Find Academic Supervisors

• Human-Computer Interaction
• Social Robotics
• Artificial Intelligence Ethics
• +3 more

Kaisa Väänänen is a Professor at Tampere University, specializing in Human-Computer Interaction (HCI), Social Robotics, and Artificial Intelligence Ethics. Her research focuses on societal participation, user experience (UX) in technology design, and ethical integration of AI systems. She has contributed extensively to understanding how social robots can foster civic engagement and how AI can collaborate effectively with humans in knowledge work and smart environments. Her work bridges theoretical frameworks with practical applications, including studies on robot-mediated youth engagement, sustainable HCI practices, and the design of ethical AI systems. She has led projects exploring AI collaboration in manufacturing, healthcare, and education, emphasizing human-centric approaches. Väänänen has also edited major conference proceedings, such as the 30th International Conference on Intelligent User Interfaces (IUI 2025), showcasing her leadership in academic discourse. Key research interests include: Social robotics for youth empowerment AI ethics and human-AI collaboration UX design for smart cities Tangible interfaces for explainable AI Her recent articles highlight trends in AI-driven societal participation, sustainability in technology design, and the role of large language models in transforming research and collaboration methods. She advocates for frameworks that ensure technology aligns with human values and societal needs.

Günter WallnerView profile

Assistant Professor

• Games User Research
• Data Analytics
• Information Visualization
• +3 more

Günter Wallner is an Assistant Professor (Part-time) in the Systemic Change Cluster within the Department of Industrial Design at Eindhoven University of Technology (TU/e). He simultaneously holds positions as Professor for Game Computing at Johannes Kepler University Linz, Adjunct Professor at Ontario Tech University, and Senior Scientist at the University of Applied Arts Vienna, Institute of Art & Technology. His work bridges multiple institutions and focuses on the intersection of games, data analytics, and visualization. Wallner's academic credentials include: Diploma in Computer Science from University of Technology, graduated with distinction in 2005 Doctoral degree in Natural Sciences from University of Applied Arts Vienna, graduated with distinction in 2009 His research program centers on understanding player behavior in games and developing methods to explore and communicate collected data for actionable game design insights. Wallner's expertise spans three interconnected domains: games user research examining player engagement, data analytics specifically for game-related behavioral datasets, and information visualization techniques for representing complex game data. A significant portion of his work focuses on creating data visualizations to support analysis of increasingly large-scale player behavioral datasets used in game analytics. Wallner's recent publications reveal several key research trends. His work shows a strong focus on visual analytics for games with multiple papers exploring effective representation of player behavior through visualization techniques. There's growing interdisciplinary reach into healthcare applications, as seen in his 2024 paper on MR imaging preparation. Many publications address practical applications in competitive gaming environments like League of Legends and Hollow Knight. The interdisciplinary nature of his work is evident in publication venues spanning top-tier HCI conferences (CHI, CHI PLAY), visualization conferences (EuroVis), and specialized game research venues (FDG). Wallner has received various awards and recognitions for his work on games, though specific awards are not detailed in available information. As an active researcher, Wallner provides substantial service to the academic community. He frequently serves on program committees for games, visualization, and human-computer interaction conferences. He has held significant organizational roles including Program Chair for CHI PLAY 2019 and currently serves as Steering Committee Vice-Chair for CHI PLAY since 2023. His editorial work includes serving on boards of ACM Games: Research and Practice and Behaviour & Information Technology. He has been instrumental in organizing workshops such as the PLEY series on Eye Tracking in Games and Play. At TU/e, Wallner is affiliated with multiple research groups: EAISI Foundational, Industrial Design Research, and specifically the Design Of Empowering Systems subgroup. His work demonstrates extensive interdisciplinary collaboration across game studies, human-computer interaction, and data visualization researchers, particularly within the EAISI (Eindhoven Artificial Intelligence Systems Institute) ecosystem.

Kai PolstererView profile

Research Professor

• Astroinformatics
• Machine Learning
• Data Science
• +4 more

Dr. Kai Polsterer is the Scientific Director of the Heidelberg Institute for Theoretical Studies (HITS) since January 2025, succeeding Tilmann Gneiting. He has been a leading researcher at HITS since 2013, heading Europe's first astroinformatics research group. His work focuses on developing machine learning methods to handle exponential data growth in astrophysics, including projects like the ERC Synergy Grant for universe mapping and exascale computing initiatives (SPACE). He collaborates across disciplines with statisticians and physicians to advance weather forecasting and cardiological analysis. Polsterer is actively involved in international organizations such as the International Astroinformatics Association (IAIA, President since 2023), IEEE Task Force on Mining Complex Astronomical Data, and the German Physical Society's AI working group. His research spans astroinformatics, data science, and interdisciplinary applications of AI. His expertise includes photometric redshift estimation, galaxy classification, and unsupervised learning techniques. Polsterer has pioneered tools like PINK (Parallelized Kohonen Maps) and contributed to projects like the LUCIFER instrument for near-infrared spectroscopy. He emphasizes open science and collaborative frameworks, such as the HiPS ecosystem for astronomical data visualization. His current role as Scientific Director reflects his leadership in advancing theoretical studies through computational and data-driven approaches. Polsterer’s contributions include over 50 peer-reviewed articles, spanning astroinformatics, machine learning applications in astronomy, and computational methodologies. He advocates for interdisciplinary research, bridging astrophysics, computer science, and medical data analysis. His ERC Synergy Grant project exemplifies his commitment to large-scale, collaborative science addressing fundamental questions in cosmology and data science.

Tom BrinckView profile

Academic

• Human-Computer Interaction
• User Experience (UX) Design
• Accessibility
• +4 more

Tom Brinck is an **Adjunct Lecturer** at the **INFO College, University of Maryland**, specializing in Human-Computer Interaction and User Experience (UX) Design. He holds a dual role as a Board Member at the Palo Alto Art Center Foundation. His career spans over two decades of leadership in design and innovation, with roles at Amazon (A9.com), Samsung, Cisco (via Broadsoft acquisition), and Bellcore, alongside founding RetroAccess, a startup focused on accessibility. **Education & Background**: Tom’s academic journey includes advanced studies in collaborative systems and UX design, reflected in his graduate work on collaborative whiteboards and subsequent industry contributions. He has taught graduate UX courses at the University of Michigan and Academy of Art University, co-authoring the influential book *Usability for the Web*. **Research Focus**: His work emphasizes accessibility, usability evaluation, and collaborative technologies. Early contributions include foundational research in groupware and videoconferencing systems, while recent efforts focus on UX in telecommunication platforms and AI-driven learning systems. **Industry Impact**: Tom’s career highlights include pioneering accessibility standards at RetroAccess, leading UX teams at Samsung and Cisco, and innovating search and advertising UX at Amazon. His work bridges academia and industry, emphasizing practical solutions for inclusive design and measurable ROI in usability investments. **Labs & Teams**: He directed UX Innovations labs at Samsung and led Calling UX teams at Cisco, demonstrating expertise in scaling UX practices across large organizations. His board role at the Palo Alto Art Center Foundation reflects his commitment to interdisciplinary creativity.

• Virtual Reality
• Human-Computer Interaction
• Robotics
• +3 more

Frédéric Davesne is a Researcher at the IBISC Laboratory affiliated with the University of Évry Val d'Essonne , part of the Université Paris-Saclay. His work focuses on virtual reality (VR), augmented reality (AR), human-computer interaction, and robotics. He actively contributes to the EVR@ Platform , a technological hub for immersive environments, and collaborates on projects like the AlzVR cognitive screening tool . Research Interests: His research spans gesture recognition via LSTM networks, cognitive assessment in virtual environments, collaborative 3D interaction models, and robotics applications. Recent efforts include developing user-centric interfaces for healthcare and retail domains, leveraging machine learning and spatial analysis techniques. Contributions: Davesne organizes lab events (e.g., IBISC Lab Days), participates in Telethon fundraising, and advises doctoral defenses (e.g., Duc To NGUYEN, Ding CHEN). He has published widely in journals like IEEE Transactions on Fuzzy Systems and Computers & Geosciences , with a focus on advancing VR/AR applications and interaction techniques. Platforms: He leads the EVR@ Platform, which integrates AR/VR technologies for collaborative teleoperation and 3D interaction studies. This infrastructure supports interdisciplinary projects in robotics, healthcare, and human behavior analysis.

• Deep Learning
• Image and Video Analysis
• Visual Similarity Search
• +3 more

Nikolaus Korfhage is a Research Fellow at Philipps-Universität Marburg, affiliated with the Department of Mathematics and Computer Science within the Faculty of Mathematics and Computer Science. He is part of Prof. Bernd Freisleben's research group focusing on Distributed Systems and Intelligent Computing. His research emphasizes deep learning applications in image and video analysis, particularly visual similarity search and biomedical data analysis. Korfhage initiated his PhD in 2016 under Prof. Freisleben’s supervision, exploring computational methods for multimedia data processing. His work spans diverse domains including avian physiology analysis, automated music notation transcription, and historical video archive retrieval. Notable projects include the VIVA initiative for content-based video search and the DeepTab system for transcribing organ tablature music. Recent publications highlight advancements in cell segmentation, bat echolocation analysis, and transformer-based species recognition. Korfhage’s contributions bridge computer science and interdisciplinary fields like biology and musicology. He collaborates actively on tools like ElasticHash for semantic image search and MESA for synthetic DNA assessment. His research underscores innovation in both technical methodologies and real-world applications across multimedia, biomedical, and ecological domains.

Heike HofmannView profile

Professor

• Statistical Visualization
• Forensic Data Analysis
• Machine Learning for Forensics
• +4 more

Heike Hofmann is a Professor in the Department of Statistics at the University of Nebraska-Lincoln. Her research spans statistical visualization, forensic data analysis, and machine learning applications in crime scene evidence evaluation. Key contributions include developing interactive frameworks for forensic bullet comparisons, advancing reproducibility in toolmark analysis, and creating explainable machine learning pipelines. Email: hhofmann4@unl.edu Research Interests focus on: Visual statistical inference and human factors in data interpretation 3D imaging and algorithmic matching for firearms/toolmark identification Psychometrics and mixed-effects modeling Open-source software development for statistical analysis (e.g., R packages) Recent Work Trends (2021-2025) emphasize: Forensic error rate quantification Interactive visualization tools (e.g., ggplot2 extensions) Machine learning integration in forensic science Large-scale data graphics validation for public understanding Automated matching algorithms for bullets/cartridge cases

Abello Monedero, JamesView profile

Professor

• Graph Mining
• Relational Learning
• Visualization of Massive Data Sets
• +10 more

James Abello Monedero is a Professor in the Computer Science Department at Rutgers University , specializing in algorithms, graph mining, and visualization of massive datasets. He earned a Ph.D. in Computer Science from the University of California, San Diego, and held postdoctoral and academic positions at UC Santa Barbara, Texas A&M University, and Bell Labs. Ph.D. in Computer Science, UC San Diego M.S. in Computer Science, UC Santa Barbara His research interests span external memory algorithms , graph mining , relational learning , and visual analytics for massive datasets. He has pioneered techniques for dynamic weighted multi-digraph analysis, large-scale network visualization, and interdisciplinary applications in epidemiology and cultural analytics. James’s publications focus on scalable graph algorithms, visual metaphors for data exploration, and network decomposition. His work includes foundational contributions to graph sketches , quasi-clique detection , and 3D graph navigation , with applications to telecommunications, web graphs, and homeland security. Scientific awards include the ESA Test of Time Award (2017) , Best Teaching Award at Rutgers (2015) , and Fellow of the Institute of Combinatorics (1993) . He has advised numerous Ph.D. and M.S. students, and his research has been funded by NSF , DHS , and LLNL . James leads the Universal Information Graphs Project at DyDAn (DHS Center) and has developed software systems like MGV and Ask-GraphView for interactive graph analysis. He is an active organizer of conferences and workshops in data mining and visualization.

• Computer Vision
• Deep Learning
• Object Detection
• +4 more

Zheng Ge is an active researcher specializing in computer vision and deep learning, with a prolific publication record spanning from 2018 to 2025. They have authored or co-authored 81 publications in top-tier venues including CVPR, ICLR, ECCV, and NeurIPS, demonstrating consistent research productivity and impact in the field of artificial intelligence. Dr. Ge's primary research interests focus on computer vision with particular emphasis on object detection, 3D perception, and multimodal learning systems. Their work bridges theoretical advancements with practical applications, especially in video understanding, image generation, and large vision-language models. Recent research directions show a strong focus on developing more efficient and capable multimodal systems that can handle complex visual tasks with human-like understanding. The analysis of their recent publications reveals a clear trend toward building more sophisticated multimodal systems that integrate vision, language, and temporal understanding. Their work on video generation, perception modeling, and instruction tuning demonstrates a strategic focus on advancing the capabilities of multimodal large language models while addressing practical challenges in scalability and robustness. While specific awards are not documented in the available publication records, Zheng Ge's consistent presence in top-tier computer vision and machine learning conferences indicates significant recognition within the research community. Their work has contributed to advancing state-of-the-art techniques in multiple subfields of computer vision. Dr. Ge appears to be actively collaborating with a large research team, frequently working with researchers such as Xiangyu Zhang, Jianjian Sun, Chunrui Han, and Liang Zhao. These collaborations span multiple institutions and research groups, suggesting a well-integrated position within the computer vision research ecosystem. While specific grant information isn't available in the publication metadata, the scale and scope of their projects indicate substantial research funding support. Based on publication patterns and technical focus, Zheng Ge appears to be part of a large research organization or lab specializing in computer vision and multimodal AI systems. Their work on technical reports for video foundation models and large-scale multimodal systems suggests involvement in industry-leading AI research initiatives with strong engineering capabilities.

Ioannis BrilakisView profile

Professor

• Construction Engineering
• Construction Automation
• Digital Twins
• +5 more

Ioannis Brilakis is the Laing O’Rourke Professor of Construction Engineering and Director of the Construction Information Technology Laboratory at the University of Cambridge’s Department of Engineering. He holds a PhD from the University of Illinois, Urbana-Champaign and has held academic roles at the University of Michigan, Georgia Tech, and visiting appointments at Stanford and Technical University of Munich (TUM) as a Visiting Professor and Hans Fischer Senior Fellow (2019–2021). His work focuses on construction automation, digital twins, and infrastructure sensing technologies. Research interests include generating/updating digital twins for infrastructure, computer vision for construction site analysis, automated design/construction tasks, and project management technologies. Awards include the NSF CAREER Award, ASCE J. James R. Croes Medal, and ASCE John O. Bickel Award. Collaborations include projects funded by EPSRC, H2020, InnovateUK, and industry partners like BP and Trimble. His lab develops AI-driven solutions for infrastructure monitoring and BIM integration. Recent work emphasizes climate resilience of critical infrastructure and graph-based construction scheduling analysis.

Freida AbtanView profile

Associate Professor

• Electronic Music Composition
• Immersive Media
• Multimedia Performance
• +3 more

Abtan’s research focuses on the intersection of technology design and artistic practice, emphasizing real-time systems and inclusive audiovisual mappings. She teaches Electronic Music Composition and contributes to programs in Music & Technology at CMU. Her creative output includes solo projects and collaborative works that challenge traditional boundaries between media and performance. Her articles and installations reflect interests in inter-sensory gestures, instrument design, and gender dynamics in electronic music culture. Abtan’s work bridges experimental music traditions with cutting-edge digital innovation, fostering interdisciplinary approaches to artistic creation.

• Human-Computer Interaction (HCI)
• User-Centered Design
• Healthcare Technology
• +3 more

Yngve Dahl is an Associate Professor at the Department of Computer Engineering and Information Technology at NTNU. His research focuses on Human-Machine Interaction (HMI), with a strong emphasis on user-centered design, participatory design, and healthcare technology. He holds a PhD in computer science from NTNU and is affiliated with the Information Systems and System Development research group. His academic journey includes extensive contributions to healthcare IT, welfare technology, and assistive systems. Notable research areas include the design of interactive technologies for elderly care, telehealth systems, and exergames to promote physical activity. He has supervised numerous master’s and PhD students, fostering innovation in fields like participatory design methodologies and usability assessments in clinical settings. Publications highlight Dahl’s interdisciplinary work, including studies on scaling participatory design, facilitation practices in large IT projects, and the integration of technology in audiological consultations. His research often bridges theoretical frameworks with practical implementations, addressing challenges such as ethical considerations in healthcare technology and user involvement in asymmetric stakeholder environments. Key projects include developing GPS solutions for dementia care, sensor-enhanced emergency response systems, and tangible interfaces for physiotherapy. Dahl’s work frequently emphasizes stakeholder perspectives, ensuring technologies align with user needs and societal values.

• Mathematical modeling and simulation in biology
• Scientific computing and numerical methods
• Computational fluid dynamics
• +4 more

Ying Chen is a Visiting Assistant Professor of Mathematics at Purdue University's Department of Mathematics, affiliated with the College of Science. Her research focuses on mathematical modeling in biology, scientific computing, and computational fluid dynamics. She has contributed to interdisciplinary projects involving autonomous systems, human-computer interaction, and medical visualization. Her work bridges theoretical mathematics with practical applications in healthcare systems, environmental monitoring, and autonomous vehicle technologies. Key research interests include developing algorithms for 3D scene reconstruction, optimizing vehicle interface safety, and applying AI to clinical decision support. Her recent publications explore topics like neural motion flow for autonomous driving, haptic feedback in bicycle safety systems, and LiDAR-camera fusion techniques. Collaborations span computer science, engineering, and biomedical fields. Publications from 2023–2025 reveal a focus on spatiotemporal data visualization, VR training systems, and multi-modal forest monitoring. Notable trends include integrating machine learning with real-world challenges in transportation safety and environmental analysis. While no awards are explicitly listed, her work has been recognized in VAST Challenge competitions for innovative visualization methodologies. Ying Chen’s teaching and research emphasize bridging abstract mathematical concepts with tangible applications. She has developed educational tools like the Mindwriter academic writing environment and conducted studies on visual learning strategies for students with math difficulties. Her work on car dashboard interface design and in-car entertainment systems highlights a commitment to user-centered technology solutions.

Markus SchützView profile

Researcher

• Computer Graphics
• Point Cloud Rendering
• Real-Time Visualization
• +3 more

Markus Schütz is a Researcher at the Department of Computer Graphics, Faculty of Informatics, TU Wien. He holds a Dipl.-Ing. Dr.techn. and BSc. His work focuses on real-time rendering of massive point clouds, GPU acceleration, and interactive visualization. Key projects include 'Bringing Point Clouds to WebGPU' and 'Instant Visualization and Interaction for Large Point Clouds'. He has developed the Potree library for web-based point cloud visualization. Education: Bachelor of Science (BSc) Diplom-Ingenieur (Dipl.-Ing.) Doctor of Technical Sciences (Dr.techn.) from TU Wien Research Interests: His research emphasizes real-time rendering techniques for large-scale point clouds, GPU optimization, and efficient data processing. He explores areas such as level-of-detail generation, compute shader utilization, and web-based visualization tools like Potree. Recent work includes software rasterization of 2 billion points and simultaneous LOD generation for point clouds. Awards: Best Paper Award at EGPGV2024 High-Performance Graphics 2022 Best Paper Award Second Place in SIGGRAPH Poster Student Research Competition (2018) AGEO AWARD 2017 Projects & Grants: Bringing Point Clouds to WebGPU (2024–2025, netidee Foundation) Instant Visualization and Interaction for Large Point Clouds (2023–2026, WWTF) IVILPC (Interactive Visualization of Large Point Clouds) project Labs & Teams: Active in TU Wien's Computer Graphics Group, collaborating on GPU-accelerated rendering and real-time visualization systems.

• Virtual Reality
• Augmented Reality
• Haptic Feedback Systems
• +5 more

Emanuel Vonach is a PreDoc Researcher at the Institute of Visual Computing & Human-Centered Technology at Vienna University of Technology (TU Wien), specializing in virtual reality, haptics, and tangible user interfaces. His work focuses on developing innovative VR systems with robotic haptic feedback, health monitoring technologies for children, and motion capture applications. He maintains an active research profile with publications spanning from 2011 to 2025, demonstrating continuous contribution to the field of human-computer interaction. Vonach's research interests primarily center around enhancing virtual reality experiences through physical interaction. His work explores how robots can provide haptic feedback in VR environments, developing systems like CoboDeck (a large-scale haptic VR system using collaborative mobile robots) and Action-Origami inspired haptic devices. He has also pioneered applications in health monitoring for children through projects like MediCubes, which transforms medical examinations into engaging storytelling experiences using tangible interfaces. His research bridges the gap between theoretical computer science and practical applications in healthcare, education, and emergency response. His publication record shows a clear progression from foundational work in motion capture and tracking systems to increasingly sophisticated haptic VR applications. Recent publications focus on environment-independent locomotion prediction for haptic VR and safety monitoring systems for encountered-type haptics, indicating a maturation of his research toward more complex, real-world applications. The consistent funding from organizations like the Austrian Research Promotion Agency (FFG) and European Commission demonstrates recognition of his work's significance. Vonach actively supervises graduate students, with thesis topics covering mobile collaborating robots for haptics, in-situ questionnaires for haptic experience, and visual assessment with eye-tracking displays. His role as a PreDoc Researcher with FWF funding suggests he is either completing or has recently completed his doctoral studies while maintaining an active research program. His collaborations with Professor Hannes Kaufmann and other researchers at TU Wien form a cohesive research group focused on advancing VR and haptic technologies.