جستجوی استاد راهنمای دانشگاهی

• Human-Computer Interaction
• Digital Humanities
• Art and Technology
• +۵ مورد دیگر

Steven Devleminck is an Associate Professor in the Department of Computer Science at KU Leuven's Faculty of Engineering Technology, concurrently serving as coordinator of the School of Arts (Associated Faculty) in Brussels. His dual appointment bridges engineering and arts through the Human-Computer Interaction (HCI) group at Group T Leuven Campus and Unit Art & Technology in Brussels, with active membership in DigiSoc – KU Leuven Digital Society Institute. His research centers on human-centered computing and speculative design methodologies , with core expertise in tangible interaction for emotion regulation and multispecies futures. Key themes include biofuturing as co-creative response to climate crises, squeeze-based interfaces for workplace stress, and artistic AI collaborations. His work uniquely integrates computer science with choreography, film studies, and anthropology through projects like “Youth TikTok production as public pedagogy” and “Imagining the Post-Anthropocene in BioFutures Living Lab”. Analysis of recent publications reveals three dominant trajectories: (1) Advancement of squeeze interaction techniques for affective computing, (2) Development of biofuturing frameworks for multispecies speculation, and (3) Critical examinations of AI's role in artistic mediumship. Cross-cutting themes include post-anthropocentric design, climate-responsive technologies, and decolonial approaches to digital pedagogy. Devleminck actively mentors doctoral candidates including Ula Sickle (choreographic exhibitions) and J. Verbesselt (cinema studies), while leading major funded projects such as: Living Corpora (2025-2029): Pioneering human-AI collaboration in digital humanities as Co-promotor Experiential Futuring (2022-2026): Co-creative methodology for social media outage response as Co-promotor Deradicalizing the City (2021-2025): Urban intervention research as Promotor He serves on the Computer Science Department Council and Doctoral Committee for the Associated Faculty of Arts. His laboratory ecosystem spans the HCI Group T Leuven Campus for technical development, Brussels-based Unit Art & Technology for artistic integration, and BioFutures Living Lab for participatory multispecies experimentation. This tripartite structure enables transdisciplinary work connecting squeeze sensor engineering with climate futures speculation and museum interface design.

Burkhard Maessمشاهده پروفایل

استاد پژوهش

• Neuroscience
• Auditory Processing
• Signal Analysis
• +۳ مورد دیگر

Dr. Burkhard Maess is a Research Professor and Group Leader at the Max Planck Institute for Human Cognitive and Brain Sciences, leading the Methods and Development Group Brain Networks. His research focuses on auditory and language processing, signal analysis, and dynamic modeling of neuronal networks. He holds a Diploma in Physics (University of Leipzig, 1987) and a PhD in Physics (University of Leipzig, 1990). His career includes postdoctoral positions at the Academy of Sciences of the GDR and the Free University of Berlin before joining the MPI in 1995. Since 2000, he has led research groups on MEG/EEG signal analysis and cortical network dynamics. His work integrates advanced neuroimaging techniques like MEG and EEG to study sensory processing, neural network dynamics, and the effects of aging on auditory attention. Key contributions include developing high-resolution BEM-FMM methods for source localization and analyzing cross-frequency coupling in neuroscience data. His group also explores spinal cord electrophysiology and the neural underpinnings of perceptual decision-making. Dr. Maess’ research spans cognitive neuroscience, biomedical engineering, and computational modeling, with a focus on bridging empirical findings with theoretical frameworks in neuroscience.

Petar Kormushevمشاهده پروفایل

مدرس ارشد

• Robotics
• Machine Learning
• Reinforcement Learning
• +۴ مورد دیگر

Petar Kormushev is a Senior Lecturer (Associate Professor) in Robotics at the Dyson School of Design Engineering, Imperial College London, and the founder/director of the Robot Intelligence Lab. He holds a PhD in Computational Intelligence from Tokyo Institute of Technology. His research focuses on robotics and machine learning, particularly reinforcement learning for autonomous robots. Key projects include the WALK-MAN humanoid robot for disaster response and contributions to the PANDORA and STIFF-FLOP EU projects. He has received the 2013 John Atanasoff Award for scientific excellence in ICT. His lab develops machine learning algorithms applied to humanoid robots like COMAN and iCub, with interests in robot learning, compliant control, and autonomous systems. He has supervised numerous PhD students and led research teams at IIT and Imperial College.

Venkatram Ramaswamyمشاهده پروفایل

استاد

• Marketing
• Strategy
• Innovation
• +۴ مورد دیگر

Venkatram Ramaswamy is the Hallman Fellow of Electronic Business and Professor of Marketing at the Ross School of Business, University of Michigan. He is a globally recognized thought leader in innovation, strategy, and co-creation, with expertise spanning marketing, branding, IT, and organizational dynamics. His work emphasizes the transformative potential of co-creating value with stakeholders across industries and sectors. Education: PhD in Marketing, The Wharton School, University of Pennsylvania (1989). Research Interests: Venkat’s work focuses on co-creation paradigms, experience innovation, digital ecosystems, and stakeholder collaboration. He pioneered the concept of co-creation as a revolutionary approach to business value, detailed in his seminal books The Future of Competition (2004) and The Power of Co-Creation (2010). His recent work explores AI-human interactional creation and platformed ecosystems. Key Contributions: He has advised global firms like Mahindra, Hitachi, and Infosys on co-creation strategies. His frameworks integrate strategic risk management, digital platforms, and lived-experience ecosystems to drive sustainable value. He has delivered keynotes at events worldwide, including the Drucker Forum and InnovationsKongress. Awards: Recipient of the MIT-PwC Award (2003), Emerald Literati Award (2009), and Best Speaker Award at the Baptie Marketing Focus (2005). Grants & Labs: Collaborations with institutions like the International University of Japan (IUJ) and involvement in initiatives like the India Philanthropic Co-Creation Project reflect his commitment to systemic social impact. His research is supported by grants exploring digitalized societal ecosystems and wellbeing-focused platforms.

Ben Greenمشاهده پروفایل

استادیار

• AI Ethics
• Algorithmic Fairness
• Human-Algorithm Interactions
• +۵ مورد دیگر

Ben Green is an Assistant Professor in the University of Michigan School of Information and a courtesy Assistant Professor in the Gerald R. Ford School of Public Policy. He holds a PhD in Applied Mathematics from Harvard University with a secondary focus on Science, Technology, and Society. His research examines algorithmic ethics, fairness, and governance, aiming to reduce harms and advance social justice. Notable works include The Smart Enough City (2019) and his forthcoming Algorithmic Realism . He is affiliated with the Berkman Klein Center for Internet & Society at Harvard and the Center for Democracy & Technology. Education: PhD in Applied Mathematics, Harvard University (with secondary field in Science, Technology & Society) BS in Mathematics & Physics, Yale University Research Interests: Algorithmic fairness in public policy Human-algorithm interaction dynamics Regulatory frameworks for AI Equity-centered data science practices Urban technology policy His recent publications explore themes like the limitations of human oversight in algorithmic systems, the sociotechnical challenges of implementing ethical AI, and the intersection of legal reasoning with computational systems. His writing emphasizes actionable solutions to systemic biases in algorithmic governance. Ben’s current projects include advancing algorithmic realism – a framework for grounding data science in socially just practices – and analyzing how counterfactual explanations influence judicial decisions. He serves on multiple interdisciplinary advisory boards and frequently collaborates with policymakers to translate research into actionable strategies.

Ken Holsteinمشاهده پروفایل

استادیار

• Human-Centered AI
• Research through Design
• Responsible Computing
• +۹ مورد دیگر

Ken Holstein is an Assistant Professor at Carnegie Mellon University's Human-Computer Interaction Institute (HCII) , where he directs the CoALA Lab and contributes to the CMU-NIST Cooperative Research Center on AI Measurement Science & Engineering (AIMSEC) . His work bridges human-computer interaction, AI, cognitive science, and design to create systems that respect and elevate human expertise in AI development. Research focuses on participatory and expertise-driven approaches to AI design, development, and evaluation Emphasizes AI's impacts on human workers and integrating diverse expertise (domain, lived, technical) across the AI lifecycle His research is supported by grants from the National Science Foundation (NSF) , NIST , The Block Center for Technology and Society , and industry partners like Microsoft, Google, and Amazon. He collaborates with labs including CASMI , UL Research Institutes , and MetaGov . Visit his personal website or Google Scholar page for publications.

Stefanie Tellexمشاهده پروفایل

دانشیار

• Robotics
• Human-Robot Interaction
• Artificial Intelligence
• +۳ مورد دیگر

Stefanie Tellex is an Associate Professor of Computer Science and Engineering at Brown University. She leads research in Human-Robot Interaction, focusing on enabling robots to understand natural language instructions and collaborate effectively with humans. Her work spans robotics, artificial intelligence, and reinforcement learning, with a strong emphasis on practical applications like teleoperation, task execution, and language grounding. Education : PhD in Computer Science, Massachusetts Institute of Technology (2010) MS in Computer Science, MIT (2006) MEng in Computer Science, MIT (2003) BSc in Computer Science, MIT (2002) Research Interests : Her research integrates robotics with natural language processing, emphasizing: Developing systems that interpret complex human instructions Improving robot learning through weak supervision Designing intuitive human-robot collaboration interfaces Advancing reinforcement learning for real-world robotic tasks Publications Trends : Recent work highlights advancements in: - Language-grounded reward functions for robots - Virtual reality frameworks for robot teleoperation (ROS Reality) - Abstract planning techniques for non-Markovian tasks - Hybrid architectures for interpreting multi-granularity instructions. Teaching : CSCI 1410: Artificial Intelligence CSCI 1951R: Introduction to Robotics CSCI 2951K: Topics in Collaborative Robotics Advising & Labs : Advises students on robotics and NLP projects. Active in Brown’s robotics labs focusing on human-robot collaboration and AI-driven systems.

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +۵ مورد دیگر

Johanna Pirker serves as an Associate Professor at the Institute of Human-Centred Computing, Graz University of Technology, where she holds teaching authorization in Applied Computer Science. Her work bridges academic research with practical applications in interactive technologies, maintaining active consultation hours for students every Monday morning. Her research centers on human-centered computing with emphases on virtual/augmented reality systems, serious game design, and AI-driven interactive experiences. She investigates player behavior, user experience optimization, and therapeutic/educational applications of immersive technologies across diverse contexts including rehabilitation, engineering education, and social platforms. Recent 2025 publications reveal strong trends in AI integration for gaming ecosystems (toxicity detection, dialogue systems), VR-based educational tools across disciplines, and cross-cultural analyses of gaming communities. Her work consistently combines experimental user studies with novel system development to address real-world challenges. While specific grant details and student advising records aren't documented in source materials, her extensive publication output across venues like FDG and iLRN indicates active leadership in interdisciplinary collaborations focused on advancing immersive technologies for societal benefit.

Steven Mansonمشاهده پروفایل

استاد

• Geographic Information Science
• Environmental Science
• Biocomplexity
• +۱۲ مورد دیگر

Dr. Steven Manson is a Professor in the Department of Geography, Environment, and Society at the University of Minnesota's College of Liberal Arts, where he also served as Associate Dean for Research and Graduate Programs. He directs the Human-Environment Geographic Information Science (HEGIS) laboratory and leads major data science initiatives like the National Historical Geographic Information System (NHGIS) and IPUMS Terra. PhD in Geography, Clark University (2002) BA Honours in Geography, University of Victoria (1995) His research focuses on geographic information science and human-environment systems , using agent-based modeling and big data to analyze land use change, urban dynamics, and sustainability challenges. Recent work explores spatiotemporal data harmonization and geospatial cyberinfrastructure . The articles reveal trends in GIScience methodology , urbanization analysis , and data-intensive sustainability research . Key contributions include self-organizing map applications for health data and hybrid statistical-GIS techniques for environmental policy. Scientific accolades include: Ecological Society of America Sustainability Science Award NASA Earth System Science Fellow McKnight Land Grant Professorship As Principal Investigator for NHGIS and IPUMS Terra, he secured over $40M in NSF, NIH, and DOJ grants for spatiotemporal data infrastructure. Outreach initiatives include developing open geospatial textbooks adopted globally and collaborating with Twin Cities K-12 programs.

Jann Spiessمشاهده پروفایل

دانشیار

• Data-Driven Decision-Making
• Machine Learning
• Econometrics
• +۲ مورد دیگر

Jann Spiess is an Associate Professor of Operations, Information & Technology at Stanford University's Graduate School of Business and holds a courtesy appointment as Associate Professor of Economics in the School of Humanities and Sciences. He is also a Center Fellow at the Stanford Institute for Economic Policy Research and a Faculty Affiliate of the Golub Capital Social Impact Lab. PhD in Economics (Harvard University, 2018) AM in Economics (Harvard University, 2015) MPP in Public Policy (Harvard University, 2013) MASt in Mathematics (University of Cambridge, 2011) BSc in Mathematics (Technical University of Munich, 2010) Jann's research integrates machine learning with econometric methods to advance causal inference and data-driven decision-making . He explores high-dimensional and robust causal inference, synthetic control methods, and algorithmic fairness, while addressing challenges in human-AI collaboration and policy design. His publications span econometrics, behavioral economics, and data science, focusing on experimental design, robust statistical techniques, and applications of machine learning to public policy. Key themes include replicable inferences from big data, human-AI interaction, and ethical algorithmic design. Philip F. Maritz Faculty Scholar, 2021–22 David A. Wells Prize for best dissertation, Harvard Economics, 2018 Restud Tour, 2018 Jann's work bridges microeconometric methods , statistical decision theory , and mechanism design to enhance analytical frameworks for data-driven policy. He has contributed to robust inference in panel data and synthetic control methods, alongside studies on nudges for vaccination and financial aid renewals. As Faculty Affiliate at the Golub Capital Social Impact Lab, Jann collaborates on projects applying data science to social policy challenges, merging technical rigor with societal impact.

Roy Peaمشاهده پروفایل

استاد

• Brain and Learning Sciences
• Child Development
• Collaborative Learning
• +۹ مورد دیگر

Professor Roy Pea is the David Jacks Professor of Education & Learning Sciences at Stanford University, with a courtesy appointment in Computer Science. He served as Director of the H-STAR Institute (2007-2021) and founded Stanford’s PhD program in Learning Sciences and Technology Design. His research focuses on technology-enhanced learning, social foundations of human learning, and interdisciplinary applications of digital tools. Stanford University, School of Education Graduate School of Education Department Courtesy appointment in Computer Science His work spans complex domains like concussion education, climate change learning, and AI-driven mental health interventions. He co-authored the 2010 National Education Technology Plan and co-edited key texts including Video Research in the Learning Sciences and AI in Education . His NSF-funded LIFE Center (2004-2014) advanced learning science theories. Recent publications address: (1) linguistic framing of concussions and reporting behavior, (2) AI chatbots for mental health, (3) "engineering fiction" to reduce climate change abstractness, and (4) immersive AR/LLM learning experiences. His research integrates data science, psychology, and educational technology. Fellow, American Academy of Arts and Sciences (2019) Inaugural Fellow, International Society of the Learning Sciences (2018) Honorary Doctorate, The Open University (2018) Best Bridging Paper, EDM 2014 LAK13 Best Paper Award (2013) Roy mentors doctoral and master’s students in learning sciences, advising on topics related to technology, cognition, and equity. He contributes to digital education policy through roles on advisory boards for organizations like NSF, NIH, and the Joan Ganz Cooney Center. His patents include methods for digital video analysis and collaborative learning systems.

Joshua Bardمشاهده پروفایل

دانشیار

• Robotic Fabrication
• Architectural Design
• Human-Machine Collaboration
• +۴ مورد دیگر

Joshua D. Bard is an Associate Professor and Associate Head for Design Research at Carnegie Mellon University's School of Architecture. His work bridges traditional craft and cutting-edge robotics, focusing on human-machine collaboration in construction domains. He leads Archolab, an award-winning research group exploring digital fabrication methods like 'Morphfaux' (robotic plaster techniques) and 'Spring Back' (parametric steam bending). Education: M.Arch (Distinction) from University of Michigan; B.A. in Literature & Philosophy from Wheaton College. Professional affiliations include the Manufacturing Futures Institute and rob|arch. Research emphasizes reviving historical crafts through digital tools, such as augmented reality interfaces for architectural education and thermal-tuned concrete panels via robotic processes. His teaching includes generative modeling and architectural robotics labs. Awards: Architect Magazine R+D Award, Canadian Wood Council Merit Award Key Projects: Plaster ReCast AR app, Thermally Informed Robotic Concrete Panels Collaborators: Dana Cupkova, Garth Zeglin, Steven Mankouche Current courses include 62-225 Generative Modeling and 48-555 Introduction to Architectural Robotics. His work is featured in venues like the Carnegie Museum of Art and academic journals like International Journal of Architectural Computing .

Brandon Weissbourdمشاهده پروفایل

استادیار

• Neuroscience
• Evolutionary Biology
• Systems Neuroscience
• +۳ مورد دیگر

Brandon Weissbourd is an Assistant Professor in the Biology department at the Massachusetts Institute of Technology (MIT) and holds a joint appointment as an Investigator at the Picower Institute for Learning and Memory. He joined MIT in 2023 after completing a postdoctoral fellowship in the lab of David Anderson at the California Institute of Technology (Caltech). Prior to that, he earned his PhD in Biology from Stanford University in 2016 under the mentorship of Liqun Luo, and a BA in Human Evolutionary Biology from Harvard University in 2009. His research interests encompass systems neuroscience, evolutionary biology, and molecular biology. He uses jellyfish models, such as Clytia hemisphaerica, to study the evolution and functional mechanisms of nervous systems. His work combines computational techniques like single-cell RNA-seq and advanced microscopy with traditional genetic and anatomical approaches to dissect neural circuits and their roles in behaviors like feeding and social interaction. Additionally, he has explored serotonin and noradrenaline systems in mammals, focusing on their heterogeneity and functional connectivity. Recent publications emphasize the utility of non-traditional model organisms for evolutionary studies and underscore his expertise in computational methods for neurobiological analysis. Earlier work includes groundbreaking studies on the dorsal raphe serotonin system and basal forebrain circuits governing sleep-wake cycles. No scientific awards or honors have been explicitly mentioned in the provided text. Weissbourd’s academic trajectory reflects a strong emphasis on interdisciplinary research, merging evolutionary, molecular, and systems-level perspectives to understand neural systems across species. His advising record is not detailed here, though he has been affiliated with prestigious research labs during his training. Current affiliations include the MIT Biology department and the Picower Institute, where he likely contributes to collaborative projects in systems and evolutionary neuroscience. Weissbourd’s work is grounded in experimental models such as Clytia medusa and mouse brain studies, enabling him to investigate both ancient nervous system architectures and modern mammalian neural pathways. His lab’s focus on functional genomics and circuit mapping positions him at the forefront of studies on neural diversity and evolutionary innovation.

R. Michael Alvarezمشاهده پروفایل

استاد

• Political Science
• Computational Social Science
• Voting Behavior
• +۶ مورد دیگر

R. Michael Alvarez , Flintridge Foundation Professor of Political and Computational Social Science at Caltech, is a leading scholar in election technology, political methodology, and machine learning applications in social science. Affiliated with the Caltech/MIT Voting Technology Project , the Social and Decision Neuroscience Program , and the Resnick Sustainability Institute , his work bridges technology and democracy. Education: B.A. from Carleton College, Ph.D. from Duke University Academic Career: Caltech faculty since 1992 His research spans: Election Integrity : Monitoring election security, fraud detection, and ballot systems Computational Social Science : Applying machine learning to voter behavior and policy analysis Climate Policy : Examining public attitudes and behavioral interventions for sustainability Online Behavior : Analyzing toxicity in gaming and social media dynamics Key article trends show focus on election forensics (2025 Nature Climate Change study), game toxicity analysis (2025 CHI Play paper), and LLM applications in social science. His students include Jacob Morrier, Mitchell Linegar, and teams of postdocs and undergraduates in Caltech's SURF program. Scientific recognition includes: Google Cloud Research Innovators Class of 2022 Co-editor of multiple academic series including Cambridge Elements in Quantitative Methods

Angel Hsing-Chi Hwangمشاهده پروفایل

استادیار

• Human-AI Interaction
• Sociotechnical Impact of AI
• Digital Mental Health
• +۴ مورد دیگر

Angel Hsing-Chi Hwang is an Assistant Professor of Communication at the University of Southern California (USC) Annenberg School for Communication and Journalism and a core faculty member at the USC Center for AI in Society . Her research focuses on the societal impact of artificial intelligence (AI) on work practices, with a particular emphasis on human-AI interaction (HAII), digital mental health, and the future of work. She holds a PhD in Communication from Cornell University with a concentration in Human-Computer Interaction and completed postdoctoral training at the Cornell Bowers College of Computing and Information Science . Research Interests: Human-AI collaboration and ethical design Sociotechnical consequences of AI deployment at scale AI in healthcare systems and mental health services Creative processes and AI empowerment in professional domains Methods for scalable AI impact assessment Online labor markets and AI-driven work transformations Recent Work: Her publications explore topics such as the integration of AI in mental healthcare ecosystems, gender dynamics in AI-mediated teams, and the ethical implications of generative AI in creative industries. She actively engages with industry through collaborations with Microsoft Research, Google Research, and other tech institutions. Affiliations & Activities: Organizing workshops on AI disclosure, ownership, and accountability (CHIWORK 2025) Contributing to conferences like ACM CHI and ICWSM Collaborating with interdisciplinary teams on AI ethics and policy initiatives