جستجوی استاد راهنمای دانشگاهی

Wei-Chen Hungمشاهده پروفایل

استاد

• Problem Solving
• Human-Computer Interaction
• Performance Support Systems
• +۷ مورد دیگر

Wei-Chen Hung is a Professor and Department Chair in the Department of Educational Technology, Research and Assessment at Northern Illinois University’s College of Education. He holds a Ph.D. in Instructional Systems Technology from Indiana University-Bloomington and is actively engaged in teaching, research, and leadership in educational technology. Ph.D., Instructional Systems Technology, Indiana University-Bloomington (with Minor in Information Science) His research focuses on problem solving, human-computer interaction (HCI), and performance support systems in educational contexts. He explores how technology can scaffold learning, enhance problem-solving skills, and support teachers in instructional design and classroom management. His work spans K–12, higher education, and professional training environments. The recent publications highlight a strong trend in developing and evaluating technology-enhanced learning environments, including intelligent tutoring systems, 3D virtual worlds, educational simulations, and performance support tools. These works span disciplines such as STEM education, nursing, and social sciences, reflecting an interdisciplinary approach to solving instructional challenges through technology. Wei-Chen Hung has secured significant research funding from agencies including the National Science Foundation, NASA, and the Illinois Department of Education. He has served as Principal Investigator and Co-Principal Investigator on multiple grants focused on educational simulations, research methods training, and assistive technologies. National Science Foundation: Web-based Interactive Landform Simulation Model (WILSIM), $236,041, 2013–2016 (Senior Faculty Expert) Elgin Community College: Information security awareness, $10,000, 2011–2012 (Principal Investigator) National Science Foundation: Intelligent tutoring system for research methods, $150,000, 2008–2012 (Co-Principal Investigator) NASA: MARS Valley Networks Project, $20,000, 2005–2007 (Faculty Expert) Illinois Department of Education: Assistive technology for blind and visually impaired children, $75,000, 2005–2007 (Faculty Expert) He has contributed to the development of software tools and systems such as the Cause and Consequence behavior management system and performance support systems for educators. His lab and research initiatives emphasize applied design, usability testing, and evaluation of educational technologies in real-world settings.

• Exercise Physiology
• Sport Science
• Nutritional Science in Sports
• +۱۰ مورد دیگر

Dr. David Kelly is a Lecturer in the Department of Sport and Health Science at Dublin City University (DCU), within the Faculty of Science and Health. He teaches across Sport Science, Athletic Therapy, and Physical Activity programs, with a focus on Applied Sport Science. David Kelly obtained his BSc in Sport Science and Health in 2010 and a PhD in Exercise Physiology in 2014, both from DCU. His academic journey reflects a strong foundation in sport and health sciences. His research employs a multidisciplinary approach integrating physiological, nutritional, and biomechanical methodologies. Key interests include Exercise Training Specificity, Energy Demands, Nutritional Knowledge and Dietary Intake of Adolescent Team Sport Players, and Performance Profiling of elite and sub-elite athletes. His work has significant application in Gaelic games and team sports performance. The most recent articles indicate a growing trend toward data-driven athlete monitoring, including machine learning applications for performance prediction, meta-analyses of training methods, physiological comparisons in Gaelic football, athlete recovery perceptions, and nutritional behaviors. These span sports science, physiology, nutrition, and data analytics. David is actively involved in national sports organizations, serving on the Sport Science Working Group for the Gaelic Athletic Association (GAA) and the Player Welfare and Safety Committee for the Gaelic Players Association (GPA). These roles reflect his commitment to athlete welfare and performance optimization. There is no public information on specific research grants or students he has supervised. He is not listed as part-time, retired, or deceased, and there are no mentions of scientific awards in the provided text. He is associated with collaborative research networks and contributes to interdisciplinary projects, particularly in athlete performance and health. His work bridges academic research and practical application in elite sports settings.

Michael Wimmerمشاهده پروفایل

دانشیار

• Real-time Rendering
• Computer Games
• Real-time Visualization
• +۶ مورد دیگر

Michael Wimmer is an Associate Professor at the Institute of Computer Graphics and Algorithms, Faculty of Informatics, Technical University of Vienna (TU Wien), where he leads the Rendering and Modeling Group. His work bridges real-time graphics, visualization, and urban modeling applications. Research Interests: His primary research lies in real-time rendering, procedural and shape modeling, point-based rendering, and real-time visualization of urban environments, with applications in computer games and interactive systems. He has coauthored over 100 papers and the notable book Real-Time Shadows . The available publication indicates a trend toward integrating domain knowledge into dynamic financial data visualization, expanding his expertise from core graphics into data-intensive applications. Associate Editor: Computers & Graphics, IEEE Transactions on Visualization and Computer Graphics (TVCG), Computer Graphics Forum (CGF) Program Committees: ACM SIGGRAPH, SIGGRAPH Asia, Eurographics, Eurographics Symposium on Rendering, ACM I3D Papers Co-Chair: EGSR 2008, Pacific Graphics 2012, Eurographics 2015 Michael Wimmer has supervised research students and leads the Rendering and Modeling Group at TU Wien, fostering innovation in graphics and visualization. While specific grants are not listed, his extensive publication record and editorial roles suggest sustained research funding and academic leadership. The group focuses on advancing real-time graphics techniques, with applications in urban simulation, gaming, and data visualization, maintaining strong ties to both academic and industrial partners in the computer graphics community.

Kathryn E. Spierمشاهده پروفایل

استاد

• Law and Economics
• Industrial Organization
• Litigation
• +۹ مورد دیگر

Kathryn E. Spier is the Domenico De Sole Professor of Law at Harvard Law School and a Research Associate at the National Bureau of Economic Research (NBER). She previously held faculty positions at Northwestern University’s Kellogg School of Management and Harvard University’s Economics Department. She served as President of the American Law and Economics Association (2015–2016) and has held editorial roles at the RAND Journal of Economics and the American Economic Review. Education: Ph.D. in Economics, Massachusetts Institute of Technology, 1989 B.A. in Mathematics and Economics, Yale University, 1985 Her research centers on law and economics, with a focus on litigation, contracts, tort law, antitrust, and business organizations. She employs theoretical and experimental methods to analyze settlement bargaining, platform liability, class actions, and product safety. Her work integrates insights from industrial organization and game theory to address legal and regulatory challenges. Recent publications explore the liability of digital platforms, class action waivers, IPO disclosure, and litigation finance. Her articles frequently appear in top journals such as the American Economic Review, RAND Journal of Economics, and Journal of Law, Economics, and Organization. The research demonstrates a consistent focus on incentive design, strategic behavior, and institutional mechanisms in legal contexts. Scientific Awards and Honors: Honorary Doctorate, BI Norwegian Business School, 2023 Garvin Prize in Law & Economics, Berkeley, 2001 National Science Foundation Graduate Fellowship, 1985–1988 Sidney J. Levy Teaching Award (twice), Kellogg, 2002 & 2006 Multiple Yale University prizes for academic excellence, 1984–1985 Olin Fellowship, University of Chicago Law School, 1993–1994 She has advised numerous doctoral students and collaborated extensively with scholars such as Albert H. Choi, Claudia M. Landeo, and J.J. Prescott. Her research has been supported by the National Science Foundation and the Searle Foundation. She is actively engaged in academic service, including editorial board memberships and leadership in professional associations. Professor Spier leads research initiatives on platform regulation and civil litigation reform. She teaches courses in analytical methods for lawyers, business strategy, and graduate workshops in contracts and organizations. Her work continues to shape policy debates on liability, antitrust, and consumer protection.

• Complex Systems
• Computational Modeling
• Network Science
• +۷ مورد دیگر

Jorge Louçã is a Full Professor in the Department of Information Science and Technology at ISCTE-IUL, where he has been a faculty member since 2000. He is also an Integrated Researcher at ISTAR-Iscte, the Research Center in Information Sciences, Technologies and Architecture, and leads the research group The Observatorium . He holds a PhD in Computer Science and Artificial Intelligence from Université Paris Dauphine and the University of Lisbon, and completed his Aggregation in Complexity Sciences in 2019. PhD in Computing – University of Lisbon & Université Paris-Dauphine (2000) Master’s in Informatique: Intelligent Systems – Université Paris-Dauphine (1995) Aggregation in Complexity Sciences – ISCTE-IUL (2019) His research centers on computational modeling of social systems, focusing on data-intensive analysis of human communication, knowledge generation in large networks, and the dynamics of complex systems. He founded the Doctoral Program in Complexity Sciences and has been instrumental in advancing the field through international collaborations such as the UNESCO Unitwin network for the Complex Systems Digital Campus and participation in the Conference on Complex Systems (CCS/ECCS). The recent publications highlight a strong interdisciplinary focus, combining network science, data analysis, and social theory. Key themes include the modeling of malaria transmission, information diffusion in social media, structural inequality in education, and the dynamics of opinion and popularity. His work often employs agent-based models, temporal network analysis, and entropy-based measures, reflecting a deep integration of computational and theoretical approaches. Research Methods for Doctorate in Complexity Sciences Advanced Topics in Complexity Sciences Data Science Fundamentals Development for the Internet and Mobile Applications Web Interfaces for Data Management Advanced Network Analysis Jorge Louçã has supervised over a dozen doctoral and master’s students, with completed theses on topics such as malaria modeling, information diffusion, temporal networks, and social inequality. His research has been supported by projects like NESS (Non-Equilibrium Social Science in ICT and Economics), reflecting his leadership in interdisciplinary science. He has held significant academic management roles, including Director of the Department of Information Science and Technology and head of multiple degree programs. His work continues to bridge computer science, social science, and policy, positioning him as a key figure in the global complexity science community.

• Game Theory
• Epistemic Game Theory
• Quantum Game Theory
• +۷ مورد دیگر

Adam M. Brandenburger is the J.P. Valles Professor at the Leonard N. Stern School of Business, New York University, with additional appointments as Distinguished Professor at the Tandon School of Engineering, Faculty Director of the NYU Shanghai Program on Creativity + Innovation, and Global Network Professor. He previously served as a professor at Harvard Business School from 1987 to 2002. His academic foundation includes a B.A., M.Phil., and Ph.D. from the University of Cambridge. His research focuses on game theory , epistemic game theory , quantum game theory , and business strategy . He has made foundational contributions to the understanding of rationality, belief hierarchies, and the intersection of quantum mechanics with decision theory. His work spans economics, philosophy, computer science, and cognitive neuroscience, reflecting a deeply interdisciplinary approach. The recent publications show a strong trend toward integrating quantum foundations , information theory , and behavioral economics . Themes include epistemic reasoning in non-classical systems, the role of symmetry in strategic interactions, and the neural basis of decision-making. His work increasingly explores the limits of classical probability and cognition, using tools from quantum information and sheaf theory. While no formal scientific awards are listed, his publications in Nature Communications , Econometrica , and Philosophical Transactions of the Royal Society indicate high scholarly impact. His collaborations with leading researchers across disciplines suggest a central role in advancing interdisciplinary science. He advises and collaborates extensively, though specific students are not listed. His leadership in the NYU Shanghai Program on Creativity + Innovation highlights his commitment to global education and innovation. He has not received any grants explicitly mentioned, but his sustained publication output suggests active funding support. He is associated with research initiatives bridging game theory, quantum information, and cognitive science. His recent unpublished work on quantum-assisted observatories and large language models points to forward-looking research at the intersection of AI, quantum technology, and strategic reasoning.

Eva Erikssonمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Participatory Design
• Interaction Design
• +۷ مورد دیگر

Eva Eriksson is an Associate Professor at Aarhus University, affiliated with the School of Communication and Culture and the Department of Digital Design and Information Studies. Her work bridges design, technology, and social values, focusing on participatory and human-centered approaches. Her research interests center on Human-Computer Interaction (HCI) , Participatory Design , and Design for Sustainability . She explores how co-design methods can empower youth, support children with learning differences like dyscalculia, and integrate more-than-human perspectives—considering non-human actors such as nature and technology—in design processes. Her work emphasizes ethical, inclusive, and reflective design practices. The recent publications highlight a strong trend in co-design with youth , XR and AR for education , sustainable technology , and methodological innovation in design research . These works span case studies, scoping reviews, and conceptual provocations, often published in top-tier venues like CHI and Interacting with Computers . Honourable Mention Award at CHI 2020 Honorable Mention, Design Space, CHI 2021 Most Cited Paper of 2021, International Journal of Child-Computer Interaction Eva Eriksson leads and contributes to externally funded research projects such as COMPILE (focused on dyscalculia and AR) and MOVA (on more-than-human values in design education), supported by the Independent Research Fund Denmark and Erasmus+. She supervises student projects and teaches courses such as Co-design and Bachelor Project . She also serves on international PhD examination and evaluation panels, demonstrating her active role in the global academic community. She is a core member of the Center for Computational Thinking & Design (CCTD) , a multidisciplinary research center at Aarhus University that fosters innovation in design, education, and technology.

Peter Buiمشاهده پروفایل

استاد آموزشی

• Systems Programming
• Operating Systems
• Parallel Computing
• +۶ مورد دیگر

Peter Bui is a Teaching Professor in the Computer Science and Engineering department at the University of Notre Dame , located within the College of Engineering. He teaches courses such as Data Structures, Systems Programming, and Ethical and Professional Issues, while also managing the core Elements of Computing programming sequence for the Computing & Digital Technologies minor. Education: Ph.D. in Computer Science and Engineering from University of Notre Dame (2012) His research interests span systems programming, operating systems, parallel computing, cloud computing, distributed computing, programming languages, compilers, and web services . He actively integrates these domains into his teaching and extracurricular work with the Linux Users Group. Recent publications highlight his work in distributed computing frameworks , including the development of tools like WorkQueue and Madeup for scalable scientific workflows and 3D printing integration. Projects such as ROARS and Weaver demonstrate his focus on robust data management and workflow automation. Outside academia, he stewards the Linux Users Group , engages with open-source communities, and balances personal interests like gaming in RuneScape with family time.

Sameer Deshpandeمشاهده پروفایل

استادیار

• Bayesian hierarchical modeling
• Bayesian regression trees
• Causal inference
• +۳ مورد دیگر

Sameer Deshpande is an Assistant Professor in the Department of Statistics at the University of Wisconsin–Madison. His research bridges Bayesian methodology development with applications in public health and sports analytics. Prior to joining UW–Madison, he completed a postdoctoral fellowship with Professor Tamara Broderick at MIT and earned his Ph.D. in Statistics from the Wharton School under Professors Ed George and Veronika Rockova. His educational background includes undergraduate studies in mathematics at MIT and a year at Jesus College, Cambridge through the Cambridge-MIT Exchange program. His research focuses on advancing Bayesian hierarchical modeling, treed regression, and causal inference techniques, with particular emphasis on flexible tree-based methods like BART variants for complex data structures. Deshpande's recent publications reveal a strong trend toward developing scalable Bayesian methods for high-dimensional data while maintaining rigorous uncertainty quantification. His work frequently applies these techniques to sports analytics (particularly baseball and football) and public health studies examining long-term effects of adolescent sports participation. The consistent focus on methodological innovation paired with substantive applications demonstrates his dual commitment to statistical theory and real-world impact. He actively mentors graduate students at UW–Madison, requiring STAT 775 as preparation for research collaboration. His Deshpande Lab focuses on Bayesian computation and causal inference, though specific grant details are not publicly listed. Notable projects include the NFL Big Data Bowl submission analyzing quarterback decision-making using Expected Hypothetical Completion Probability. Outside academia, Deshpande maintains interests in cooking, cocktail making, and photography, while remaining a devoted fan of Dallas sports teams – often seen wearing a Texas belt buckle.

Ulrich Schroedersمشاهده پروفایل

استاد

• Psychological Diagnostics
• Technology-based Competency Diagnostics
• Measurement of Cognitive Abilities
• +۵ مورد دیگر

Ulrich Schroeders is a Professor of Psychological Diagnostics at the University of Kassel, where he has been employed since October 2017. His work focuses on developing and validating psychological assessment tools, with particular expertise in cognitive diagnostics and educational measurement. He teaches various programs for approximately 500 students annually and serves as a supervisor for teacher training students preparing for their oral state examinations in Pedagogy/Psychology. Dr. Schroeders earned his PhD from Humboldt University of Berlin in 2010 with a dissertation titled "Measurement of Cognitive Abilities Using Modern Technologies: Artifacts, Equivalence, and New Constructs." Prior to that, he completed his Diploma in Psychology at Julius-Maximilians-University Würzburg in 2004 with a thesis on diagnosing dyscalculia in first-grade students. His research spans several key areas in psychological assessment. He specializes in technology-based competency diagnostics, developing innovative methods for measuring cognitive abilities and school competencies. A significant portion of his work involves applying Machine Learning and metaheuristics to psychometric problems, particularly in structural equation modeling. His methodological expertise includes advancing techniques in Local Structural Equation Modeling (LSEM) and Meta-Analytic Structural Equation Modeling (MASEM), with applications across educational and clinical psychology contexts. Analysis of Dr. Schroeders' recent publications reveals a strong focus on computational approaches to psychological assessment. His work frequently employs optimization algorithms like Ant Colony Optimization and Bee Swarm Optimization to address challenges in test construction and validation. There's a clear trajectory toward game-based and technology-enhanced assessment methods, as seen in studies using Mastermind and Wordle as assessment tools. His research also demonstrates growing interest in applying machine learning to predict behavioral outcomes, including juvenile delinquency, suicide risk, and psychotherapy outcomes. Dr. Schroeders has secured significant research funding, including projects funded by the German Research Foundation (DFG) and the Hector Foundation. His current projects include "Facing the Replication Crisis in Machine Learning Modeling" (2025-2027) and "PINGUIN: Potenzialidentifikation IN der GrUndschule" (2024-2027), which focuses on identifying elementary students' initial competencies. He leads the development of the BEFKI assessment system (Berliner Test zur Erfassung fluider und kristalliner Intelligenz), which includes versions for different age groups (5-7, 8-10, and 11+). His methodological toolbox includes specialized approaches for test construction and validation, particularly focusing on optimization algorithms applied to psychological measurement problems.

Éva Tardosمشاهده پروفایل

استاد

• Algorithms
• Algorithmic Game Theory
• Network Games
• +۳ مورد دیگر

Éva Tardos is a Professor of Computer Science at Cornell University, holding the prestigious Jacob Gould Schurman Professorship . Her research spans theoretical computer science, with a focus on algorithms and game theory in decentralized systems. Education : DiplMath (1981), PhD (1984) from Eötvös Loránd University under advisor András Frank Her work addresses algorithmic challenges in networks and auctions, ensuring provably optimal outcomes despite user selfishness. She has contributed to programs at Cornell including Learning and Games (Spring 2022) , Real-Time Decision Making (Spring 2018) , and Economics and Computation (Fall 2015) . Key Research Areas : Algorithm design, Game theory, Network optimization, Auction mechanisms, Complexity analysis Scientific Awards : Jacob Gould Schurman Professor of Computer Science

• Big data analytics
• Data analysis
• Data management
• +۸ مورد دیگر

Daniele Apiletti is an Associate Professor at the Polytechnic University of Turin , affiliated with the Department of Control and Computer Engineering (DAUIN). He serves as a member of the Interdepartmental Center SmartData@PoliTO and acts as Academic Advisor for the Master's degree program in Data Science and Engineering. Research Groups: DBDM - Database and Data Mining Group (DAUIN) ERC Sectors: Algorithms, Artificial Intelligence, Machine Learning, Web and Information Systems Research Interests span Big Data Analytics, Data Science, Machine Learning, Computer Vision, and Quantum Computing. His work focuses on integrating data-driven and theory-guided approaches for heterogeneous data querying, cloud continuum machine learning, and spatio-temporal models for crisis management. Recent Publications highlight trends in medical image segmentation, predictive industrial modeling, and fault-tolerant data systems. Key subfields include AI in healthcare, scalable manufacturing analytics, and vision-language models for game tutorials. Teaching roles include course ownership of Big Data: Architectures and Data Analytics and Internships across multiple academic years. He has collaborated on courses in Data Science, Database Technologies, and Data Management. PhD Students Supervised: Etibar Vazirov (Cloud Continuum Machine Learning) Gabriele Scaffidi Militone (Cloud Storage Microservices) Daniele Rege Cambrin (Spatio-Temporal Ecology Models) Simone Monaco (Theory-Guided Data Science) Research Projects include commercial contracts on: - Natural language querying of corporate research archives - National tourism ecosystem platforms - AI for thermotechnical system design - Machine Learning in clinical trials and supply chains

Benjamin Lubinمشاهده پروفایل

دانشیار بالینی

• Mechanism Design
• Combinatorial Auctions
• Spectral Graph Theory
• +۴ مورد دیگر

Benjamin Lubin is a Clinical Associate Professor in the Information Systems Department at Boston University's Questrom School of Business. He holds office 621A in the Rafik B. Hariri Building at 595 Commonwealth Avenue, Boston, MA 02215. His academic journey began with a Bachelor's degree in Computer Science from Harvard University in 1999, followed by six years working at BBN Technologies, where he contributed to advanced multi-agent modeling, scheduling, and logistics systems. He later returned to Harvard to complete his Ph.D. at the intersection of computer science, game theory, and economics. Dr. Lubin's research spans three primary areas: (1) mechanism design, particularly combinatorial auctions and exchanges that support efficient reallocation of goods with complex participant preferences; (2) application of spectral graph theory to advance social network analysis; and (3) leveraging network science and machine learning to improve healthcare delivery systems. His work demonstrates a consistent pattern of bridging theoretical computer science with practical economic applications, with recent publications showing increasing focus on healthcare applications while maintaining strong contributions to auction theory and network analysis. His research has been supported by significant funding from NIHCM and the Veterans Administration, and he has received prestigious recognition including the Siebel Fellowship and Yahoo Key Technical Challenge award. Dr. Lubin has mentored numerous graduate students including PhD candidates Vatche Ishakian, Marisabel Guevara, and Sarah Zheng, as well as Master's students Benedikt Buenz and Michael Weiss. Siebel Fellowship Yahoo Key Technical Challenge award As an educator, Dr. Lubin teaches several courses including IS 710 (Core MBA Class on Information Systems), IS 716 (Accelerated Part-Time Evening MBA), IS 717 and IS 756 (MSMBA Intensives), and QD601x (Business Experimentation on edX). His teaching materials include innovative approaches like using adventure games to teach web development and creating practical exercises for understanding analytics in business contexts. He has developed several software tools including JOpt for MIP programming, the Iterative Combinatorial Exchange market software, InvEigen for inverse eigenvector problems, SpectralGOF for network model goodness-of-fit testing, and SATS for spectrum auction instance generation.

Shaundra B. Dailyمشاهده پروفایل

استاد

• Identity-inclusive computing
• Human-centered design & engineering
• Justice-centered STEM education
• +۵ مورد دیگر

Shaundra 'Shani B' Daily serves as the Cue Family Professor of the Practice in the Department of Electrical and Computer Engineering at Duke University's Pratt School of Engineering. She also holds appointments as Professor of the Practice of Computer Science and serves as Faculty Director of the Duke Technology Scholars program. As a core faculty member in Innovation & Entrepreneurship and one of Duke's inaugural Levitan Faculty Fellows, Daily plays a pivotal role in connecting faculty with undergraduate residential life through the QuadEx initiative. Daily's educational background includes a Ph.D. from the Massachusetts Institute of Technology (2010), an S.M. from the MIT Media Lab, and B.S. and M.S. degrees in Electrical Engineering from the Florida Agricultural and Mechanical University – Florida State University College of Engineering. Her academic journey includes previous positions as an Associate Professor with tenure at the University of Florida (2015-2017) and Associate Professor in the School of Computing at Clemson University (2011-2015). Daily's research focuses on analyzing, designing, and building sociotechnical systems to support meaningful participation and success in STEM fields. Her work encompasses four interconnected strategies: understanding sociotechnical ecosystems through mixed methods approaches; employing participatory approaches that empower communities to shape technology development; designing technologies that enhance emotional development and interpersonal skills; and building supportive infrastructure through programs and curricula. Her research areas include identity-inclusive computing, human-centered design and engineering, and justice-centered STEM education, with particular emphasis on creating pathways for historically underrepresented groups in computing. Analysis of Daily's recent publications reveals a consistent focus on embodied approaches to computational thinking education, particularly through dance and movement-based learning. Her work bridges computer science education with affective computing, exploring how technologies can support emotional development while teaching technical skills. A significant thread throughout her research is the development of inclusive computing environments that address systemic barriers faced by women and underrepresented minorities in STEM fields. Educator of the Year, ACHI Magazine (2022) Program of the Year, CoNECD Conference (2022) North Carolina Black STEM Leaders, Governor Roy Cooper (2022) Capers and Marion McDonald Award for Excellence in Mentoring and Advising, Pratt School of Engineering (2021) Undergraduate Mentor of the Year, Mary Lou William Center for Black Culture (2020) Technology, Instruction, Cognition and Learning Early Career Research Award, American Education Research Association (2015) Daily has secured over $40 million in funding from public and private sources to support her collaborative research activities. Notable recent grants include the NSF INCLUDES Alliance: The Alliance for Identity-Inclusive Computing Education ($10 million), the AI Institute: Athena, and The Alliance for Interdisciplinary Innovation in Computing Education-Postdoctoral Research Fellowship. As Faculty Director of Duke Technology Scholars, she oversees a program providing comprehensive support for students from underrepresented backgrounds. Daily also serves as Education and Workforce Director for the Athena AI Institute and was appointed to develop competencies for the National Academies' Future Of Data And Computing Committee. Through her work with the Alliance for Identity-Inclusive Computing Education and the Duke Technology Scholars program, Daily has established herself as a leader in creating supportive infrastructure for learners to thrive in STEM. Her approach combines technology development with programmatic interventions to address systemic barriers in computing education. As a Levitan Faculty Fellow, she continues to bridge the gap between academic research and residential student life, creating opportunities for meaningful faculty-student connections that support intellectual and personal development.

William Seamanمشاهده پروفایل

استاد

• Recombinant Poetics
• Neosentience
• Computational Creativity
• +۷ مورد دیگر

William Seaman is a Professor of Art, Art History & Visual Studies and a Professor of Music at Duke University since 2008. He is a Faculty Network Member of the Duke Institute for Brain Sciences and co-director of the Emergence Lab , focusing on the intersection of art, science, and computational creativity. His career spans institutions like MIT, the University of Wales, and the San Francisco Art Institute, where he earned his Ph.D. in Interactive Art. Education Ph.D., University of Wales (1999) M.S., Massachusetts Institute of Technology (1985) B.A., San Francisco Art Institute (1979) Seaman’s research centers on Recombinant Poetics , a framework for combining and recombining media (image, music, text) in interactive art. His Neosentience work proposes new AI paradigms inspired by human cognition, while his Computational Creativity explores how machines can augment creative processes. He employs game engines, cybernetics, and biomimetic computation to develop systems like the Insight Engine , which fosters cross-disciplinary thinking. His publications and artistic collaborations, including the book Neosentience | The Benevolence Engine and the album s_traits (praised by The New York Times ), reflect his commitment to blending poetic inquiry with scientific rigor. Current projects, such as the Seaman-Rössler Dialogues , examine chaos theory, information science, and physics. Scientific Awards Lifetime Achievement Award, ACM SIGGRAPH (2021) Honorable Mention, Ars Electronica Interactive Art (multiple) Intel Research Gift (3 years) Rockefeller Foundation Visual Arts Award Fulbright Distinguished American Scholar International German Video Art Prize NEA Fellowship Leonardo Award for Excellence Seaman teaches courses like Neosentience: A Potential Future Form of AI and Generative Media Authorship . He has advised research teams through Bass Connections and Computational Media, Arts & Cultures programs. His lab, the Emergence Lab , collaborates with composers, scientists, and technologists to push the boundaries of AI-driven art and education.