Kimbal Marriott is a Professor in Computer Science at Monash University, affiliated with the Clayton School of Information Technology and the Department of Human Centred Computing. He leads the Monash Assistive Tech and Society (MATS) Centre. Previously, he served as Head of the Department of Human-Centred Computing. His research focuses on accessible technologies for visually impaired individuals, leveraging mixed reality, AI, tactile displays, and 3D printing. He holds a PhD (1989) and B.Sc. (Honours) from the University of Melbourne, with prior experience at IBM TJ Watson Research Center. Key projects include 'Accessible Data Exploration and Analysis for Blind People' (ARC-funded) and 'Enabling Accessible, Inclusive Playgrounds for Children with Vision Impairment'. Awards include IEEE InfoVis 2015 Best Paper and Honorable Mention (2016). He teaches units such as FIT5147 (Data Exploration) and FIT1049 (IT Professional Practice). His work aligns with UN SDGs related to education and accessibility. Recent articles emphasize tactile displays combined with conversational agents, commodity technology for accessibility in cultural institutions, and immersive analytics workflows. His book *The Golden Age of Data Visualization* explores historical and technological advancements in the field.
Jian Zhao is an Associate Professor at the University of Waterloo's School of Computer Science, specializing in Information Visualization (InfoVis), Human-Computer Interaction (HCI), and Data Science. With a Ph.D. from the University of Toronto (2016), his research emphasizes interactive visualization techniques, AI integration in design processes, and socio-technical systems. He explores how human-AI collaboration can enhance data analysis, presentation, and user experience in complex systems. Key research areas include: 1) AI-Driven Design (e.g., code generation via sketching, infographic creation), 2) Health Informatics (therapeutic AI tools for autism support), 3) Immersive Technologies (VR/AR interfaces for presentations and education), and 4) Social Computing (remote family communication, multi-modal emoticons). His work bridges technical innovation with human-centered design principles. His publications (2021–2025) reflect a focus on interactive visualization frameworks (e.g., iTrace for cross-view data analysis), AI-human collaboration (CoLadder for hierarchical code editing), and specialized applications like TherAIssist for art therapy and EMooly for autism support. Zhao frequently explores novel interaction modalities , including gesture-based VR interfaces and sketch-based programming tools. He leads projects in computational notebooks (EDAssistant, Slide4N), visual analytics (MissBin for bipartite networks), and neurofeedback training games (Eggly). His work often emphasizes systematic design considerations for missing data, cross-view analysis, and contextual visualization in spatial AR environments.
Giuseppe Santucci is an Associate Professor at the Department of Computer, Control and Management Engineering Antonio Ruberti at Sapienza University of Rome. He teaches courses on Fundamentals of Computer Science, Software Engineering, and Visual Analytics. His office is located in Room B218 at Via Ariosto 25, Rome, and his contact email is santucci@diag.uniroma1.it. Dr. Santucci's research focuses on Visual Analytics, Information Visualization, Human-Computer Interaction, and Information Retrieval. His work spans theoretical aspects of visual query languages for semantic models to practical applications in visual analytics for cybersecurity, cryptocurrencies, and deep learning explainability. He has published over 130 articles in international journals and conferences, demonstrating his significant contributions to these fields. His recent publications show a strong trend toward applying visual analytics to increasingly complex domains including cybersecurity, cryptocurrencies, and explainable AI. The work demonstrates an evolution from theoretical foundations of visual query systems to practical applications that help users understand complex data and systems. His research bridges the gap between theoretical computer science and practical user-centered solutions. Dr. Santucci has received notable recognition including: IEEE VizSec 2018 Best Paper Award Human-Computer Interaction Cybersecurity Awards 2018 He actively mentors students through thesis projects focused on information visualization and visual analytics. His PROMISE project provides a framework for students to engage in cutting-edge research in information retrieval and visual analytics. He has supervised work on topics including visual evaluation techniques, visual mappings optimization, and user studies for Infovis systems. Dr. Santucci leads the A.WA.RE (Advanced Visualization & Visual Analytics REsearch) group at Sapienza University. This group conducts research on visual analytics tools for information retrieval evaluation, cybersecurity analysis, and deep learning explainability. Their work includes developing frameworks like CryptoComparator for cryptocurrency analysis and BUCEPHALUS for cybersecurity platform analysis.
Professor Jason Dykes is a leading figure in the field of information and geovisualization at City, University of London, where he holds the position of Professor in the Department of Computer Science and co-directs the giCentre , a renowned research centre in visualization. He is affiliated with the School of Mathematics, Computer Science and Engineering and maintains an active research and teaching profile. His academic journey includes a PhD in Geography from the University of Leicester and extensive leadership in both research and education. Education: PhD in Geography, University of Leicester, 2000 MSc in Geographic Information Systems, University of Leicester, 1991 BA/MA in Geography, University of Oxford, 1989 Jason Dykes' research is centered on designing visual methods and tools for exploring, analyzing, and presenting information, with a strong emphasis on geographic data. His work integrates cartography, information visualization, GIScience, and human-computer interaction , leading to the development of innovative techniques such as geowigs, ODmaps, BallotMaps, and AttributeSignatures. He has published extensively in top-tier journals like IEEE Transactions on Visualization & Computer Graphics, with over 20 papers in the last decade, and co-authored the seminal book Exploring Geovisualization (2005). His research is supported by major funders including EPSRC and the EU, with projects like RAMP VIS (Covid-19 response) and VALCRI (criminal intelligence). The most recent articles highlight a consistent trend in applied and human-centered visualization , focusing on responsive design, education, pandemic modeling, and novel visual metaphors for complex data. His work increasingly emphasizes methodological rigor, design exposition, and the role of visualization in interdisciplinary and emergency contexts. Scientific Awards and Recognition: National Teaching Fellow, Higher Education Academy (2005) Best Paper Awards at GIS Research UK (consecutive years) Honorable Mentions, IEEE InfoVis (2009, 2010, 2016, 2018) Security Innovation Commercialisation Award (EU, 2022) Research Supervisor of the Year, City Student Union (2020) Innovations in Teaching Award and multiple teaching grants at City Jason Dykes has supervised eight PhD students to completion and advised many others, including notable researchers like Roger Beecham, Sarah Goodwin, and Susanne Bleisch. His teaching includes modules such as Visualizing Society and Data Presentation. He has received significant grant funding from UK research councils and the EU for projects like DIVA, VALCRI, and RAMP VIS. His service to the community includes leadership roles in IEEE VIS, ICA Commission on GeoVisualization, and editorial positions at IEEE TVCG and the Journal of Visualization and Interaction. He leads the giCentre , a dynamic research group that fosters innovation in visualization, and has been instrumental in establishing the field’s educational and methodological foundations through participation in Dagstuhl seminars and publications on visualization pedagogy.
Bill Howe is an Associate Professor at the University of Washington's Information School, with adjunct appointments in Computer Science & Engineering and Electrical Engineering. He serves as Founding Program Director and Faculty Chair of the UW Data Science Masters Degree, Founding Associate Director and Senior Data Science Fellow at the UW eScience Institute, Director of the Urbanalytics Lab, and Co-Founding Director of the Center for Responsible AI Systems and Experiences. He also co-founded Urban@UW and created the first Data Science MOOC through Coursera. His research focuses on making data science accessible in public sector applications with emphasis on equity, privacy, and compliance. Current interests include: Algorithmic fairness in urban and social contexts Privacy-preserving synthetic data generation Machine learning for heterogeneous data Database systems and high-performance computing Human-computer interaction for data systems Responsible AI development and deployment Publication analysis reveals strong focus on responsible data science, with recent work emphasizing differential privacy, COVID-19 data equity, urban mobility fairness, and relational data systems. Earlier foundational work established contributions to scientific workflow systems and data pricing models. Awards and Honors: Runner-up Best Paper Award (VLDB 2023) Best Paper Award (SIGMOD 2019) Best Paper Award (VIs 2019) Best Paper Award (InfoVis 2018) He leads the Urbanalytics Lab and advises multiple students including An Yan (fairness in urban mobility), Sean Yang (machine learning embeddings), and Dominik Moritz (visualization systems). His projects span EZLearn for automatic claim validation, privacy-preserving synthetic data, and Myria middleware for polystores.
Professor Joseph Wood is a Professor of Visual Analytics at City St George's, University of London, where he serves as a founding member of the giCentre. His academic career spans over three decades, with continuous contributions to Geographic Information Science and visualization since 1990. He previously served as Head of Department for Computer Science at City University between 2014 and 2017. Professor Wood's educational background includes a PhD in Geographical Information Science from the University of Leicester (1996), an MSc in the same field from the University of Leicester (1990), and a BSc in Physical Geography & Geology from the University of Sheffield (1989). His academic progression shows steady advancement from Research Scholar at the University of Leicester (1990-1992) through various lecturer and senior positions to his current professorship. His research interests center on visual analytics and data visualization, with particular expertise in geographic information science and terrain analysis. Professor Wood has developed innovative methods bridging GI Science, Data Visualization, and education domains. His specific interests include narrative of visual analytic design, computational thinking in pedagogy, and novel visualization design for geographic data. His work demonstrates a consistent focus on making complex spatial data understandable through innovative visualization techniques. Analysis of Professor Wood's recent publications reveals a strong emphasis on practical applications of visualization techniques across diverse domains including transportation, epidemiology, sports analytics, and historical migration patterns. His work shows an evolution from foundational geographic information science toward broader applications in visual analytics, with increasing focus on narrative structures, responsive design, and accessibility considerations in visualization. The interdisciplinary nature of his research is evident in collaborations spanning computer science, geography, urban planning, and public health domains. Professor Wood has been actively involved in the academic community, serving on organizing and program committees for major international conferences including IEEE Infovis and VAST, Eurovis, GIScience, Spatial Accuracy, and Geomorphometry. His contributions to the field have been recognized through invitations to deliver keynote talks at prestigious venues ranging from GeoComputation to TEDx, where he presented on topics such as visualizing movement behavior of cyclists. As an advisor, Professor Wood has supervised numerous PhD and Master's students, with current supervision of Julia Crossley (Student conceptualisation of abstraction in computer science) and Jude Nzemeke (Understanding student misconception in recursive algorithmic thinking). His extensive supervision history includes completed PhDs on topics ranging from cycling behavior to spatio-social relations in photographic archives. His academic leadership extends to software development, with contributions to tools like litvis, elm-vega/el-vegalite, giCentre Utils, handy, and LandSerf GIS. Professor Wood is an active member of professional organizations including IEEE (2007-present), Association of Computing Machinery (ACM) (2007-present), and Association of Geographic Information (AGI) (1997-present), demonstrating his commitment to interdisciplinary collaboration across computer science and geographic information domains.
Dominik Moritz is a Professor at Carnegie Mellon University's Human-Computer Interaction Institute and concurrently serves as an ML Researcher at Apple. He co-leads the Data Interaction Group, focusing on building interactive visualization systems. His educational background includes a PhD from the University of Washington's Paul G. Allen School and a B.S. from Hasso Plattner Institute. Moritz's research spans interactive visualization systems , scalable data analysis tools , and accessibility-focused design . His work combines database technologies with human-computer interaction to create frameworks like Mosaic for cross-filtering billion-record datasets and Draco for visualization constraint modeling. Projects include Vega-Lite (high-level visualization grammar) and Swift Charts (Apple's charting framework). His publications consistently explore scalability in visualization , perceptual accuracy in data representation , and accessibility tooling , with recent work emphasizing real-time interaction with massive datasets. Awards include multiple Best Paper recognitions at VIS/InfoVis. Fulbright Program German National Academic Foundation Scholar Best Paper Honorable Mention (VIS 2023 ×2) Best Paper (InfoVis 2018) Best Paper (InfoVis 2017) SIGGRAPH Invitation (2016) Moritz mentors PhD students through the Data Interaction Group and has collaborated with Google Research, Microsoft Research, and Open Knowledge Foundation. His systems are widely adopted in Python/JavaScript data science communities.
Lena Cibulski is a Postdoctoral Researcher at the Institute for Visual and Analytic Computing , University of Rostock , Germany. Her work focuses on the design of visualization tools that empower experts to make data-informed decisions, particularly in engineering and life-science contexts where human expertise must be synthesized with large, complex data. Education PhD in Visualization, 2024 – Technical University of Darmstadt, Germany MSc in Computer Science, 2017 – Otto-von-Guericke University Magdeburg, Germany BSc in Visual Computing, 2016 – Otto-von-Guericke University Magdeburg, Germany Research Interests Lena’s research blends computer science, design, and decision theory . She investigates how interactive visualizations can amplify experiential knowledge, support preference construction, and facilitate multi-attribute choices under conflicting objectives. Key themes include: Multivariate and temporal data visualization Human factors and cognition in visual analytics Real-world, application-driven design studies in engineering and life sciences Parameter-space exploration, feature engineering, and causal analysis Publication Trends Across 2020-2025 her articles cluster around three thrusts: (1) foundational work on Pareto-based decision interfaces (PAVED, COMPO*SED), (2) empirical studies of visualization adoption and usability in manufacturing and engineering, and (3) methodological contributions toward understanding decision problems as a primary goal of visualization design. Recent papers extend these ideas to cell-signaling simulations and sustainable-development education. Scientific Awards 2024 – Best Dissertation in Computer Science, TU Darmstadt 2025 – Honorable Mention, VRVis Visual Computing Award Teaching, Outreach & Collaboration Lena currently teaches master-level courses on visualization, visual analytics, and interactive data analysis at the University of Rostock. She is open to multidisciplinary collaborations involving human factors, methodological aspects of visualization research, and real-world applications. Interested students or partners are encouraged to contact her directly.
Dr. Sarah Goodwin is a Senior Lecturer at Monash University's Department of Human Centred Computing, specializing in geospatial analysis and information visualization. She leads the Embodied Visualisation research group and holds roles as Director of Engagement for Human-Centred Computing and co-Director of the Monash Grid Innovation Hub. Her work focuses on creating visual solutions for complex data, including energy grid analysis, cancer prevalence visualization, and urban data exploration. Dr. Goodwin has over 20 years of experience in academic and professional roles, collaborating globally with institutions like the giCentre (City University London) and RMIT University. Education: She holds a PhD in Geographical Information Science (City University London, 2015), MSc in Geographical Information Systems (City University London, 2007), and BSc (Honours) in Geography (University of Manchester, 2003). Research Interests: Geovisualization, energy data analytics, urban data visualization, HCI, and geostatistical modeling. She has developed tools like Gazealytics and led projects such as the Australian Cancer Atlas and the Australia's Discourse Explorer. Teaching: She teaches Data Exploration and Visualisation (FIT5147) and Research Methods at Monash, impacting over 1000 students annually. She has also taught at RMIT University. Grants & Awards: Recipient of the IEEE InfoVis Best Paper Honorable Mention (2016). Active in conferences like IEEE VIS (General Chair, 2023) and organizes workshops on EnergyVis and CityVis. Labs & Teams: Involved with the Immersive Analytics Lab and collaborates with Monash Energy Institute and Data Futures Institute. Her work aligns with UN SDGs on sustainable cities and energy systems.
Michael Oppermann is a researcher, data visualization developer, and co-founder of Viaduct, currently affiliated with the Austrian Institute of Technology (AIT) . His work integrates visualization, machine learning, and human-centered design to create interactive tools for data exploration and communication. He holds a PhD in Computer Science from the University of British Columbia (2021), where he collaborated with Tamara Munzner's InfoVis Group, and a Master of Business Informatics from the University of Vienna (2017). Expertise in interactive visualization, mixed-methods research, and web development Previously served as a visiting research fellow at Harvard University's Visual Computing Group Industry experience at Tableau Software and Virtual Identity as a data science consultant His research spans human-data interaction, haptics, and spatiotemporal data analysis. Publications include top venues like CHI , IEEE VIS , and EuroVis . He has contributed to projects such as VizSnippets , Haptipedia , and Bike Sharing Atlas . Awards include the Accenture Campus Innovation Challenge first place in Austria (2016) and recognition in the NaturTalente High Potential Program (2016). Michael also has extensive teaching experience, having restructured large undergraduate courses and served as a teaching assistant for human-computer interaction and visualization topics.
Assoc. Prof. Michael Wybrow is an Associate Professor in the Department of Human Centred Computing at Monash University's Faculty of Information Technology. His research focuses on visual interfaces for AI explainability, constraint-based optimization, and interactive visualization, with applications in healthcare, energy systems, and decision-making. He holds a PhD from Monash University (2008) and a Bachelor of Computer Science (Honours) from the University of Melbourne (2003). Wybrow has received notable awards, including the Australasian Distinguished Doctoral Dissertation (2009) and the IEEE InfoVis 2015 Best Paper Award. He leads industry projects on chemical plant layout optimization and Bayesian network reasoning, and serves as Director of Work Integrated Learning, overseeing Monash's industry placement programs. Wybrow has developed influential software tools like libavoid and Dunnart, contributing to both academia and industry. His teaching includes creating the ENG1003 course for engineering students, emphasizing app development and software engineering. Over $2.25M in competitive and industry grants fund his research, with collaborations spanning healthcare, energy, and visualization domains. Recent projects include optimizing LNG plant layouts with Woodside Energy, developing near-real-time healthcare dashboards for Eastern Health, and improving causal reasoning through Bayesian networks. Wybrow's work aligns with UN Sustainable Development Goals, particularly in healthcare and sustainable energy.
Kalliopi Kontiza serves as a Lecturer (Teaching) in Computing and Information Systems within the Department of Information Studies at University College London. Her academic foundation combines linguistics expertise with specialized information science training. Education: PhD in Information Studies, University College London (thesis: Cognition-Based Evaluation of Visualisation Frameworks for Exploring Structured Cultural Heritage Data ) MSc in Information Science, University College London (specializing in Semantic Web and InfoVis) Bachelor's in Linguistics, University of Athens Her research pioneers cognitive approaches to visualizing cultural heritage data, focusing on how Information Visualization tools enhance user engagement with museum collections and digital exhibitions. She investigates the intersection of semantic technologies , storytelling techniques , and user experience in contexts like the CrossCult H2020 project, where she developed frameworks for evaluating visitor interactions with digital cultural resources. Current work emphasizes timelines , maps , and interactive narratives as vehicles for deeper historical understanding. Her 15 recent publications (2014-2023) reveal consistent focus on cultural heritage visualization, with growing emphasis on sustainability and educational applications. Key themes include semantic representation of museum collections, evaluation methodologies for digital exhibitions, and technology-powered storytelling across multiple venues. Teaching Activities: Undergraduate: INST0003 Information Systems (Module Leader) Postgraduate: INST0018 Internet Technologies (Teaching Assistant), INST0038 Fundamentals of Information Science (Module Leader) She actively participates in the Hellenic Digital Humanities Research Network and Ionian Islands Museum Network, contributing to European digital heritage initiatives. Her work aligns with UN Sustainable Development Goal 4 (Quality Education) through technology-enhanced cultural learning.
Fereshteh Amini is a Lecturer at the University of California, Berkeley School of Information and Senior Applied Data Scientist at Microsoft Corp. Her research focuses on: Data Science Human-computer Interaction (HCI) Information Visualization User Experience Research She earned her PhD at the University of Manitoba and has published extensively in leading HCI venues like CHI and IEEE VIS. Her work explores: Animation techniques for data dashboards Immersive visualization via VR/AR Collaborative visual analytics Temporal data representation Recent publications include studies on dynamic organizational networks and 3D data recall. Recognitions include: NSERC Postdoctoral Fellowship (2018) Multiple Manitoba University travel grants IEEE InfoVis reviewer (2013-2017) She has taught Data Science 209: Data Visualization since 2018 and previously taught computer science courses at University of Manitoba and University of Winnipeg.
Tim Dwyer is a Professor of Data Visualization and Immersive Analytics at Monash University's Faculty of Information Technology, Department of Human Centred Computing. He holds a PhD from the University of Sydney (2005) and has extensive industry experience, including roles at Microsoft Research and Microsoft Corporation. His research focuses on information visualization, network visualization, and immersive analytics, leveraging emerging technologies like AR/VR to enhance data analysis. He leads the Immersive Analytics Lab and has advised numerous PhD students. Education: PhD in Computer Science, University of Sydney (2005) Bachelor of Computer Science (Honours), University of Melbourne (2001) Bachelor of Science, University of Melbourne (1995) Research Interests: Tim's work spans information visualization, network visualization, and immersive analytics. He explores how technologies like augmented and virtual reality can transform data analysis. Key areas include network layout optimization, novel data representations, and interaction design. His Immersive Analytics Lab pioneers projects such as Immersive Analytics (book) and the IATK toolkit. Article Trends: Recent work emphasizes immersive analytics applications (e.g., forensic autopsy in mixed reality), network visualization techniques (e.g., torus wrapping), and human-computer interaction challenges in AR/VR. His research bridges theoretical foundations (e.g., graph proofs) and practical tools (e.g., visualization toolkits). Awards: IEEE InfoVis 2015 Best Paper Award IEEE InfoVis 2016 Honorable Mention Advising & Grants: Current PhD students include Benjamin Lee and Kun-Ting Chen. He leads projects funded by CSIRO, Australian Research Council, and industry collaborations. Notable grants include 'Australian Research for Global Power System Transformation' and 'Immersive Analytics CRC'. Labs & Teams: Director of the Immersive Analytics Lab, collaborating with global researchers on projects like IATK (Immersive Analytics Toolkit) and Immersive Human-Centred Computational Analytics. Active in IEEE VIS conferences as a chair and organizer.
Kresimir Matkovic serves as an Associate Professor in the Computer Graphics department (E193-02) at the Faculty of Informatics, Vienna University of Technology. His research spans multiple domains within visualization, with a particular focus on applying visualization techniques to solve complex problems in geology, healthcare, engineering, and meteorology. His work bridges the gap between theoretical visualization principles and practical applications in diverse scientific fields. Dr. Matkovic's research interests center around Computer Graphics, Information Visualization (InfoVis), Scientific Visualization (SciVis), and Human-Computer Interaction (HCI). His work demonstrates a strong emphasis on developing interactive visual analytics systems that enable domain experts to explore complex datasets. A significant portion of his research focuses on geological data visualization, particularly for mineral classification and analysis, where he has developed specialized tools like the Spinel Explorer. His work also extends to healthcare visualization, where he has created systems for analyzing intensive care unit data, and engineering applications, where visual analytics supports simulation and design processes. An analysis of his recent publications reveals a consistent focus on developing interactive visualization techniques for domain-specific applications. His work shows a progression from foundational visualization techniques toward more specialized domain applications, particularly in geology and healthcare. His research demonstrates a strong interdisciplinary approach, collaborating with domain experts to develop visualization solutions that address specific scientific challenges. The publications show consistent contributions to major visualization conferences including IEEE Transactions on Visualization and Computer Graphics and EuroVis. Dr. Matkovic has supervised multiple students including Radoš, S. (2023) on reprojecting visualizations for advanced interaction, Priselac, M. (2021) on visual analytics of spatial time series data, and Freiler, W. (2008) on set type enabled information visualization. His research has been supported by several major projects including Visual Computing-Basic Research (2008-2013) at VRVis, KASI (2010-2015) focused on Visual Analytics for Complex Engineering Systems, and HypoVis (2011-2015) which explored various visual analytics applications. His laboratory work centers around the development of interactive visual analytics systems, with particular emphasis on applications in geological data analysis, medical/healthcare visualization, and engineering systems. His team has developed specialized tools like the Spinel Explorer for mineral analysis and Albero for weather forecasting visualization. Current research appears to be focused on advancing interactive techniques for visual analytics, particularly in handling complex, multi-dimensional datasets across various scientific domains.
