جست‌وجوی استاد و پژوهشگر

Krishna Garikipatiمشاهده پروفایل

استاد

• Mathematical Biology
• Biophysics
• Materials Physics
• +۶ مورد دیگر

Prof. Krishna Garikipati is a Professor at the University of Michigan's College of Engineering and Mathematics, with an affiliation to the Center for South Asian Studies. He holds a PhD in Aeronautics and Astronautics from Stanford University, an MS from the same discipline at Stanford, and a BTech in Aeronautical Engineering from the Indian Institute of Technology. His research integrates nonlinear mechanics, materials physics, applied mathematics, and numerical methods, with a focus on mathematical biology, biophysics, and mechanics of biological systems. Current interests include tissue growth remodeling, cell adhesion, semiconductor materials, and multiscale material behavior. His work bridges computational and experimental approaches to address challenges in biological and engineering systems. While no specific awards are listed, his contributions span interdisciplinary applications of mechanics and mathematical modeling. He advises students across interdisciplinary programs, and his affiliations include roles in the International Institute at the University of Michigan.

• Accessibility
• Deaf Studies
• Human-Computer Interaction
• +۴ مورد دیگر

Abraham Glasser serves as an Assistant Professor in the Department of Accessible Human-Centered Computing within Gallaudet University's School of Science, Technology, Accessibility, Mathematics, and Public Health. His teaching portfolio includes graduate courses such as AHC-604 Applied Information Accessibility, AHC-691 Thesis Accessibility Project Planning, and specialized topics in accessibility standards and data visualization, reflecting his commitment to advancing accessible technology education. Professor Glasser's research centers on dismantling digital barriers for deaf and hard of hearing communities through innovative human-computer interaction solutions. His work pioneers sign language interfaces for personal assistants, investigates captioning system optimization, and explores AI-driven accessibility enhancements. Methodologically, he combines empirical user studies with technical development to create genuinely inclusive technologies that address real-world communication challenges faced by deaf users in digital environments. Analysis of his recent publications reveals a strong trajectory toward integrating artificial intelligence with accessibility needs, particularly through large language models for caption customization and robust sign language recognition systems. His research consistently prioritizes deaf user perspectives in technology design, with increasing focus on ethical AI implementation and workplace accessibility solutions as evidenced by his 2025 publications on employment barriers and AI action planning. Professor Glasser actively mentors graduate students, currently advising five master's candidates in accessibility-focused research. His professional service includes leadership roles as Chair for the ASSETS 2023 Student Research Competition and Associate Chair for ACM CHI 2024, demonstrating significant contributions to the accessibility research community. He has secured internal funding through Gallaudet's Faculty Development Committee grant to advance his accessibility initiatives.

• Information Systems
• Intelligent Agent Systems
• E-Learning
• +۵ مورد دیگر

Dongming Xu is a Professor at Sun Yat-sen University's School of Data and Computer Science, Department of Information Systems, with an extensive publication record spanning over two decades in the field of Information Systems. His scholarly contributions demonstrate expertise in intelligent agent systems, e-learning environments, digital innovation, and knowledge management, with recent work expanding into healthcare informatics, 5G technology, and FPGA design. Xu's research interests focus on the intersection of technology and human behavior, particularly examining how digital systems can enhance learning, financial management, healthcare delivery, and disaster response. His work employs both theoretical frameworks and practical implementations, often utilizing intelligent agents, machine learning techniques, and socio-technical perspectives to address complex information system challenges. Analysis of Xu's 15 most recent publications reveals a strategic evolution in research focus, beginning with foundational work in intelligent agent-supported systems and virtual learning environments, expanding into knowledge management and digital disruption theory, and most recently incorporating advanced technical implementations in wireless communications and hardware design. This progression demonstrates both theoretical depth and practical application across multiple domains. Multiple publications in top-tier Information Systems journals including Information Systems Journal, Journal of Global Information Management, and Decision Support Systems Regular contributions to premier conferences such as PACIS, ICIS, HICSS, and AMCIS Interdisciplinary research connecting computer science, business, healthcare, and social sciences Xu has established productive research collaborations with scholars across multiple institutions, particularly working with Huaiqing Wang, Jun Shen, Tingru Cui, and Geng Sun. His research has received consistent funding support, enabling sustained investigation into evolving information technology challenges. Current work shows increasing emphasis on AI applications in healthcare, advanced communication technologies, and digital platform ecosystems.

• Human-Computer Interaction
• Crowdsourcing
• Accessibility
• +۴ مورد دیگر

Walter S. Lasecki is an Associate Professor at the University of Michigan's School of Information, where he leads research at the intersection of Human-Computer Interaction, Crowdsourcing, and Artificial Intelligence. His work focuses on creating systems that integrate human and machine intelligence to solve complex problems in real-time. Dr. Lasecki's research interests center on human-AI collaboration, particularly in developing crowd-powered systems that enhance accessibility, improve programming education, and create more effective human-computer interfaces. His work explores how to effectively integrate human intelligence with AI systems, focusing on real-time applications where speed and accuracy are critical. His research has significant implications for accessibility technologies, educational tools, and conversational AI systems. He has pioneered approaches to real-time captioning, crowd-powered interfaces, and human-in-the-loop machine learning systems that adapt to user needs. Analysis of his recent publications reveals a strong focus on multi-agent conversational AI, human-in-the-loop systems for pose estimation and object recognition, and innovative approaches to programming education through live streaming. His research consistently explores the intersection of human computation and artificial intelligence, with particular attention to how crowd workers can complement and enhance AI capabilities. His work demonstrates a trajectory from foundational crowd-powered systems to more sophisticated integrations of human and machine intelligence in complex tasks. Dr. Lasecki has collaborated extensively with researchers across multiple institutions, particularly with Jeffrey P. Bigham (earlier in his career) and more recently with colleagues at the University of Michigan including Juho Kim. His research has been supported by substantial grants that have enabled the development of systems like Scribe for real-time captioning and Codeon for on-demand programming assistance. He has mentored numerous graduate students who have gone on to contribute to the fields of HCI and AI. His laboratory focuses on developing practical applications of crowd-AI hybrid systems, with particular emphasis on creating tools that can be deployed in real-world settings. Current projects explore how to make conversational AI more robust through multi-agent approaches, improve programming education at scale, and create more accessible interfaces for diverse user populations.

• Computer Science Education
• Artificial Intelligence Education
• K-12 Computer Science
• +۵ مورد دیگر

Fred G. Martin is a Professor in the Department of Computer Science at the University of Massachusetts Lowell's Manning College of Information Sciences. With a research career spanning over 25 years, his work has evolved from foundational educational robotics in the 1990s to contemporary AI literacy initiatives for K-12 students. His current research focuses on developing accessible tools and curricula that make artificial intelligence concepts tangible for middle school learners. Dr. Martin's research interests center on computer science education, particularly AI education for K-12. His work bridges theoretical computer science concepts with practical, age-appropriate learning experiences. He has pioneered approaches to teaching machine learning concepts through interactive tools like TrainYourSnakeAI for reinforcement learning and ChemAIstry for model training. His research consistently emphasizes ethical considerations in AI education, as seen in projects like AI MyData that integrate ethics into machine learning curricula. Martin's work demonstrates how complex AI concepts can be made accessible through carefully designed educational interfaces that balance engagement with conceptual accuracy. Analysis of Martin's recent publications reveals a clear trajectory toward increasingly sophisticated AI education tools for younger learners. His work has evolved from general computational thinking and robotics education to specialized AI literacy frameworks. The research shows strong emphasis on three interconnected themes: 1) developing age-appropriate metaphors for complex AI concepts, 2) creating interactive software tools that make abstract concepts tangible, and 3) investigating how students' mental models of AI develop through structured learning experiences. His collaborations often involve interdisciplinary teams including computer scientists, education researchers, and classroom teachers. Dr. Martin has been instrumental in building professional networks for computer science educators, particularly through projects that connect university researchers with K-12 teachers. His work on 'Building Teacher and Community Networks for Sustainable Middle School Computer Science Education' demonstrates his commitment to creating sustainable models for CS education beyond isolated curriculum initiatives. He has secured substantial research funding for projects focused on AI education, as evidenced by the scale and scope of his collaborative work across multiple institutions. Through initiatives like the 'iSENSE' project and more recent AI education tools, Martin has established research environments that bridge university labs with classroom settings. His work often involves creating physical or digital 'exhibits' that allow students to interact with AI concepts in hands-on ways, reflecting his longstanding interest in tangible interfaces for learning. These environments serve as testbeds for both educational research and practical curriculum development.

Saul Albertمشاهده پروفایل

مدرس ارشد

• Conversational AI
• Aesthetic Judgements
• Conversation Analysis
• +۳ مورد دیگر

Saul Albert is a Senior Lecturer in Social Science (Social Psychology) at Loughborough University, leading the Undergraduate Programme in Communication and Media. He holds a PhD from Queen Mary University of London’s Cognitive Science Research Group and conducted a postdoc at Tufts University’s Human Interaction Lab, focusing on conversation analysis and experimental psychology. His research bridges disciplines like HCI, psychology, and conversation analysis to explore how technology mediates social interaction, particularly in aesthetic evaluations and conversational AI limitations. He co-founded projects like GailBot, an automated transcription tool for CA, and Drawing Interactions, a methodological interface using artistic techniques for interaction analysis. His work spans methodological innovations, including collaborations with NHS on smart homecare systems and studies on dementia care interactions. Key themes include distributed agency in healthcare tech, ethical AI design, and public engagement with interaction research. He has published widely on topics like voice interface challenges, methodological fusion between CA and computational tools, and the role of rhythm in social practices. His interdisciplinary projects aim to create tools and frameworks for bridging academic and industry approaches to interaction studies. Albert’s research emphasizes empirical rigor and practical applications, with a focus on improving interactional understanding through cross-disciplinary collaboration. He actively engages in public science exhibitions to disseminate findings and challenges traditional methodological silos in social sciences.

Sang Won Leeمشاهده پروفایل

دانشیار

• Human-Computer Interaction (HCI)
• Computer-Mediated Empathy
• Creative Computing
• +۵ مورد دیگر

Sang Won Lee is an Associate Professor of Computer Science at Virginia Tech and a Visiting Researcher at NAVER AI Lab. His work focuses on Human-Computer Interaction (HCI), computer-mediated empathy, and creative computing. He explores technologies like VR, conversational agents, and live coding to foster empathy, support self-reflection, and enable inclusive collaboration. His research has been recognized with best paper awards at ACM CHI and Creativity & Cognition. He holds a Ph.D. in Computer Science from the University of Michigan, alongside degrees in Music Technology (Georgia Tech), Management Science (Stanford), and Industrial Engineering (Seoul National University). His teaching spans courses like Creative Computing Studio, Computer-Supported Cooperative Work, and Game Design. Research interests include: Empathy through interactive systems Music technology and live coding performances Collaborative tools for education and work VR/AR applications in learning Notable awards include the 2016 International Computer Music Association Award for his composition Live Writing: Gloomy Streets . Recent work explores AI ethics in education, voice agents in parent-child interactions, and cross-device mixed reality experiences. Active in both academic conferences (CHI, NIME) and artistic venues (ICMC performances), he bridges technical innovation with creative expression. His lab develops tools like TaskScape for holistic task management and Octave for spatiotemporal data analysis in construction education.

• Automatic Speech Recognition
• Conversational User Interfaces
• Human-Computer Interaction
• +۶ مورد دیگر

Prof. Hans-Peter Hutter is a Professor of Computer Science at the ZHAW School of Engineering, specializing in Deep Learning-based Automatic Speech Recognition, Conversational User Interfaces, and Human-Centered Computing. He leads the Human-Centered Computing research group at InIT/ZHAW and has held this position since 2005. His work focuses on accessibility technologies, mobile usability, and inclusive design for visually impaired users. Education: Dr. sc. techn. ETH in Computer Engineering (ETH Zurich, 1996) Dipl. El.-Ing. ETH in Electrical Engineering (ETH Zurich, 1986) Research Interests: Advancing accessibility in digital systems (e.g., accessible PDFs, navigation aids for visually impaired users) Speech recognition and dialogue systems Mobile application design principles Service engineering and platform development His recent work emphasizes multimodal interaction, accessible document remediation, and SLAM systems for navigation assistance. Projects: Leading the InCrowd-VI dataset project for indoor navigation Developing MathNet for mathematical expression recognition Creating accessible tourism services in Lake Constance region Grants & Labs: Active in EU-funded and industry collaborations, leading the InIT Institute founded in 2002. Collaborates with organizations like SwissICT and ACM.

Martin Gaedkeمشاهده پروفایل

استاد

• Web Engineering
• Knowledge Engineering
• Artificial Intelligence (AI)
• +۴ مورد دیگر

Prof. Dr.-Ing. Martin Gaedke is a Full Professor and Dean of the Department of Computer Science at Technische Universität Chemnitz (TU Chemnitz). He leads the research group Distributed and Self-organizing Systems (VSR) and holds roles such as President of the International Society of Web Engineering (ISWE), founder of the International AIQT Foundation, and member of the German Foundation for University Admissions' IT-advisory board. His expertise spans Web Engineering, AI-driven systems, and decentralized technologies. Education: Martin Gaedke earned a Master's degree (1997) and doctoral degree (2000) in Computer Science/Engineering from the University of Karlsruhe (now Karlsruhe Institute of Technology). Research Focus: Gaedke's work advances collaborative systems in hyper-connected societies, emphasizing Web Engineering, knowledge engineering, and AI-supported hypermedia systems. Key areas include chatbot design patterns, decentralized web trust, smart IoT systems, and end-user development tools. His contributions include pioneering work in Web Engineering since the 1990s, notably co-authoring the first Web Engineering paper at WWW6 (1997). Recent Trends in Publications: Recent research highlights dynamic code migration, GenAI-driven UIs, and ethical AI in chatbots. He emphasizes trust in decentralized systems (e.g., Solid-based social networks) and practical applications like autonomous smart home agents (WS3H). Awards: Ranked 39th globally in Knowledge Engineering (2020), honored with the AI 2000 Most Influential Scholars Honorable Mention and listed in the AI 2000 Annual List. His work is cited over 1,800 times in key areas like Web Engineering and IoT. Advising & Outreach: Gaedke has mentored numerous researchers and entrepreneurs through roles as a Certified High Performance Coach and business advisor. His lab, VSR, develops open-source tools like the Web-Based Network Simulator (WNSWE) for education and industry. Labs/Teams: The Distributed and Self-organizing Systems (VSR) group at TU Chemnitz focuses on innovative projects such as the Trusting Decentralized Web Data framework and the GenAI-Driven Multimodal UI Architecture .

• Pervasive Computing
• Artificial Intelligence
• Cybersecurity
• +۴ مورد دیگر

Nikhil Yadav, PhD, is an Associate Professor and Chair of the Computer Science Department at the University of San Diego's Shiley-Marcos School of Engineering. He holds a PhD from the University of Notre Dame, an MS from the University of Florida, and a BEng from the National University of Lesotho. His research focuses on pervasive computing, AI-driven context-aware systems, and healthcare technology innovation. Previously, Dr. Yadav served as computer science faculty at St. John's University in New York, where he led ABET accreditation efforts and developed internship programs. He currently advises Collidescope Inc. as their consulting CTO, focusing on social impact through ESG-oriented digital solutions. His industry experience includes software engineering roles and founding a startup leveraging speech biomarker analysis for mild traumatic brain injury (mTBI) assessment. Research themes span IoT security, healthcare informatics, and AI ethics. Notable projects include CRADLE—a psychophysiological analytics platform—and work on mobile health applications in underserved regions. His publications address edge AI deployment, cybersecurity in federated learning, and mental health prediction during public health crises. Teaching contributions include pioneering Python pedagogy in graduate data science curricula and integrating mobile healthcare projects in undergraduate courses. Professional service includes conference program committees and advocacy for secure ecological momentary assessments in clinical research.

Viktoria Pammer-Schindlerمشاهده پروفایل

دانشیار

• Human-Computer Interaction (HCI)
• Educational Technology (EdTech)
• AI in Education
• +۷ مورد دیگر

Assoc. Prof. Viktoria Pammer-Schindler is an Associate Professor in Human-Computer Interaction (HCI) and Educational Technology (EdTech) at Graz University of Technology. She is Deputy Head of the Institute of Human-Centred Computing and a research area head at the Know-Center. Her work focuses on interactive AI for productivity, learning, and socio-technical systems design. She teaches courses such as 'Designing Interactive Systems' and 'Conversational Systems,' and has received recognition for teaching excellence. Her research spans language-based interaction, workplace learning, and ethical AI, with over 50 peer-reviewed publications. She actively serves in roles like Special Issue Editor for IEEE Transactions on Technologies for Learning and President of the International Alliance to Advance Learning in the Digital Era. Affiliations: Graz University of Technology (Institute of Human-Centred Computing), Know-Center Research Areas: HCI, EdTech, AI ethics, conversational agents, workplace learning analytics, and socio-technical systems Her awards include the 2023 Outstanding Paper Award at Bled eConference and multiple teaching nominations. She advises over 20 graduate students and leads projects funded by national and EU grants. Current research explores generative AI in creativity, voice-based interaction, and ethics in professional learning technologies. She has supervised impactful theses on topics like GenAI for creative collaboration and AI-enabled environments for well-being. Her work bridges theory and practice through field studies in call centers, apprenticeships, and SMEs, emphasizing user-centered design principles.

Hui Fangمشاهده پروفایل

استاد

• Information Retrieval
• Text Mining
• Bioinformatics
• +۶ مورد دیگر

Prof. Hui Fang is a Professor in the Department of Electrical and Computer Engineering at the University of Delaware's College of Engineering. Her research focuses on overcoming information overload through advancements in text information management, including search engine technology, text mining, and bioinformatics. She has pioneered task-aware information retrieval frameworks and collaborates with domain experts in journalism and biology. Education : PhD from the University of Illinois at Urbana-Champaign. Research Interests : Information Retrieval (Search Engine Technology) Text Mining and Natural Language Processing Algorithmic Fairness and Bias Mitigation Conversational AI and Dialogue Systems Medical and Scientific Domain Retrieval Awards & Honors : JP Morgan Chase Interim Fellow/Scholar (2017-Present) David L. and Beverley J. C. Mills Career Development Chair (2016-2020) 2013 College of Engineering Excellence in Teaching Award ACM SIGIR 2004 Best Paper Award Advising & Lab Work : Leads the UDInfoLab, focusing on fair web search and conversational systems. Her work integrates interdisciplinary approaches to tackle challenges in scalable information access and ethical AI systems.

D. Keith Williamsمشاهده پروفایل

استاد

• Biostatistics
• Linear Models
• Statistical Graphics
• +۵ مورد دیگر

D. Keith Williams serves as Professor and Vice-Chair of Education in the Department of Biostatistics at the University of Arkansas for Medical Sciences (UAMS), with dual appointments in the College of Medicine and College of Public Health. He additionally directs Biostatistics and Data Innovation at ACNC, demonstrating leadership in academic administration and research infrastructure. His academic foundation includes: B.S. in Mathematics Education from University of Central Oklahoma M.S. in Statistics from Oklahoma State University M.P.H. from University of Oklahoma Ph.D. in Biostatistics from University of Oklahoma Dr. Williams' research centers on advanced statistical methodologies including linear models, graphical techniques, and simulation approaches. His current focus targets efficient analysis of complex multivariate datasets from microbiome, metabolic, genetic, and whole-organism studies. This work addresses critical challenges in handling high-dimensional biological data where traditional methods fail, particularly in modeling multiple interdependent responses common in modern biomedical research. Analysis of his 2024-2025 publications reveals a strong interdisciplinary pattern spanning pediatric obesity, pregnancy complications, toxicology, and nutritional science. His biostatistical expertise consistently enables novel insights across diverse domains—from cannabis extract pharmacology to rheumatoid arthritis immunology—by developing specialized analytical frameworks for complex datasets. A notable trend involves translating methodological innovations into clinical applications, especially for maternal-child health and metabolic disorders. As Vice-Chair of Education, Dr. Williams oversees biostatistics curriculum development and training programs. His directorship at ACNC involves leading data science initiatives that support UAMS research enterprise. While specific grant details aren't provided, his extensive publication record indicates sustained extramural funding. He directs the Biostatistics and Data Innovation unit at ACNC, which integrates statistical expertise with cutting-edge computational resources to advance research across UAMS. This role positions him at the nexus of methodological development and translational science, fostering collaborations between statisticians and domain experts in medicine and public health.

Michael Twidaleمشاهده پروفایل

استاد

• Digital Libraries
• Human-Computer Interaction
• Open Source Software
• +۶ مورد دیگر

Michael Twidale is an Interim Associate Dean of Faculty Affairs, Professor, and Director of the Ph.D. Program at the School of Information Sciences at the University of Illinois at Urbana-Champaign. He holds affiliate professorships at the Siebel School of Computing and Data Science, the Information Trust Institute, the National Center for Supercomputing Applications (NCSA), and the Beckman Institute for Advanced Science and Technology. His research focuses on digital libraries, human-computer interaction, open source software, and metadata. Twidale has been recognized with the ASIS&T Outstanding Information Science Teacher Award and the Clarivate Analytics Outstanding Information Science Teacher Award, both in 2017. His work emphasizes collaborative design, user experience, and the intersection of technology with community practices. He has advised on numerous projects involving cultural heritage digitization, educational technology, and software sustainability, and collaborates across disciplines to address challenges in information systems. Twidale’s research interests span digital libraries, human-computer interaction, and open source software development. He explores how users interact with information systems, including studies on metadata, mental models, and software usability. His work often bridges theory and practice, such as designing tools for cultural heritage communities or analyzing volunteer motivations in FLOSS projects. His recent studies investigate information seeking behaviors, metaphors in user interfaces, and confusion management in educational contexts. Key Collaborations: Projects with African universities, musicology initiatives, and software sustainability networks. Labs/Teams: Active in NCSA, Beckman Institute, and the School of Information Sciences’ research groups. Grants: Funding for collaborative design, digital humanities, and educational technology projects (details unspecified).

• Health Information Technology
• Older Adults Health
• Conversational Agents
• +۳ مورد دیگر

Jessie Chin is an Assistant Professor at the University of Illinois at Urbana-Champaign, holding affiliations across multiple institutions including the School of Information Sciences, Educational Psychology, Coordinated Science Lab, Beckman Institute, and National Center for Supercomputing Applications (NCSA). Her research focuses on health information technology, human-computer interaction, and aging populations. She investigates how conversational agents, voice user interfaces, and smart devices can improve health literacy, behavior change, and well-being among older adults. Education: Not explicitly stated in provided texts. Her work integrates cognitive science principles with design methodologies to create inclusive technologies. Key areas include: Co-designing voice interfaces for older adults Evaluating smart speaker feasibility in behavioral interventions Examining social dynamics in health peer discussions Exploring motivational states via large language models Recent studies highlight metaphor-driven conversational agent design, privacy considerations in aging tech, and health belief modeling through social media analysis. She collaborates across disciplines, leveraging computational methods and mixed-methods research to address health inequities and technology adoption barriers. Affiliated with interdisciplinary centers like the Beckman Institute and NCSA, her work bridges health informatics, AI ethics, and aging research.