Paul Rosen is an Associate Professor at the University of Utah, affiliated with the Scientific Computing and Imaging Institute and the Kahlert School of Computing. He holds a Ph.D. in Computer Science from Purdue University (2010). Prior to his current role, he was an Assistant/Associate Professor at the University of South Florida (2015–2022) and a Research Assistant Professor at the University of Utah's SCI Institute (2010–2015). Research Focus: Rosen specializes in topology-based visualization techniques, with emphasis on network visualization, uncertainty quantification, and perceptual studies. His work bridges computational methods with human perception, aiming to enhance data understanding through effective visual design. Awards & Recognition: National Science Foundation CAREER Award (2019) Best Paper Awards at PacificVis 2016, IVAPP 2016, and multiple other conferences Honorable Mentions for IEEE VIS and VAST Challenge submissions Leadership: As General Chair of IEEE VIS 2024, Rosen led the planning for this flagship visualization conference, emphasizing community-driven design and in-person collaboration. Education Contributions: His research includes pedagogical innovations, such as predictive modeling for student feedback and peer review analysis in visual literacy courses.
Gita Reese Sukthankar is a Professor in the Department of Computer Science at the University of Central Florida (UCF) , where she directs the Intelligent Agents Lab . Her research focuses on activity and plan recognition , with applications in multi-agent systems, robotics, and human-robot interaction. She earned her Ph.D. from the Robotics Institute at Carnegie Mellon University and joined UCF in fall 2007. Research Interests: Her work spans activity recognition , intent inference , multi-agent coordination , and human-robot teams . She has applied these techniques to domains such as adversarial games (e.g., military simulations, Unreal Tournament), assistive technologies, and cooperative robotics. Her research integrates AI, machine learning, and probabilistic models to understand and predict complex team behaviors. Publication Trends: Her publications emphasize spatio-temporal modeling , probabilistic graphical models (e.g., HMMs, CRFs) , and multi-agent plan recognition . She frequently publishes in top venues like AAMAS, AAAI, and ICRA, with a focus on robust recognition of team behaviors, transfer learning, and real-world AI applications. Scientific Awards: NSF CAREER Award (2009) AFOSR Young Investigator (2009) ONR Summer Faculty Fellow (2008) UCF Faculty Excellence for Doctoral Mentoring (2012) CECS Dean's Research Professorship (2013) AAAI Senior Member (2021) ACM and IEEE Senior Member Advising and Grants: She mentors graduate students in AI and robotics and has led research funded by DARPA, AFOSR, and ONR. Her lab develops systems for intelligent agents that can understand and collaborate with humans. She has served on numerous program committees and editorial boards, including ACM Transactions on Autonomous and Adaptive Systems . She teaches courses such as Intelligent Systems , Robotics , and Machine Learning , and has been recognized for both research and teaching excellence. Labs and Teams: She leads the Intelligent Agents Lab at UCF, which focuses on data-driven social informatics and AI for human-agent teams. Her group collaborates with researchers in robotics, computer vision, and cognitive science to build adaptive, intelligent systems.
Dr. Zhao Na is a tenure-track Assistant Professor at the Singapore University of Technology and Design (SUTD), affiliated with the Institute of Sustainable Technology and Design (ISTD). She holds a Ph.D. in Computer Science from the National University of Singapore (NUS), where her thesis on 3D point cloud semantics earned the IMDA Excellence Prize. Her research bridges computer vision and machine learning, focusing on scene understanding, data-efficient learning, and domain generalization. Education: Ph.D. in Computer Science (NUS, 2021); Prior roles include Research Fellow at NUS. Research interests emphasize 3D scene analysis, object detection, semantic segmentation, and robust learning under noisy or limited data. Her work addresses challenges in multi-modal learning, continual learning, and open-world scenarios. Recent projects include geometry-semantics synergy in neural fields and cross-modal augmentation for visual grounding. Publications span top-tier venues like CVPR, ECCV, and ICCV, with a focus on 3D vision and AI. Key contributions include the PCTeacher framework for semi-supervised segmentation and Static-Dynamic Co-Teaching for incremental learning. Scientific Awards: IMDA Excellence Prize (2021). Active grants include a DSO Research Grant (2023–2026) and A*STAR MTC Grant (2023–2026). She leads the SUTD-ZJU Thematic Grant on 3D scene understanding (2022–2024). Laboratory/Team: Research group at ISTD/SUTD focuses on advancing AI-driven 3D perception and scene understanding systems.
Marie-Paule Cani is a Professor of Computer Science at École Polytechnique (since May 2017), on leave from Grenoble INP and Inria . She leads the STREAM team at the LIX laboratory (CNRS, École Polytechnique) and collaborates externally with the IMAGINE team at Inria. Her research focuses on advancing intuitive methods for creating 3D shapes and virtual worlds, emphasizing user control and model-based knowledge. Education: 1987: M.Sc. in Computer Science, École Normale Supérieure & University Paris XI 1990: Ph.D. in Computer Graphics, University Paris XI (advisor: Claude Puech) 1995: Habilitation in Computer Science, Institut National Polytechnique de Grenoble Research Interests: Her work spans shape modeling , computer animation , and procedural modeling . She pioneered methods such as implicit surfaces, physically-based animation, and sketch-based interfaces. Recent projects include combining procedural models with intuitive user interactions to streamline 3D content creation. Awards & Recognition: ERC Advanced Grant (2011) for the EXPRESSIVE project 2011 Eurographics Technical Contributions Award 2012 CNRS Silver Medal 2013 Election to Academia Europaea Leadership & Service: She created and led the STREAM (2017–present), IMAGINE (2011–2016), and ÉV@NCE (2003–2010) research teams. She has served as President of Eurographics (2017–present), Technical Paper Chair of SIGGRAPH 2017 , and on editorial boards of ACM Transactions on Graphics , Computer Graphics Forum , and others. Labs & Teams: Active in the LIX laboratory and collaborates with Inria's IMAGINE team. Her work bridges academic research and industrial applications in computer graphics and animation.
Mehmet Uğur KAHRAMAN is an Assistant Professor at the Department of Interior Architecture and Environmental Design at Antalya Bilim University, where he has served since 2017. Previously, he held a faculty position at Kayseri Nuh Naci Yazgan University (2015–2017). His academic journey includes a Doctorate from Hacettepe University (Interior Architecture and Environmental Design), a Master of Design (Interior Design) from Swinburne University of Technology (Australia), and a Bachelor’s degree from Hacettepe University’s Department of Interior Architecture and Environmental Design. Before academia, he worked as a construction site manager at KG Architecture in Istanbul, co-founded the food and beverage brand 'Shot&Bite' in Ankara, and later served as a designer at QUBİ Design Office. His research focuses on integrating artificial intelligence into design education, neurocognitive aspects of spatial design, sustainable materials, and pedagogical innovations in interior architecture education. He has authored over 20 peer-reviewed articles on topics ranging from AI-driven furniture design to multisensory hospitality spaces. His work bridges theoretical research with practical applications, such as developing curriculum models for design studios and exploring waste-to-art construction techniques. KAHRAMAN’s studies also address health impacts of building materials and the psychological dimensions of housing during crises like the COVID-19 pandemic. He maintains active research collaborations, particularly in Turkey and Australia, and has contributed to public infrastructure projects involving material conservation and adaptive reuse. His educational philosophy emphasizes student-centered learning, interdisciplinary approaches, and leveraging digital tools for contemporary design challenges.
Ewa Szczurek is a Professor at the University of Warsaw's Faculty of Mathematics, Informatics and Mechanics and Co-director of the Institute for AI for Health, leading joint labs at Helmholtz Munich and the University of Warsaw. Education: Master degree in Computer Science from Uppsala University, Sweden (2005) Master degree in Computer Science from University of Warsaw, Poland (2006) Doctoral degree from Max Planck Institute for Molecular Genetics, Berlin (2011) Postdoctoral fellowship at ETH Zurich, Switzerland (2011) Habilitation at University of Warsaw, Poland (2020) Visiting associate professor at Northwestern University, USA (2023) Research Focus: Her work centers on probabilistic graphical models and deep generative models applied to computational medicine, with emphasis on oncology (tumor microenvironment modeling and evolution), pulmonology, and AI-driven antimicrobial peptide design to combat antibiotic resistance. She develops specialized deep learning frameworks for spatial transcriptomics analysis, tumor evolution reconstruction, and synthetic antimicrobial compound generation. Publication Trends: Recent publications (2022-2023) demonstrate consistent innovation in AI-driven biomedical solutions, bridging machine learning with oncology and infectious disease research. Her work shows increasing focus on generative models for drug design and spatial data analysis, with strong industry-academia collaborations (e.g., Merck, IMMUcan consortium). Awards: ERC Consolidator Grant (2023) for DOG-AMP project Scientific and didactic award from Rector of University of Warsaw ETH Zurich and IMPRS fellowship awards Grants & Leadership: Leads the ERC Consolidator Grant project DOG-AMP for antimicrobial peptide design. Serves as Associate Editor for Genome Biology and participates in program committees for ISMB and RECOMB-CCB conferences. Collaborates with international consortia including IMMUcan and Merck's Oncology Bioinformatics department. Labs & Networks: Co-directs AI for Health Institute with joint labs at Helmholtz Munich and University of Warsaw. Active in ELLIS (pan-European AI network) and Polish Bioinformatics Society, driving interdisciplinary research at the AI-medicine interface.
Niels da Vitoria Lobo is an Associate Professor in the Department of Computer Science at the University of Central Florida. His research spans computational vision, mobile robotics, and user interface design, with a focus on real-world applications including object detection, person tracking, and obstacle avoidance systems. Education: Ph.D. in Computer Science – University of Toronto Research Interests: Dr. Lobo’s work in computational vision addresses challenges like integral image-based curve detection and object detection in cluttered environments. He has developed systems for hand and person tracking, automobile lane following, and optical flow integration, alongside exploring graphical modeling for wristband trackers and educational games. Scientific Contributions: UCF Millionaire’s Club (2008) – recognizing significant research contributions Teaching Incentive Program Award (1996) – honoring excellence in academic instruction As an Associate Editor for computer vision journals, he has played a key role in advancing scholarly discourse in artificial intelligence and robotics.
Sidonie Christophe is a Senior Researcher (Directrice de Recherche, DR1) at UMR LASTIG, a joint research unit of Université Gustave Eiffel, IGN-ENSG, and EIVP. She serves as co-director of the LASTIG laboratory and leads research in geovisualization, map design, and interactive spatial data exploration. She also holds a part-time advisory role (60%) at the French Ministry of Higher Education and Research in the domain of digital technology, environment, climate, and sustainable urban development. PhD in Geographic Information Sciences Senior Researcher, DR1, MTECT Co-Director, LASTIG Laboratory (since 2021) Former Team Leader, GEOVIS (Geovisualization, Interaction, and Immersion) Advisor, Environment and Urban Climate, French Ministry of Higher Education & Research Her research centers on innovative methods for 2D/3D and nD geospatial data visualization, with a focus on enabling spatio-temporal understanding through visual and non-visual spatial thinking. Her work integrates principles from geographic information science, human-computer interaction, and computer graphics. Key areas include urban climate visualization, tactile and augmented reality for accessibility, expressive cartographic rendering, and cognitive aspects of map design. She investigates how aesthetic and semiotic choices impact map comprehension and utility. The 15 most recent publications reflect a strong trend in interactive and accessible geovisualization, particularly for urban and environmental applications. Topics include neural map style transfer, 3D urban climate analysis, tactile maps for the visually impaired, augmented reality in geography, and visual analytics for crisis and climate data. There is a consistent emphasis on user-centered design, interdisciplinary integration, and the development of tools for decision-making under uncertainty. Scientific Recognition and Service: Invited speaker at major conferences (IEEEVIS, AGILE, ICC, CPGIS) Co-organizer of international workshops (e.g., GeoVIS, ISPRS AR/VR sessions) Leader of national research projects (ANR ORACLES, ANR ACTIVmap, ANR ECOCIM) Recipient of international mobility grants (AMICI I-SITE FUTURE) Contributor to national glossaries and research strategy (e.g., French photogrammetry glossary) Advising and Grants: Sidonie Christophe actively supervises PhD students and postdoctoral researchers, including Markie Jiang, Maria-Jesus Lobo, and Alexandre Mielniczek. She leads or participates in multiple funded research projects such as ANR ORACLES (marine flooding visualization), ANR ACTIVmap (tactile 3D maps), and ANR ECOCIM (eco-design of city information models). Her advisory role at the MESR involves shaping national research strategy in digital and environmental sciences. Labs and Research Teams: She is a core member of the GEOVIS team (Geovisualization, Interaction, and Immersion) at LASTIG and previously served as its leader. As co-director of LASTIG, she plays a central role in the leadership and strategic direction of the entire laboratory, which comprises over 100 researchers across four teams: ACTE, GEOVIS, MEIG, and STRUDEL.
Minchen Li Assistant Professor at Carnegie Mellon University's School of Computer Science (Computer Science Department). Formerly an Assistant Adjunct Professor at UCLA's Mathematics Department. Holds a Ph.D. from the University of Pennsylvania's SIG Center for Computer Graphics, followed by a postdoctoral position there. Research focuses on physics-based simulation, integrating numerical analysis, high-performance computing, and machine learning. Notable contributions include the IPC method for frictional contact simulation and large-scale material point methods. Education Ph.D., Computer and Information Science, University of Pennsylvania (2020) M.Sc., Computer Science, University of British Columbia (2018) B.Eng., Computer Science and Technology, Zhejiang University (2015) Research Interests Advances in physical simulation for visual computing, robotics, and manufacturing. Specializes in robust and efficient methods for solid/fluid dynamics, contact modeling, and GPU acceleration. Combines numerical analysis with machine learning to address challenges in simulation accuracy and versatility. Awards 2021 ACM SIGGRAPH Outstanding Doctoral Dissertation Award 2024 SCA Early Career Researcher Award Advising & Labs Leads the Simulation Intelligence Group (SIG) at CMU Graphics Lab. Advises PhD students Guying Lin, Juntian Zheng, Michael Liu, and Zhaofeng Luo. Collaborates with industry and academic partners on projects like VR-based modeling systems and scalable simulation frameworks.
Hariharan Subramonyam is an Assistant Professor (Research) at Stanford University's Graduate School of Education and Computer Science (by courtesy) . He serves as the Ram and Vijay Shriram Faculty Fellow at the Institute for Human-Centered AI (HAI) and is a core faculty member of Stanford HCI . His research bridges Human-Computer Interaction (HCI) and the Learning Sciences , focusing on augmenting human learning through AI via cognitively informed design practices, co-design with learners/educators, and transformative AI-enabled learning experiences. His work emphasizes ethical AI, responsible design, and human values in technology. He earned a PhD in Information from the University of Michigan under Eytan Adar. Current projects include Script&Shift (layered interfaces for LLM writing), AltCanvas (accessible image editing for BVI users), and CogGen (AI tutoring systems). His teaching includes EDUC 432: Designing Explorable Explanations and CS 448B: Data Visualization . Key Research Areas Cognitively Informed AI Systems Human-AI Collaborative Writing Accessible Generative AI Tools Ethical AI Frameworks Interactive Learning Environments Awards & Grants Best Paper Award (CHI 2025) Honorable Mention Award (CHI 2025) HAI Hoffman Yee Grant (2024) Cover Story in Interactions Magazine (2024) Collaborative Networks Co-organizing CHI 2025 Tools for Thought Workshop Contributor to UIST 2024 Dynamic Abstractions Workshop Advising PhD students across Stanford, Georgia Tech, and Duke Collaborations with institutions including University of Michigan, National University of Singapore, and Technical University Munich
Professor Melanie Volkamer is a leading computer scientist at the Karlsruhe Institute of Technology (KIT), where she heads the SECUSO (Security, Usability, Society) research group within the Institute for Applied Informatics and Formal Description Methods at the Faculty of Business and Economics. She moved her research group from TU Darmstadt to KIT at the beginning of 2018 and has established herself as one of Germany's foremost experts on the human factor in security and privacy. Professor Volkamer's research focuses on human-centered security design, emphasizing that technical security solutions must be developed with user behavior and mental models in mind. She investigates why users often choose less secure passwords, fall for phishing emails, and how they react to security warnings. Her interdisciplinary team combines computer science, mathematics, and psychology to develop security solutions that better protect users against attacks while being usable in real-world contexts. Her publication record shows a strong focus on electronic voting security, email security, and cybersecurity awareness. Recent work includes analyzing the security challenges of online general meetings for listed companies, developing child-friendly authentication systems like KidzPass, and creating effective tools for detecting phishing emails. Her research demonstrates consistent attention to both technical security requirements and human factors in security design. Scientific Awards and Recognition: SECUSO tools recommended by the Federal Office for Information Security NoPhish concept materials included in the Federal Office for Information Security's CyberFibel since January 2021 Development of open source privacy-friendly apps available in the App Store Creation of educational tools like the Phishing Master Shooting Game Professor Volkamer actively advises on cybersecurity policy and regularly contributes to public discourse through media appearances and expert statements. She has supervised student projects that have resulted in practical security tools and has collaborated with government agencies including the Federal Ministry of Education and Research (BMBF) and the EU on security research projects. Her work with the Competence Center for Applied Security Technology (KASTEL) positions her at the forefront of Germany's cybersecurity research efforts. SECUSO, under Volkamer's leadership, develops practical security awareness measures including lectures, videos, flyers, and online tools that help citizens recognize fraudulent messages and better protect themselves online. The research group's work bridges academic research and practical application, making significant contributions to both theoretical understanding and real-world security solutions.
Stavros Demetriadis is a Full Professor at the School of Informatics, Aristotle University of Thessaloniki, Greece. His research focuses on Learning Technologies, including Conversational Agents in Education, Learning Analytics, Computer-Supported Collaborative Learning (CSCL), Computational Thinking, and Massive Open Online Courses (MOOCs). He has led EU-funded projects like colMOOC and developed educational tools such as 'pytolearn' for Python instruction and 'Cubes Coding' (winner of Open Education Challenge 2014 and NUMA Competition 2014). He has supervised 5 completed PhD theses, 4 ongoing PhDs, and over 60 Master’s theses. Academic Appointments: Full Professor (2020–present), Associate Professor (2015–2020), Assistant Professor (2012–2015), Lecturer (2002–2008), Informatics Teacher (1989–2002) Education: PhD in Multimedia Technology in Education (2000), MSc in Electronic Physics (1986), BSc in Physics (1983) His work bridges AI and education, with over 161 publications and an h-index of 27. Recent research explores ChatGPT integration, ethics in Learning Analytics, and AI-driven assessment tools. He has delivered invited talks at institutions like the University of Valladolid (2024) and coordinates the 'Teachers' Fast-paced Distance Training on Tele-education' project. Awards include three international best paper awards and recognition for his 'Cubes Coding' project. Key Research Contributions: Developed frameworks for Conversational Agents in CSCL Innovated Computational Thinking pedagogy through robotics Explored ethics and culture in Learning Analytics adoption Created Python-based MOOCs for non-programmers He has taught courses like Human-Computer Interaction and Learning Analytics, and led short programs on Conversational AI. His collaborations span institutions in Spain, Denmark, and Greece. ORCID: 0000-0002-1561-6372; Google Scholar, Semantic Scholar, and Scopus profiles list his extensive output.
Lien-Ti Bei is a Distinguished Professor in the Department of Business Administration at National Chengchi University's College of Commerce in Taipei, Taiwan. She also serves as Chairman of the Center for Public and Business Administration Education. With over 25 years of academic experience, Professor Bei has established herself as a leading scholar in consumer behavior and marketing research in Taiwan and Asia. Her research interests span Consumer Behavior, Consumer Psychology, Brand Management, and Marketing Research, with recent work focusing on ESG implementation, consumer neuroscience applications in marketing, and sustainable business practices. Professor Bei's work bridges theoretical marketing concepts with practical business applications, particularly in the Asian context. Her publication record shows consistent productivity with over 50 journal articles in SSCI/TSSCI-indexed journals since 1995, including recent publications in Journal of Engineering and Technology Management, Journal of Product & Brand Management, and Harvard Business Review Chinese Edition. Her research demonstrates an evolution from traditional brand extension and consumer behavior topics toward contemporary issues like ESG, AI-human interaction, and sustainable marketing practices. Distinguished Professor at National Chengchi University (multiple years) Asia's Top 100 Marketing Scholars (2017) Chungni Outstanding Teaching Award Multiple Research Awards from Taiwan's National Science and Technology Council Management Journal Paper Award Professor Bei has successfully secured numerous research grants, primarily from Taiwan's National Science and Technology Council, with current projects extending through 2026. Her active role as Principal Investigator on multiple grants demonstrates ongoing research productivity. She serves as Editor for Management Review and has contributed to special issues on sustainable development and consumer behavior trends.
R.K. Shyamasundar is a Professor at the Indian Institute of Technology Bombay , with a focus on Real-Time and Reactive Programming, Logic Programming, Pi-Calculus, and Parallel Programs. Research spans formal verification, concurrency, and distributed systems. Key contributions include RT-CDL semantics, Esterel language extensions, and hybrid system controller synthesis. Scientific awards include JC Bose National Fellow, Fellowships at Indian Academy of Sciences and Indian National Science Academy, and Senior Membership in IEEE. His work involves collaborations with institutions like TCS Group and researchers such as Basant Rajan, N. Raja, and Deepak Kapur.
Cathy Ennis is an Assistant Professor in the Department of Computer Science at Maynooth University, Ireland, specializing in perceptually guided graphics and virtual reality. She is actively involved in research and teaching, with affiliations to the ADAPT Centre and D-REAL SFI Centre for Research Training. Education: BEng in Electronic Engineering, Maynooth University MSc in Cognitive Science, University College Dublin PhD in Computer Graphics, Trinity College Dublin PG Dip in Higher Education Teaching and Learning, DIT Research Interests: Dr. Ennis's research centers on creating realistic virtual humans and crowds, exploring multisensory perception in VR, and applying these technologies in serious games and interactive systems. Her work integrates AI, HCI, and immersive technologies to enhance user engagement and learning. Her recent publications reflect a strong focus on virtual character realism, VR-based education, and machine learning applications in animation and interaction. Notable themes include speech-animation realism, cultural VR experiences, and reinforcement learning for character control. Scientific Awards: Best Paper Award, IEEE VR 2022 Teaching and Supervision: Dr. Ennis currently teaches CS401 (Machine Learning and Neural Networks) and CS261 (Multimedia Technology). She is actively seeking PhD students and collaborators interested in VR, games, and virtual characters, particularly using machine learning for gesture generation and engagement. Labs and Teams: She is a Funded Investigator with the ADAPT Centre and D-REAL SFI Centre for Research Training, contributing to interdisciplinary research in AI, HCI, and immersive technologies.
.jpeg)
