and other departments. His research focuses on language acquisition, developmental neuroscience, cross-cultural numerical cognition, and MRI-based studies of language processing. Dr. Gordon earned a B.A. (Hons) in Psychology from the University of Stirling (Scotland) and a Ph.D. in Psychology from MIT. His fieldwork includes extensive studies with the Piraha in Amazonia, Brazil, and the Kadiweu in Mato Grosso do Sul, Brazil. His research interests span infant event representations, behavioral genetics of language, and the interplay between language structure and cognitive development. Notable contributions include work on anumeric cultures and the linguistic relativity hypothesis. Publications highlight cross-cultural studies, morphological processing, and cognitive neuroscience of language. He has conducted influential research on numerical cognition in Amazonian cultures and the genetic influences on language acquisition. Contact: pg328@tc.columbia.edu | Office: 1152 Building 528 | Lab: [Link Provided].

Laurent DUPONTمشاهده پروفایل

پژوهشگر

• Innovation Engineering
• Sustainable Cities
• Collaborative Innovation
• +۴ مورد دیگر

Laurent DUPONT is a Research Engineer and Co-coordinator of the IUVTT Master’s program at ENSGSI (École Nationale Supérieure de Géologie et de Sciences Industrielles), part of the Groupe INP in Nancy, France. He also serves as Scientific Manager of the Lorraine Fab Living Lab. His work focuses on user-driven innovation, smart and sustainable territories, collaborative engineering, and immersive environments. He holds a PhD in Industrial Systems Engineering from INPL (2009), a DEA (2004), and a degree in Industrial Systems Engineering (2003) from ENSGSI. Research interests include innovation lab strategies, open innovation spaces, territorial resilience, and digital twin applications in manufacturing. He leads projects like INEDIT, exploring co-design frameworks and circular economy solutions. His articles highlight trends in collaborative innovation networks, systemic impact mapping, and the integration of extended reality in industrial contexts. Key contributions include frameworks for evaluating territorial resilience and tools for monitoring innovation lab networks. He has been involved in initiatives such as the DHDA Project for resilience assessment and the Smagrinet project on smart grid training. His work bridges academia and practice through participatory methods and cross-sector collaborations. Current projects emphasize Industry 5.0, open manufacturing, and community-driven innovation.

• Wearable Sensors
• Smart Garments
• Sustainable Textiles
• +۵ مورد دیگر

Dr. Shirley Coyle is an Assistant Professor in the School of Electronic Engineering at Dublin City University (DCU) and Programme Chair for the BSc Global Challenges. She holds a BEng in Electronic Engineering from DCU (2000) and a PhD in Biomedical Engineering from NUI Maynooth (2005). Her career includes roles as a Telecoms Engineer at Siemens, Research Fellow at the National Centre for Sensor Research, and Team Leader of Wearable Sensors in the INSIGHT Centre for Data Analytics. She also studied part-time at the Grafton Academy for Fashion Design and later founded a consultancy in wearable technologies. Her research focuses on smart garments, wearable sensors, and sustainable textiles, with applications in healthcare, sports performance, and S.T.E.A.M. integration. Key interests include developing wearable chemical sensors, energy-autonomous sensing systems, and IoT-enabled rehabilitation devices. She has pioneered work on wearable sensors for monitoring chronic diseases, athlete training, and home rehabilitation using VR. Dr. Coyle’s work spans interdisciplinary collaboration, combining biomedical engineering with textile design. Her contributions include innovations in electrospun textiles, self-powered sensors, and sensor integration with microfluidics. She has held leadership roles in DCU’s Governing Authority and promotes STEM education through design-focused initiatives.

France Bouthillierمشاهده پروفایل

دانشیار

• Competitive Intelligence
• Information Management
• Healthcare Information Systems
• +۴ مورد دیگر

France Bouthillier is an Associate Professor and Associate Dean of Graduate and Postdoctoral Studies at McGill University's School of Information Studies. She holds a PhD from the University of Toronto and multiple advanced degrees in library science, administration, and education from Quebec institutions. Her research focuses on competitive intelligence, healthcare information systems, and small business information needs. She has led major grants including a SSHRC-funded study on children’s cyber-safety and CIHR projects on evidence dissemination in healthcare. Education: PhD, Faculty of Information Studies, University of Toronto MBSI, École de bibliothéconomie et des sciences de l'information, Université de Montréal C. Admin, Département des sciences de l'administration, UQAM BEd, Département des sciences de l'éducation, UQAM Research Interests: Dr. Bouthillier investigates digital resource assessment in healthcare, cross-cultural competitive intelligence practices, and information needs of marginalized communities. She emphasizes collaborative information monitoring and user-centered design in information systems. Her work bridges theory and practice, addressing gaps in evidence-based decision-making. Grants & Awards: Competia Award (2003) for co-authored book on CI software assessment SSHRC Standard Research Grant (2005-2008) on CI technology use CIHR grants for healthcare evidence dissemination (2006, 2008) Professional Involvement: Editorial Board member of the Journal of Information Science Theory and Practice, ASIST member, and SSHRC grant reviewer. She co-developed the eSRAP system for patient-oriented research monitoring. Her lab focuses on interdisciplinary projects in information visualization and collaborative tools.

Pearl Puمشاهده پروفایل

مدرس ارشد

• Human-Computer Interaction
• User-Centric Design of Intelligent Systems
• Recommender Systems
• +۳ مورد دیگر

Pearl Pu is a Senior Lecturer and Researcher at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Computer and Communication Sciences and the PFP Group. Her work focuses on integrating human-centric principles into AI systems. Human-Computer Interaction User-Centric Design of Intelligent Systems Recommender Systems Neural Generation of Empathetic Dialogs Emotion-Aware Intelligent Systems AI Ethics She supervises doctoral students in projects related to interaction design, emphasizing 'goal-directed design' and 'interaction design' methodologies through collaborative team challenges. Pearl Pu Lab (GR-Pu): Research unit at EPFL's School of Computer and Communication Sciences Active member of multiple interdisciplinary groups including GR-SCI-IC, GR-PU, and SIN-ENS

Michael Smithمشاهده پروفایل

استاد

• Ethics
• Moral Psychology
• Philosophy of Mind
• +۳ مورد دیگر

Michael Smith is the McCosh Professor of Philosophy at Princeton University. He holds a DPhil from Oxford University (1989) and has been a faculty member since 2004, previously at the Australian National University. His research focuses on ethics, moral psychology, philosophy of mind, political philosophy, and philosophy of law. Smith’s work integrates constitutivist theories of practical reason with analyses of moral agency. He has contributed to debates on moral rationalism, the nature of reasons for action, and the relationship between rationality and normativity. Education: MA, Monash University (1980); BPhil (1983), DPhil (1989), University of Oxford Smith’s scholarship emphasizes the interplay between ethical theory and psychological explanations of agency. Recent publications explore topics like carbon capture technologies, cultural clashes in moral reasoning, and probabilistic forecasting in oceanography. His philosophical contributions address foundational questions in meta-ethics, including the ‘moral problem’ and the implications of constitutivism for normative frameworks. He advises on interdisciplinary projects at the intersection of philosophy and emerging technologies. Notable research trends include applying philosophical analysis to environmental ethics and developing frameworks for resolving moral dilemmas through rational agency models. His work often bridges analytic philosophy with empirical inquiries in psychology and social science.

Mark Bockoمشاهده پروفایل

استاد

• Audio and Acoustic Signal Processing
• Computer Audition
• Sensors and Transducers
• +۳ مورد دیگر

Mark Bocko is a Distinguished Professor of Electrical and Computer Engineering at the University of Rochester, affiliated with the Hajim School of Engineering & Applied Sciences. He holds roles as Director of the Center for Emerging and Innovative Sciences (CEIS) and Director of Audio & Music Engineering. He earned his PhD in Physics from the University of Rochester in 1984, focusing on gravitational wave detectors. His research spans audio signal processing, sensors, superconductivity, and quantum computing. Notable contributions include flat-panel loudspeaker development, non-contact ECG sensors, and quantum coherence studies in Josephson junctions. Research interests include audio and acoustic signal processing, computer audition, and sensor technologies. His work integrates interdisciplinary approaches, combining electrical engineering, physics, and computer science. Awards include the 2012 Goergen Award for Teaching and Mercer Brugler Distinguished Teaching Professor (2008–2011). Recent publications address modal crossover networks for loudspeakers, vibrational touch sensing, and room impulse response modeling. He has advised PhD students on topics like spatial audio rendering and musical vibrato analysis. His labs focus on advancing audio engineering and smart sensor systems through collaborative industry partnerships.

• Service Science
• Digital Services
• Artificial Intelligence (Chatbots)
• +۷ مورد دیگر

Dr. Alireza Nili is a Senior Lecturer in Service Science at QUT's School of Information Systems within the Faculty of Science. His expertise spans digitization of customer-centric services, AI/chatbots, IoT/IIoT, and sustainable technologies. He holds a PhD from Victoria University of Wellington and has coordinated large-scale courses like IT Systems Design (IFB103), achieving top teaching scores. Nili's research focuses on service ecosystems, trust in digital services, and public/retail sector innovations. He has secured over $1.4M in industry grants for projects involving Cisco, Amazon, and Services Australia. His awards include the 2023 Educator of the Year and multiple top conference paper recognitions. Nili supervises PhD students at Level 3 mentoring status and contributes to major conferences as track chair/associate editor. Research highlights include frameworks for chatbot governance, IOT in agriculture, and AI ethics. His work appears in IEEE Software , Communications of the ACM , and MIT Sloan Management Review . Current projects address consumer trust in AI technologies and spatial data systems. Nili's interdisciplinary approach combines design science with empirical methodologies to bridge theory and practice in digital service innovation.

• Semantics
• Language Technology
• Recommender Systems
• +۵ مورد دیگر

Jon Atle Gulla is a Professor at NTNU and Director of the Norwegian Research Centre for AI Innovation (NorwAI). He holds academic leadership roles, including former Head of the Department of Computer Science and Informatics at NTNU. His expertise spans Semantics, Language Technology, Recommender Systems, and AI-driven innovation. He has nearly 150 international publications and advised over 100 students across MSc, PhD, and postdoctoral levels. Education: MSc in Computer Science (1988), PhD in Computer Science (1993) from Norwegian Institute of Technology (NTH) MSc in Linguistics (1995), University of Trondheim MSc in Management (Sloan fellowship, 2003), London Business School Research interests focus on Semantics and Language Technology applied to Recommender Systems, Information Retrieval, and Text Analysis. He explores AI-based innovations in digitalization and entrepreneurship, advising industry on AI adoption and commercialization. Notable projects include Big Data collaborations with DNB, RecTech for news recommendation, and Trondheim Analytica analyzing political texts/social media. Publications emphasize AI applications in news recommendation, political text analysis, and Scandinavian language models. His work addresses ethical AI, copyright implications, and cross-lingual NLP challenges. Awards: Member of the Royal Norwegian Society of Arts and Sciences. Advising/grants: Supervised 30 PhD students and 70 MSc students. Involved in startups like Fast Search & Transfer (acquired by Microsoft) and Mito.ai/Strise.ai. Active in reviewing for journals like Data & Knowledge Engineering and conferences like ACL. Labs/teams: Leads NorwAI, co-founder of INRA and NOBIDS workshops. Collaborates with industry and academia on AI-driven solutions.

Paul Taeleمشاهده پروفایل

عضو هیئت علمی

• Sketch Recognition
• Human-Computer Interaction (HCI)
• Artificial Intelligence
• +۵ مورد دیگر

Paul Taele is an Instructional Assistant Professor and Deputy Lab Director in the Sketch Recognition Lab at Texas A&M University's Department of Computer Science & Engineering. He holds a Ph.D. (2019), M.S. (2010), and dual B.S. degrees in Computer Science and Mathematics from the University of Texas at Austin (2006). His research focuses on sketch recognition, haptics, and intelligent interfaces for education and accessibility, with notable work in mid-air gesture recognition, educational sketching tools, and assistive technologies for disabilities. He has contributed to projects like Kanji Workbook , Hashigo , and HaptiMoto , and has published over 50 peer-reviewed articles across venues like CHI, IUI, and AAAI. Taele has received awards including the NSF Student Travel Grant (2014) and Ford Foundation Honorable Mention (2015). He teaches courses in capstone design, programming, and sketch recognition, and mentors students across all academic levels through strict eligibility criteria for research collaborations. Education : Ph.D. Computer Science, Texas A&M University (2019) M.S. Computer Science, Texas A&M University (2010) B.S. Computer Science & Mathematics, University of Texas at Austin (2006) Concentration in Mandarin Chinese, National Chengchi University (2007) Research Interests : Taele's work bridges HCI and AI to create accessible educational interfaces. His projects emphasize: Sketch Recognition : Developing algorithms for mid-air gestures, children's developmental assessments, and language learning Accessibility : Haptic systems for visually impaired learners and algebra education Educational Tech : Intelligent tutoring systems for music, math, and East Asian languages Awards & Grants : EAAI-20 Travel Grant (2020) Ford Foundation Dissertation Honorable Mention (2015) NSF East Asia-Pacific Summer Institutes (2013, 2012) Royce E. Wisenbaker Fellowship (2009) Lab & Teams : Director of the Sketch Recognition Lab (SRL) and collaborator with global institutions like Singapore Management University and National Taiwan University. Active in organizing workshops like SketchRec at IUI conferences.

• Visual Analytics
• Information Visualization
• Geographic Information Science
• +۷ مورد دیگر

Jo Wood is Professor of Visual Analytics in the Department of Computer Science at City, University of London, where she has been employed since January 14, 2000. Her work bridges computer science, geographic information science, and human-computer interaction, focusing on innovative methods for visualizing complex spatial and behavioral data. Her research interests center on visual analytics , information visualization , and geovisualization , with applications in transportation, public health, crisis response, and citizen science. She investigates how interactive visual interfaces can support exploratory data analysis, decision-making, and storytelling, particularly through small multiples, faceted views, and sketch-based rendering techniques. The trends in her recent publications reflect a consistent focus on user-centered design , spatial data abstraction , and interactive exploration of multivariate datasets. Her work often integrates real-world behavioral data such as GPS tracks, cycling patterns, and crowd-sourced information to build meaningful visual narratives and support analytical reasoning. Throughout her career, Jo Wood has contributed significantly to the advancement of visual analytics through high-impact publications in top-tier venues such as IEEE Transactions on Visualization and Computer Graphics and Computer Graphics Forum. Her collaborations with researchers like Jason Dykes and Aidan Slingsby highlight her role in a vibrant research community. She has supervised numerous research projects and mentored students in visualization and geospatial analytics, though specific names are not listed in the provided text. Her work has been supported by various research grants, particularly in domains involving urban mobility, energy modeling, and crisis informatics, though grant details are not specified here. Jo Wood has also contributed to the design of visual analytics systems for applications including disease spread modeling, bicycle-hire scheme monitoring, and persuasive technology for health and leisure, demonstrating a strong commitment to impactful, interdisciplinary research.

Shuran Songمشاهده پروفایل

استادیار

• Computer Vision
• Robotics
• Robot Learning
• +۴ مورد دیگر

Shuran Song is an Assistant Professor of Electrical Engineering at Stanford University, with a courtesy appointment in Computer Science. Previously, she was faculty at Columbia University. She holds a Ph.D. in Computer Science from Princeton University and a BEng from HKUST. Her research focuses on the intersection of computer vision and robotics, particularly in embodied AI, robot manipulation, and sensorimotor learning. Song's work emphasizes learning from physical interactions to enable robots to perform complex tasks autonomously. She leads the Robotics and Embodied AI Lab (REAL@Stanford) and has received prestigious awards, including the NSF Career Award, Sloan Fellowship, and Microsoft Faculty Fellowship. Education: Ph.D., Computer Science, Princeton University; BEng, HKUST Affiliations: Stanford School of Engineering, Department of Electrical Engineering Research interests include deformable object manipulation, visuomotor policy learning, and generalizable robot skills. Her lab develops algorithms for robots to learn through interaction, with applications in household assistance (e.g., TidyBot) and industrial automation. Notable contributions include the TossingBot and Diffusion Policy frameworks. Publications span robotics, computer vision, and AI conferences (RSS, ICRA, CVPR), focusing on policy learning, deformable object handling, and embodied intelligence. Awards highlight her impact in advancing robot learning and perception. Advises doctoral and master's students in robotics and AI, and collaborates on grants from NSF, DoD, and industry partners. Teaches courses on robot perception and embodied AI at Stanford.

Xuezhe Maمشاهده پروفایل

استادیار

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Xuezhe Ma is an Assistant Professor in the Department of Computer Science at the University of Southern California's Viterbi School of Engineering. Previously, he was a Ph.D. student at Carnegie Mellon University's Language Technologies Institute, where he worked under the supervision of Professor Eduard Hovy. His academic journey includes a Master's degree from Shanghai Jiao Tong University's Center for Brain-like Computing and Machine Intelligence and a Bachelor's degree in Computer Science from the same institution. Ph.D. in Computer Science, Carnegie Mellon University (completed ~2020) M.S. in Brain-like Computing, Shanghai Jiao Tong University B.S. in Computer Science, Shanghai Jiao Tong University Dr. Ma's research spans multiple areas at the intersection of Natural Language Processing and Machine Learning, with particular focus on structured prediction, syntactic and semantic parsing, machine translation, language generation, and deep generative models. His recent work has expanded into vision-language models, large language model architectures, and applications across computer vision tasks. His research combines theoretical foundations with practical implementations, as evidenced by his development of tools like NeuroNLP2 and MaxParser. His publication record shows a clear trajectory from foundational NLP work during his PhD (including papers on dependency parsing and sequence labeling) to more recent contributions in generative models and large language systems. The 15 most recent publications reveal a strong focus on addressing fundamental challenges in generative modeling, context handling, and multimodal integration, with applications spanning literary translation, medical imaging, and news diffusion analysis. AI2 Outstanding Intern Award (2018) Dr. Ma has secured research funding supporting his work in generative models and language technologies, with projects focusing on improving the efficiency and capabilities of large language models. His research group at USC is actively working on next-generation language understanding and generation systems, with particular emphasis on context-aware modeling and multimodal integration. He has established collaborations with industry partners including the Allen Institute for AI and has contributed to open-source projects like Texar. At USC, Dr. Ma leads research in the Information Sciences Institute, directing projects on efficient large language model architectures and multimodal reasoning systems. His lab focuses on developing novel approaches to context handling, model efficiency, and multimodal integration, with applications across diverse domains including healthcare, literary analysis, and news media.