Find Academic Supervisors

Jacob BiehlView profile

Associate Professor

• Human-Computer Interaction
• Internet of Things
• Computer Systems
• +5 more

Dr. Jacob Biehl is an Associate Professor at the University of Pittsburgh, jointly affiliated with the Institute for Creative Sciences (ICDS) and the Department of Computer Science within the School of Computing and Information. His research focuses on the intersection of Human-Computer Interaction (HCI), systems, and IoT technologies, particularly in healthcare and surgical workflows. He earned his Ph.D. (2008), MS (2004), and BS (2002) in Computer Science and Statistics from the University of Illinois, Urbana. Key research interests include IoT applications for workflow optimization, AR/VR systems in surgery, and sensor-based localization. His work emphasizes practical deployments in real-world settings, such as endoscopic surgery and medical device integration. Dr. Biehl holds 25 U.S. patents and has led industry and academic collaborations to design systems that enhance human-technology interaction. Notable contributions include the Surreality Lab’s AR tools for surgical navigation and machine learning models for medical diagnostics. He received the Best Journal Paper Award (2023) for work on visual feedback delays in AR surgical tasks. His projects address challenges in neurosurgery, orthopedics, and burn care, leveraging both technical innovation and interdisciplinary collaboration. Dr. Biehl’s academic leadership includes co-directing the Surreality Lab, which bridges computer science and medicine. His educational background and industry experience at FX Palo Alto Lab (Silicon Valley) inform his focus on scalable, user-centered technologies.

Martin HalveyView profile

Professor

• Information Retrieval
• Human Computer Interaction (HCI)
• Multimodal Interaction
• +3 more

Professor Martin Halvey is a leading academic in the Department of Computer & Information Sciences at the University of Strathclyde, serving as Head of Department. His expertise lies in information retrieval (IR), human-computer interaction (HCI), and multimodal interaction, with a focus on innovative technologies for search and information access. He teaches modules across faculties, including information retrieval, machine learning, big data, and business analysis. Education: PhD in Computer Science from University College Dublin (2007), BSc from University College Dublin (2003) His research emphasizes novel uses of multimodal technology to enhance search experiences, particularly in areas like conversational agents, driver awareness systems, and user effort evaluation. Key projects include the DoSSIER initiative for domain-specific information systems and studies on thermal feedback in mobile devices. Publications span topics such as conversational breakdown recovery, search result ranking, and user experience in automated vehicles. His work has been recognized with awards like the Best Paper Award at ACM CUI 2024 and the CSTG Mark Resnick Best Paper Award. Professional Activities: Organized workshops on Applied AI, presented on AI’s role in discovery, and served as an external examiner for computing programs. Grants/Projects: Principal Investigator on projects like EmergeAdapt TDL QuickStart and co-investigator on EU-funded DoSSIER. Labs/Teams: Active in the Scottish Informatics and Computing Science Alliance (SICSA) and Strathclyde iSchool.

• Human-Computer Interaction
• Virtual Reality
• Smart Textiles
• +2 more

Dr. Vijayakumar Nanjappan is a Lecturer/Assistant Professor in Human-Computer Interaction (HCI) at University College Cork's School of Computer Science and Information Technology. His research integrates HCI, Human-Centred Design, Smart Textiles, VR, and Digital Fabrication to develop sustainable solutions enhancing user experience. Recent publications explore affective textiles, VR-enhanced creativity, and digital fabrication education, demonstrating cross-disciplinary innovation. His work spans virtual reality applications for cultural priming and rehabilitation, smart textiles for emotional interaction, and pedagogical approaches in makerspaces. Award trends are not mentioned.

Toby Jia-Jun LiView profile

Assistant Professor

• Human-Computer Interaction (HCI)
• End-User Software Engineering
• Machine Learning (ML)
• +5 more

Toby Jia-Jun Li is an Assistant Professor in the Department of Computer Science and Engineering at the University of Notre Dame, leading the SaNDwich Lab and directing the Human-Centered Responsible AI Lab at the Lucy Family Institute for Data & Society. He holds a Ph.D. in Human-Computer Interaction from Carnegie Mellon University (2021) and a B.S. in Computer Science from the University of Minnesota (2015). His research focuses on empowering end-users through human-centered AI systems, particularly in areas like human-AI collaboration, end-user software engineering, and ethical AI integration into work environments. Education: - Ph.D., Human-Computer Interaction, Carnegie Mellon University, 2021 - B.S., Computer Science (Distinction), University of Minnesota, 2015 Research Interests : - Human-AI collaboration in work systems - Ethical AI design - Generative AI co-creation tools - Sociotechnical implications of automation - Privacy-aware interfaces Grants & Awards : - NSF grants for AI in gig work and privacy education - Google Research Scholar Award (2022) - Multiple best paper awards at CHI/UIST/CSCW Lab & Teams : - SaNDwich Lab (Social-AI-Not-Dumb-Computing) - Human-Centered Responsible AI Lab - Collaborations with industry (IBM, Microsoft, J.P. Morgan) and academia

Ronald A. MetoyerView profile

Professor

• Human-Computer Interaction
• Information Visualization
• Data Visualization
• +3 more

Ronald A. Metoyer is a Professor of Computer Science and Associate Dean of the College of Engineering at the University of Notre Dame. He holds a Ph.D. from Georgia Institute of Technology (2002) and a B.S. in Computer Engineering from UCLA (1994). His research focuses on Human-Computer Interaction (HCI), particularly in Information Visualization, addressing real-world decision-making tasks such as food insecurity, bias mitigation in reviews, and data-driven storytelling. He leads the Metoyer Lab, collaborating on projects like the National Institute for Food and Agriculture-funded Food Information Networks to combat food insecurity through technological interventions. Metoyer’s work spans interdisciplinary collaborations, including social sciences and public health, to design interfaces that empower end-users in complex data analysis. He has taught courses in HCI, data visualization, and computer graphics, and previously served as an Associate Professor at Oregon State University. His projects emphasize human-centered design, with applications in healthcare, education, and social equity. Key research areas include decision support systems, visual bias mitigation in holistic reviews, and sports data analysis. He has led funded initiatives on food access technology, community navigation tools for reintegration post-incarceration, and semantic search for social services. His lab’s work integrates qualitative data with computational methods to create impactful solutions for vulnerable populations.

Tracy Anne HammondView profile

Professor

• Sketch Recognition
• Artificial Intelligence
• Human-Computer Interaction
• +5 more

Tracy Anne Hammond is a Professor in the Department of Computer Science & Engineering at Texas A&M University, part of the College of Engineering. Her work focuses on sketch recognition, human-computer interaction, and cognitive behavior studies. She leads the Sketch Recognition Lab, exploring intersections between AI and HCI to address real-world data challenges. Education includes a Ph.D. in Computer Science from MIT, dual bachelor's degrees in Mathematics and Applied Mathematics from Columbia University, and an M.A. in Anthropology. Her interdisciplinary background combines technical expertise with social sciences. Research highlights include developing sketch recognition systems for diverse applications like Kanji character recognition and educational tools. Her work emphasizes perception-based interfaces and corrective feedback mechanisms. Recent projects address entropy-based diagram analysis and gesture recognition in office environments. Key awards: IAAI Deployed Application Award (2012), CHI Honorable Mention (2013), Barclay Engineering Fellow (2012) Lab locations: Engineering Activities Building C 112B & 112C Notable collaborations: MIT Oxygen Workshop, Brown University Pen-centric Computing Active in academia since 2000, she has mentored over 10 graduate students and holds multiple patents in interface technologies. Current research trends focus on reducing the gender gap in computer science through inclusive design principles.

Kim JeeeunView profile

Assistant Professor

• Digital Fabrication
• Human-Computer Interaction
• Human-Artificial Intelligence Interaction
• +3 more

Dr. Kim Jeeeun is an Assistant Professor in Computer Science & Engineering at Texas A&M University, directing the HCIED (HCI Engineering & Design) Lab. She holds a PhD (2019) and MS (2015) from the University of Colorado Boulder, and a BS (2010) in Computer Engineering from Korea Aerospace University. Her research focuses on digital fabrication , human-computer interaction , and design research , exploring how technology can democratize access to fabrication tools and improve human-AI collaboration. Notable projects include 3DPFIX (AI-driven 3D printing troubleshooting) and 3D4ALL (inclusion in 3D printing communities). Recent work includes: Instance detection in open-world scenarios (CVPR'25) LumosX: 3D-printed light-transfer materials (CHI'25) Material-driven rapid prototyping methodologies Recipient of prestigious awards including NSF CAREER Award (2024), TEES Young Faculty Fellow (2023), and Adobe Research Fellowship (2018). Active in academic service, serving as General Co-Chair for UIST'25 and PC roles in CHI/TEI/UIST conferences. Her lab develops tools like HowDIY to bridge fabrication expertise gaps, and OmniSoft for designing soft objects. Ongoing projects explore 4D printing hybrid approaches and energy-harvesting mechanisms (E3D).

Margot BreretonView profile

Professor

• Human-Computer Interaction
• Participatory Design
• Co-Design
• +3 more

Professor Margot Brereton is a leading researcher in Human-Computer Interaction at QUT's School of Computer Science. With a PhD from Stanford and over $6M in competitive grants, she specializes in participatory design for humanitarian technologies, focusing on neurodiverse communities, indigenous languages, and aging populations. Her work integrates tangible interfaces and AI to create innovative socio-technical systems. Education includes: PhD Mechanical Engineering Design (Stanford) Masters Technology Policy (MIT) BSc.Eng (Hons) (Bristol) Research explores co-design methods for overlooked communities through long-term engagements. Key areas: Humane AI, tangible interaction, and ecological systems. Recent publications show strong focus on healthcare AI (radiology training, clinical data augmentation), inclusive design (disability systems, dementia care), and environmental interaction (nature networks, phenology). Awards: QUT STEMM Diversity Award (2019) Vice-Chancellor's Research Excellence Award (2019) Supervised 20+ PhD students to completion and leads a vibrant research group. Secured major grants including ARC projects on Ambient Nature Networks and Human-Machine Teaming. Manages collaborative projects with clinical, indigenous, and environmental stakeholders.

Danaé MetaxaView profile

Assistant Professor

• Human-Computer Interaction
• Algorithmic Justice
• Bias in AI Systems
• +3 more

Danaé Metaxa is the Raj and Neera Singh Term Assistant Professor at the University of Pennsylvania with a primary appointment in the Department of Computer and Information Science and a secondary appointment in the Annenberg School for Communication. They co-founded and co-lead the Penn HCI group. Their education includes a Ph.D. in Computer Science from Stanford University and postdoctoral training at the Stanford Center of Philanthropy and Civil Society. Research focuses on bias and representation in algorithmic systems, sociotechnical auditing, and the impact of technology on marginalized groups in high-stakes domains like employment and politics. Recent work examines how algorithmic systems interact with human behavior in social contexts. Publications demonstrate interdisciplinary approaches combining HCI, NLP, and social science to address algorithmic fairness and accessibility. Recent articles explore targeted advertising impacts on queer communities, tools for scientific paper comprehension, and healthcare information accessibility. Awards include the endowed Raj and Neera Singh Term Assistant Professorship. Advises PhD students in human-computer interaction and leads research funded by NSF and other grants. Co-directs the Penn HCI lab investigating user-centered technology design. Currently serves as General Chair for FAccT 2025 and collaborates on interdisciplinary teams studying technology ethics and design justice.

Michael LewisView profile

Professor

• Human Factors
• Human-Computer Interaction
• Visualization
• +5 more

Michael Lewis is a Professor at the University of Pittsburgh's School of Computing and Information. He holds a PhD from Georgia Institute of Technology. His research focuses on Human Factors, Human-Computer Interaction, and Robotics, particularly in swarm systems and trust dynamics in human-autonomy teams. Education: PhD in Computer Science, Georgia Institute of Technology Research Interests: His work addresses challenges in supervisory control of robotic swarms, cultural impacts on trust in automation, and theory of mind modeling in human-agent teams. Recent studies include human-swarm interaction, adaptive teaming systems, and ethical considerations in AI. Publications: His work spans 52+ publications, emphasizing trust metrics, swarm degradation effects, and cross-cultural automation studies. Recent trends focus on explainable AI, human-swarm collaboration, and adaptive agent architectures. Awards: Best Paper Award at HCI International 2014 Best Paper Award at HFES’13 Grants & Labs: Leads projects on human-autonomy teaming and swarm robotics. Collaborates with institutions like the Robotics Institute and Human-Computer Interaction labs. Active in NSF-funded research on resilient swarm systems.

Ilhan AslanView profile

Associate Professor

• Human-Computer Interaction (HCI)
• Artificial Intelligence (AI)
• Machine Learning
• +6 more

Ilhan Aslan is an Associate Professor in the Department of Computer Science at Aalborg University (Denmark), affiliated with the Technical Faculty of IT and Design. His work focuses on Human-Centered Computing, with a strong emphasis on AI-driven interaction design, emotion-aware systems, and tangible/somaesthetic interfaces. He leads research in areas such as conversational AI, mobile computing, and smart environments, integrating machine learning with user-centered methodologies. Aslan's recent projects explore emotional speech processing, proactive AI agents, and creativity support tools, often bridging technical innovation with human well-being applications. His research spans over two decades, with notable contributions to mobile navigation systems (e.g., Bum Bag Navigator), gesture-based interaction, and ambient intelligence. Media coverage highlights his work on AI solutions for COPD patients and stress management applications. Aslan's approach combines rigorous technical development with ethnographic and participatory design practices, ensuring ethical and user-centric outcomes. His lab collaborates across disciplines, addressing challenges in HCI, AI ethics, and sustainable computing. Key Research Themes : Emotion-Aware AI, Human-AI Collaboration, Tangible Interaction, Mobile Health, Interactive Machine Learning Notable Projects : 'Feel my Speech' (haptic emotion conversion), 'BEHAVE AI' (ethical agent design), and somaesthetic smarthome systems Media Impact : Featured in 400,000+ Danes-relevant health tech stories and COPD patient support innovations Aslan's publications reflect a prolific trajectory from early mobile learning platforms (2000s) to cutting-edge generative AI and multimodal systems. His work consistently prioritizes real-world applicability through iterative prototyping and user studies, making him a key figure in both academic and applied HCI domains.

• Data Visualization
• Data Analysis
• Biotelemetry
• +3 more

Dr. Mark Holton is a Research Officer at Swansea University, affiliated with the School of Biosciences, Geography and Physics, and the Colleges of Engineering and Science. His work focuses on data logging systems, sensor circuit design, and biotelemetry technologies, particularly for animal monitoring and Human-Computer Interaction (HCI) devices. He has contributed to projects involving animal behavior analysis, environmental framing studies, and the development of algorithms for big data visualization and categorization. His research spans disciplines such as ecology, marine biology, and biomechanics, with applications in wildlife conservation, animal welfare, and technology integration. Key research areas include: animal movement tracking via accelerometers and magnetometry, biotelemetry for behavioral studies, and sensor-based solutions for non-invasive wildlife tagging. Holton has collaborated on projects analyzing the effects of tourism on whale sharks, reptile behavior, and the impact of environmental cues on animal navigation. His work often bridges engineering and ecology, emphasizing practical applications such as multisensor collar design and orientation sphere visualization tools. Notable publications highlight innovations in dead-reckoning algorithms, energy expenditure modeling in terrestrial animals, and the use of angular velocity metrics for metabolic analysis. While no formal awards are listed, his contributions to biotelemetry and animal behavior research have been widely cited in ecological and engineering journals. Holton’s research extends to HCI, including tactile feedback systems and sustainable technology prototyping with everyday materials.

Munmun De ChoudhuryView profile

Associate Professor

• Computational Social Science
• Mental Health
• Social Media Analysis
• +4 more

Munmun De Choudhury is an Associate Professor at the School of Interactive Computing, Georgia Institute of Technology, and Co-Lead of the Patient-Centered Care Delivery research pillar at the Children's Healthcare of Atlanta Pediatric Technology Center. She holds affiliations with the Institute for People and Technology (IPaT), Machine Learning Center (ML@GT), Institute for Data Engineering and Science (IDEaS), and Petit Institute for Bioengineering and Bioscience (IBB). Her research focuses on computational social science, leveraging social media data to study human well-being, mental health, and societal dynamics. A key area of her work involves developing computational tools for mental health intervention and public health policy. De Choudhury’s research integrates computer science with psychology, sociology, and medicine. She pioneered computational methods to analyze social media for mental health insights, leading to collaborations with the CDC, UN Foundation, and WHO. Her work has influenced policy, including contributions to the U.S. Surgeon General’s Advisory on Social Connection and the WHO’s Commission for Social Connection. Her awards include the 2023 SIGCHI Societal Impact Award, multiple best paper awards, and induction into the SIGCHI Academy. She directs the SocWeB Lab, which studies ethical uses of social media data for societal benefit. Over $42M in grants fund her research, supported by NIH, NSF, CDC, and industry partners like Microsoft and Instagram. De Choudhury teaches courses on social computing and ethics, emphasizing responsible AI and data practices. Her leadership roles include advisory boards for the American Foundation for Suicide Prevention and the International Society for Computational Social Science.

• Machine Learning
• Health Informatics
• Artificial Intelligence
• +3 more

José Luis Castillo Sequera is a Professor at the University of Alcalá, affiliated with the Department of Computer Sciences. His research focuses on machine learning applications in healthcare, environmental science, and telecommunications. He holds a PhD from the University of Alcalá (2010) with a thesis on evolutionary algorithms for document clustering in information systems. His research interests include health computing, intelligent systems, renewable energy forecasting, and data-driven solutions for societal challenges. Notable work includes developing predictive models for solar radiation, disease detection systems, and innovative health monitoring apps like 'Sedentary' for office workers. Recent publications emphasize machine learning applications in diverse domains: from optimizing agricultural yields and reducing water losses to predicting geological hazards using quantum computing. He explores blockchain for healthcare interoperability and VR-based language learning tools. His contributions span over 100 publications since 2010, addressing topics like smart lighting systems, IoT-based health monitoring, and educational technology. He leads the HCIS research group focusing on health computing and intelligent systems.

• Ray-Tracing Techniques
• Airport Security Systems
• Wireless Localization Algorithms
• +3 more

Antonio del Corte Valiente is an Associate Professor at the Department of Automática, University of Alcalá. His research focuses on enhancing airport safety and precision localization through ray-tracing techniques, wireless networks, and artificial neural networks. He earned his PhD in 2011 with a thesis on improving airport security via efficient localization algorithms using WLAN networks and ray-tracing methods, supervised by Dr. Óscar Gutiérrez Blanco and Dr. José Manuel Gómez Pulido. His work integrates interdisciplinary approaches, combining electrical engineering with aerospace and civil engineering challenges. Key contributions include developing hybrid localization systems (ray-tracing + fingerprinting) for indoor-outdoor environments, neural network models for energy-efficient lighting, and non-cooperative aircraft surveillance systems using short-range radar. He is affiliated with the HCIS group (Health Computing and Intelligent Systems), though his primary research remains in transportation and airport infrastructure. No scientific awards are listed, but his publications span over a decade of consistent output in localization, aviation safety, and smart systems. His advising record is not explicitly detailed here, but his doctoral work indicates mentorship potential in advanced localization and safety engineering. Ongoing research likely explores further integration of AI and sensor networks in critical infrastructure systems.