جستجوی استاد راهنمای دانشگاهی

Qian Yangمشاهده پروفایل

استادیار

• Human-AI Interaction
• User Experience (UX) Design
• Healthcare Technology
• +۴ مورد دیگر

Qian Yang is an Assistant Professor in Information Science at Cornell University, with a faculty appointment in Computer Science. Her research focuses on human-AI interaction, designing AI applications for healthcare, autonomous systems, and UX design. She holds a PhD in Human-Computer Interaction from Carnegie Mellon University and has industry experience in design consultancy (2007–2014). Yang co-directs the Cornell Digital and AI Literacy Initiative and is a Senior Fellow at the Cornell Brooks Tech Policy Institute. Her work emphasizes bridging AI technologies with societal needs, supported by awards like the Schmidt Futures AI2050 Fellowship. She leads the DesignAI research group, focusing on AI-driven design methods and tools for practitioners. Education: PhD in HCI (Carnegie Mellon), M.S. in HCI (CMU), M.Des in Design, B.Eng in Industrial Design (Shanghai Jiao Tong University). Research interests include AI ethics, healthcare decision support systems, and context-aware mobile services. Notable contributions include: Developing AI systems for life-critical healthcare decisions (e.g., artificial heart implants) Innovating UX design methods for integrating AI into practice Advancing human-centered AI evaluation frameworks Awards include the SIGCHI Outstanding Dissertation Award and AI2050 Fellowship. She actively collaborates across disciplines, with work published in top HCI venues like CHI and ACM Transactions.

• Medical Informatics
• Artificial Intelligence in Healthcare
• Healthcare Data Integration
• +۷ مورد دیگر

Prof. Martin Boeker is a Professor of Medical Informatics at the Technical University of Munich (TUM), affiliated with the TUM School of Medicine and Health. His work focuses on advancing healthcare through AI-driven solutions, interoperability frameworks, and precision medicine initiatives. Key projects include the German Medical Text Corpus (GeMTeX) and the MIRACUM DIFUTURE Alignment Hub. Expertise: Medical Informatics, AI in Healthcare, Federated Learning, Health Data Integration Key Contributions: FHIR-based systems, clinical decision support, patient-centered outcomes research Leadership: Director of the Institute for AI and Informatics in Medicine at TUM Hospital Right of the Isar Research emphasizes bridging clinical practice and data science through projects like modular health crawlers, automated guideline adherence monitoring, and cross-institutional medical NLP solutions. His work spans oncology informatics, rare disease management, and pandemic response data ecosystems. Recent articles highlight innovations in digital twins for precision oncology, federated analysis in oncology, and German-language medical NLP challenges. He collaborates internationally on EHR standardization and healthcare interoperability, contributing to the Medical Informatics Initiative (MII) and pandemic evidence ecosystems. Grants and collaborations involve the German Federal Ministry of Education and Research, European initiatives, and industry partnerships. Educational efforts focus on training future medical informatics professionals through MII competency programs.

Ivan Flechaisمشاهده پروفایل

دانشیار

• Security Engineering
• Human-Computer Interaction
• Usable Security
• +۳ مورد دیگر

Ivan Flechais is an Associate Professor in Software Engineering at the Department of Computer Science, University of Oxford. His work focuses on the intersection of security engineering and human factors, developing approaches that balance technical security requirements with usability considerations in real-world contexts. Dr. Flechais earned his BSc and PhD in Computer Science from University College London. He holds dual French-British nationality and was educated in France until university level. His academic journey reflects an international perspective that informs his research on security systems across different cultural contexts. Flechais's research centers on developing methods for creating secure systems that account for real-world usability constraints. His work addresses the complex challenge where security competes with other system requirements like functionality, usability, and efficiency. He is particularly known for developing the AEGIS design methodology, which provides a cost-effective approach to security design that incorporates usability considerations. His current research explores socio-organizational factors in secure systems design, with recent work focusing on smart home security and privacy, remote work security challenges, and the intersection of security culture with technical implementation. His publication record shows a strong trajectory in usable security research, with recent work (2020-2024) increasingly focused on smart home environments, privacy in domestic settings, and the security challenges of remote work. His research demonstrates consistent attention to the human element in security systems, examining how users interact with security mechanisms in real-world contexts across different cultural settings and technological domains. Smart home security and privacy challenges User experience of security mechanisms Socio-organizational aspects of security implementation Cross-cultural security and privacy considerations Security for distributed and remote work environments Dr. Flechais has supervised numerous PhD and Master's students, including Sarah Alromaih, Varad Vishwarupe, George Chalhoub, and Martin J. Kraemer, among others. His supervision work often focuses on the practical application of security principles in emerging technologies, with students frequently examining security challenges in smart homes, IoT devices, and remote work contexts. His research has been supported through various projects including webinos and Sponstaneous Security, which address security challenges in distributed mobile applications and ad-hoc network environments.

Masood Masoodianمشاهده پروفایل

دانشیار

• Interactive Visualization
• Design Thinking
• Health Informatics
• +۳ مورد دیگر

Masood Masoodian is an Associate Professor in the Department of Art and Media at Aalto University, Finland. He leads the Visual Communication Design research group, focusing on interactive visualization for health, energy, and sustainability contexts. Previously, he held roles at the University of Waikato (2000-2016), University of Southern Denmark, and Massey University. Education: Doctoral degree in Other disciplines from the University of Waikato (1999) Research interests include design thinking, visualization of complex data, and creative aging interventions. Notable projects include the EU-funded INT-ACT initiative (2024-2026) addressing intangible cultural heritage. He has received an award for collaborative work on video game ludonarrative analysis (2019). Recent activities include organizing workshops on map-based interfaces, co-creating cultural heritage methods, and delivering public talks on digital design. Supervised two theses and contributed to 131 peer-reviewed outputs, emphasizing human-centered design and sustainability. Grants: Principal investigator for multiple EU projects totaling over 3 years of active funding. Awards: Prize for 'Comedy in the Ludonarrative of Video Games' (2019). Labs/Teams: Visual Communication Design group, collaborating internationally on projects like INT-ACT's cultural heritage mapping.

• Cloud Computing
• Databases
• Distributed Systems
• +۳ مورد دیگر

Aaron J. Elmore is an Associate Professor in the Department of Computer Science and the College of the University of Chicago. His research focuses on cloud computing, databases, and distributed systems, with an emphasis on resource-efficient database execution and collaborative analytics. PhD in Computer Science from University of California, Santa Barbara MS in Computer Science from University of Chicago Research interests include: Elastic databases and multitenancy (Database-as-a-Service) Resource-efficient systems (CrocodileDB, DenseStore, EdgeTSD) Database versioning (Datahub, Decible, OrpheusDB) Data discovery (DataSwamp, Relic) Recent publications highlight advancements in cloud-native query execution, dynamic compression frameworks, and time-series anomaly detection. His work often bridges systems design with practical data science applications. Scientific awards include: NSF CAREER Award (2021) Multiple Google and Intel research grants ACM SIGMOD Best Demo Honorable Mention Aaron has advised multiple PhD students including Jun Hyuk Chang and Riki Otaki, with former advisees now at institutions like MIT, Harvard, and UC Berkeley. He leads the ChiDATA research group and collaborates with Systems Group and CERES Center.

Mikael B. Skovمشاهده پروفایل

استاد

• Human-Computer Interaction
• Artificial Intelligence
• Robotics
• +۶ مورد دیگر

Mikael B. Skov is a Vice Dean and Professor at the Technical Faculty of IT and Design of Aalborg University , Denmark. His research spans human-AI interaction, robotics, and user experience, with a focus on trust signaling in clinical AI, swarm robotics, and sound zones for domestic environments. Role: Vice Dean for Research Department: Computer Science Research Interests: Skov investigates how humans interact with AI and robots in healthcare and domestic settings, emphasizing trust calibration, alert design, and acoustic comfort. His work includes developing frameworks for UX maturity in robotics organizations and studying long-term adoption of sound zone systems. Recent Projects: As principal/co-investigator, he leads the HERD project on human-AI collaboration in robot swarms (2021–2025) and supervises Data og Bæredygtig Mad (2020–2023), an HCI perspective on sustainable food systems. Publications: His 2024 work includes studies on AI explanations in clinical training, music applications with intermittent interactions, and multi-robot supervision. Earlier projects (2001–2020) focused on mobile device usability, UX practices, and context-aware computing.

Vera Liaoمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Human-AI Interaction
• Responsible AI
• +۶ مورد دیگر

Vera Liao is a Principal Researcher at Microsoft Research, where she is part of the FATE (Fairness, Accountability, Transparency, and Ethics of AI) group. She will join the University of Michigan Computer Science and Engineering department as an Associate Professor in fall 2025. Her work focuses on human-AI interaction, explainable AI, and responsible computing. Liao has made significant contributions to IBM products such as AI Explainability 360 and Uncertainty Quantification 360 during her time at IBM T.J. Watson Research Center. Dr. Liao received her education from the University of Illinois at Urbana-Champaign and Tsinghua University. Her academic journey has positioned her at the intersection of human-computer interaction and artificial intelligence, with a strong emphasis on creating AI systems that are transparent, accountable, and user-centered. Vera Liao's research primarily centers around human-centered AI explainability and transparency. She investigates how to design AI systems that effectively communicate their capabilities, limitations, and decision-making processes to users. Her work examines the intersection of AI transparency with trust, control, and user experience. Liao has pioneered approaches to bridging the socio-technical gap in AI evaluation and has developed frameworks for contextualized evaluation of explainable AI systems. Her research spans multiple domains including conversational interfaces, data storytelling, and creative work with generative AI. Liao's publications reveal a clear trend toward addressing the challenges of large language models and their impact on human-AI interaction. Her recent work focuses on understanding how uncertainty communication affects user trust, how to design for appropriate reliance on AI systems, and how to create authentic co-creation experiences with generative models. She has been examining the risks in AI-infused information ecosystems and developing methods for human-centered evaluation of language technologies. Her scientific contributions have been recognized with multiple honors: Best Paper Award, Honorable Mention at CHI 2025 (two papers) Best Paper Award at CHI 2024 Best Paper Award, Honorable Mention at FAccT 2023 Best Paper Award, Honorable Mention at HCOMP 2022 Best Paper Award, Honorable Mention at CHI 2021 Best Paper Award, Honorable Mention at CHI 2014 Outstanding Paper Award at IUI 2019 Dr. Liao is an active mentor, having guided numerous research interns from top universities including Cornell, Princeton, CMU, Stanford, and MIT. She serves in editorial roles as Co-Editor-in-Chief of the Springer Human-Computer Interaction Book Series and as an Editor for ACM CSCW. Liao has secured research funding through her work at Microsoft Research and previously at IBM, focusing on projects related to AI explainability, transparency, and responsible AI development. As part of Microsoft Research's FATE group, Liao collaborates with a multidisciplinary team of researchers focused on the ethical implications of AI technologies. Her work bridges the gap between technical AI development and human-centered design principles, ensuring that AI systems are developed with user needs and societal impacts in mind.

Victoria Lemieuxمشاهده پروفایل

استاد

• Blockchain Technology
• Trustworthy Records
• Records and Information Management
• +۸ مورد دیگر

Victoria Lemieux is a Professor at the University of British Columbia (UBC) Faculty of Arts, School of Information, and Cluster Lead for Blockchain@UBC, Canada’s largest research cluster focused on blockchain technology. Her research centers on risks to trustworthy records in blockchain systems and their impact on transparency, financial stability, and human rights. She has pioneered Canada’s first research-oriented graduate blockchain training program and organized multiple interdisciplinary summer institutes. Education: Ph.D. in Archival Studies from University College London (2002), Certified Information Systems Security Professional (CISSP, 2005). Affiliated with UBC’s Peter Wall Institute for Advanced Studies, Sauder School of Business, and Institute for Computers, Information and Cognitive Systems (ICICS). Research interests span blockchain technology , trustworthy records , risk management , information governance , and visual analytics , with recent work addressing healthcare data frameworks, Web3 AI integration, and socio-cultural dynamics of decentralized systems. She has published extensively on blockchain applications in archives, land transactions, and privacy-preserving technologies. Scientific Awards : 2015 Emmett Leahy Award 2015 World Bank Big Data Innovation Award 2016 Emerald Literati Award 2016 Emerald Literati Outstanding Paper Award Supervision: Currently accepts doctoral students in Computational Archival Science and blockchain-related archival research. Affiliated with the Blockchain@UBC cluster and multidisciplinary research teams exploring decentralized systems for social good.

Qiaoning Carol Zhangمشاهده پروفایل

استادیار

• Human-AI Collaboration
• Human-Robot Interaction
• Human Factors in Automated Vehicles
• +۴ مورد دیگر

Qiaoning Carol Zhang serves as Assistant Professor of Human Systems Engineering within The Polytechnic School at Arizona State University's Ira A. Fulton Schools of Engineering. Her research investigates the critical intersection of human perception, social contexts, and emerging technologies including artificial intelligence, robotics, and automated vehicles, with emphasis on creating intuitive, user-friendly, and inclusive systems. Her academic foundation includes: Ph.D. in Information, University of Michigan (2023) M.S. in Industrial and Operations Engineering, University of Michigan (2018) B.S. in Industrial Engineering, Hunan University (2016) Dr. Zhang's research program centers on understanding how individual differences and social dynamics shape technology interactions. Key focus areas include Human-AI Collaboration , Human-Robot Interaction , Human Factors in Automated Vehicles , and User Experience Design . Her work employs interdisciplinary methodologies to ensure technology adapts to diverse user needs across complex socio-technical environments, particularly in transportation and healthcare robotics. Analysis of her 15 most recent publications (2021-2025) reveals dominant themes in trust dynamics within automated vehicles, with significant attention to explainable AI interfaces. Research consistently examines how voice characteristics (gender, similarity), explanation modalities, and individual differences (age, personality) impact cognitive and affective trust. Recent work extends to healthcare robotics for elderly populations using Kano model analysis to identify critical user requirements. No scientific awards are documented in the provided materials. Dr. Zhang actively recruits Ph.D. candidates and undergraduate/master's researchers with backgrounds in human-computer interaction, data science, and interdisciplinary fields (design, computer science, cognitive science). She emphasizes opportunities in transportation technology, healthcare robotics, AI, and UX research/design, requiring applicants to submit CVs, research statements, and representative work samples. While specific grants aren't detailed, her research scope indicates substantial funding in human factors and emerging technology domains. Her research team focuses on developing empathetic technology through projects examining trust calibration in automated vehicles and healthcare robot design for older adults. Current initiatives include voice interface optimization for diverse user groups and Kano model applications in home healthcare robotics, aiming to bridge technical capabilities with human-centered design principles.

Jun Liمشاهده پروفایل

استاد

• Applied Statistics
• Bioinformatics
• Biostatistics
• +۴ مورد دیگر

Jun Li is a Full Professor in the Department of Applied and Computational Mathematics and Statistics at the University of Notre Dame's College of Science. He specializes in developing statistical and computational methods for big data, with a focus on interdisciplinary applications in bioinformatics, machine learning, and data mining. His career includes tenure as an Assistant Professor (2012–2017) and promotion to Associate Professor (2017) before becoming Full Professor (2020). Dr. Li holds a Ph.D. in Statistics from Stanford University (2012), supervised by Robert Tibshirani, and earlier degrees from Tsinghua University: a B.E. in Automation (2004) and an M.S. in Pattern Recognition and Intelligent Systems (2007). Research Interests : Dr. Li’s work centers on advancing computational frameworks for handling large-scale datasets, integrating statistical rigor with algorithmic innovation. Recent themes include AI-driven code improvement, ethical LLM applications in HCI, and GUI automation. His methodologies emphasize human-AI collaboration and transparency in algorithmic systems. Publications : His 2025 work explores LLM vulnerabilities in GUI agents, AI-assisted education tools like GLITTER, and ethical challenges in HCI research. Earlier studies (2024–2023) address topics such as natural language database queries, privacy-preserving app promotion analysis, and multimodal task learning. Lab/Teams : Affiliated with Notre Dame’s computational statistics research groups, focusing on interdisciplinary projects bridging statistics, computer science, and applied mathematics. His work often involves collaborations with industry and academic partners to translate theoretical advancements into practical applications.

Ronald Heddenمشاهده پروفایل

استاد

• Chemical Engineering
• Polymer Science
• Nanomaterials
• +۳ مورد دیگر

Ronald Hedden is a Professor of Practice in the Department of Chemical and Biological Engineering at Rensselaer Polytechnic Institute (RPI), where he focuses on innovations in undergraduate education and polymer science. Previously, he served as an Associate Professor at Texas Tech University (2009–2017). His current research emphasizes Virtual Reality (VR) integration into chemical engineering education, including the development of a Virtual Chemical Plant (VCP) simulation to provide safe, cost-effective access to process equipment. His research interests span chemical engineering, polymer science, soft materials, and nanomaterials. Notable projects include applying VR for teaching process safety and dynamics, as well as exploring nanocomposite materials and membrane technologies. He also investigates polymer rheology and structure-property relationships using advanced characterization techniques like NMR and SANS. Hedden teaches both core chemical engineering courses and interdisciplinary engineering subjects. His work bridges academic research and practical applications, with contributions to biofuel refining, asphalt modification, and nanoparticle incorporation in polymers. While no specific awards are listed, his extensive publication record highlights impactful contributions to materials science and educational technology. His advisory work involves student projects on VR simulations and materials engineering. He collaborates on initiatives like the VCP platform, aimed at advancing safety training and process control education. Hedden’s career reflects a commitment to both cutting-edge research and transformative pedagogy in engineering education.

Chinmay Kulkarniمشاهده پروفایل

استادیار

• Human Computer Interaction
• Large-scale Learning
• Automation
• +۵ مورد دیگر

Chinmay Kulkarni is an Assistant Professor at Carnegie Mellon University's Human-Computer Interaction Institute, where he leads the Expertise@Scale lab. His research integrates large-scale data and automation to transform learning, work, and mentoring systems. Education : Ph.D. in Computer Science from Stanford University (recipient of the Arthur P Samuel Award) Previous Affiliations : Microsoft Research, Barcelona Supercomputing Center His research spans: Human-Computer Interaction design for massive collaboration Voice-controlled interfaces and AI tools Future of work in remote/hybrid environments Behavioral economics through tech interventions Creative entrepreneurship support systems Algorithmic feedback in education Recent publications with AI and education focus show strong trends in voice technology, peer feedback mechanisms, and scalable learning platforms. His lab's systems have been used by >100,000 users across 150 countries. Scientific Awards : Arthur P Samuel Award (Stanford thesis award) Advising & Grants : NSF grant recipient US Department of Education funding Office of Naval Research support Departmental fellowship Labs : Directs Expertise@Scale lab developing systems adopted by Coursera and edX. Current research group includes PhD students Yasmine Kotturi, Julia Cambre, Pranav Khadpe and Masters student Sayan Chaudhry.

Margaret Burnettمشاهده پروفایل

استاد

• Software Engineering
• Human-Computer Interaction (HCI)
• End-User Programming
• +۵ مورد دیگر

Margaret Burnett is a Distinguished Professor at Oregon State University's School of Electrical Engineering and Computer Science (EECS). She specializes in software engineering, human-computer interaction (HCI), and inclusive design. Her research focuses on end-user programming, gender-inclusive software (via the GenderMag method), and improving accessibility in AI systems. She leads the EUSES Consortium and the AgAID Institute, fostering collaboration between academia and industry. Education: Ph.D., Computer Science (with honors), University of Kansas (1987–1991) M.S., Computer Science, University of Kansas (1979–1981) B.A. Mathematics, Cum Laude, Phi Beta Kappa, Miami University (1967–1970) Research & Awards: Recipient of the 2023 AnitaB.org Technical Leadership Abie Award, ACM Fellow, IEEE Fellow, and numerous university awards. Her work has been recognized for advancing inclusive design methodologies and mentoring students in computing. Teaching & Mentorship: Teaches courses like Inclusive Design with Personas (CS 468/568). Mentored over 50 graduate students, many of whom became professors, researchers, or UX professionals. Current students include Sadia Afroz, Alec Busteed, and Fatima Moussaoui. Labs & Collaborations: Leads the EUSES Consortium (multi-institution collaboration on end-user software engineering) and the AgAID Institute (AI for agriculture). Active in developing the GenderMag and InclusiveMag methodologies to address gender and socioeconomic biases in software.

Christof Lutterothمشاهده پروفایل

استاد

• Human-Computer Interaction
• Virtual Reality
• Eye-Gaze Interaction
• +۵ مورد دیگر

Christof Lutteroth is a Professor in the Department of Computer Science at the University of Bath and Director of the REal and Virtual Environments Augmentation Labs (REVEAL). His work focuses on Human-Computer Interaction (HCI) with emphasis on eye-gaze interaction and virtual reality (VR), particularly for health, exercise, and learning applications. He leads multiple research projects funded by organizations like EPSRC, The British Academy, and The Royal Society. Research Interests include developing gaze-controlled interfaces, immersive VR systems, and adaptive UI/UX for fitness and cognitive training. He explores affective design tools, emotion recognition in VR exergaming, and biometric data analysis for health applications. Recent Publications highlight advancements in gaze-based text entry, emotion measurement in VR, AI-driven UI development, and cross-European XR innovation networks. His work spans from foundational HCI methodologies to applied projects in rehabilitation and immersive learning. Grants include EPSRC IAA, British Academy, and Royal Society funding for projects like TapGazer, Hyper-immersive XR, and Affective Design Tools for VR. He collaborates with institutions across Europe through the EMIL project. Laboratory : REVEAL Lab at the University of Bath drives research in immersive technologies, motion analysis, and augmentation of human interaction with digital environments.

• Digital Media
• Artificial Intelligence
• Cognitive Science
• +۷ مورد دیگر

Brian Magerko is Professor of Digital Media in the School of Literature, Media, and Communication at Georgia Institute of Technology , where he also serves as Director of Graduate Studies for the Digital Media program and holds an adjunct appointment in the School of Interactive Computing . He directs the Expressive Machinery Lab and has led over $20 million in federally funded research at the intersection of cognition, computation, and creativity. Education Ph.D. Computer Science and Engineering, University of Michigan (2006) M.S. Computer Science and Engineering, University of Michigan (2001) B.S. Cognitive Science (minor Computer Science & Jazz Performance), Carnegie Mellon University (1999) Research Interests Dr. Magerko’s scholarship integrates cognitive science , AI , and computational media to investigate three core themes: (1) social and creative collaboration between humans and AI; (2) design of interactive narrative, music, and arts-based computational experiences; and (3) inclusive STEAM education that leverages personal expression—most notably through the widely-adopted EarSketch platform, which engages learners in computer science via music remixing and coding. Publication Trends Recent publications (2022-2025) reveal a surge in work on generative and co-creative AI systems , AI literacy frameworks , and accessible computing education . Studies span dance improvisation agents (LuminAI), inclusive design for blind and visually-impaired learners, and large-scale evaluations of creativity and learning outcomes in EarSketch classrooms across the United States. Awards & Honors Methods Paper Recognition, ACM CSCW 2022 Best Paper Award, ACM Creativity & Cognition 2021 & 2017 Ivan Allen College Researcher of the Year 2018 NCWIT Engagement Excellence Award 2017 Multiple Best Student Paper Awards (AIED 2021, ICCCI 2021) CETL Thank-a-Teacher Award 2008 Grants & Advising Dr. Magerko has served as PI or Co-PI on numerous NSF, NEA, and private foundation grants totaling more than $20 million. His projects fund interdisciplinary teams of graduate and undergraduate students, post-docs, and external collaborators, producing open-source software, museum installations, and K-12 curricula. Labs & Teams As head of the Expressive Machinery Lab , he mentors researchers creating AI partners for dance, drawing, music, and storytelling. The lab’s artifacts have been exhibited at the Smithsonian, ArtScience Museum Singapore, MoogFest, and other international venues.