Find Academic Supervisors

Dominik MoritzView profile

Professor

• Data Visualization
• Human-Computer Interaction
• Interactive Systems
• +3 more

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.

• Climate Science
• Environmental Data Management
• Geographic Information Systems (GIS)
• +3 more

Jon Blower is an academic affiliated with the University of Reading's Department of Geography and Environmental Science. His work focuses on climate data management, environmental data visualization, and geospatial technologies. He has contributed to projects like the C3S ECEM climate service, the CHARMe metadata initiative, and the GODIVA2 web mapping system. His research spans cloud computing applications in environmental science, oceanographic data dissemination, and urban density analysis. He has authored over 40 peer-reviewed publications and technical reports, including foundational work on Climate Forecast metadata conventions and cloud-based GIS systems. Blower has led interdisciplinary efforts in integrating environmental data quality frameworks and developing open-source tools for geospatial analysis. Education & Background: While specific educational details are not explicitly stated, his extensive contributions to environmental science and computing imply advanced training in these fields. His work often bridges computer science and environmental applications, suggesting a multidisciplinary academic background. Research Focus: Key areas include: Data interoperability standards (e.g., CF metadata conventions) Climate service development for energy policy Interactive environmental data visualization systems Cloud computing for large-scale environmental datasets Oceanographic data synthesis and quality frameworks Recent Trends in Publications: Recent work emphasizes urban systems analysis (2023), renewable energy-climate integration (2018), and cloud infrastructure for environmental science (2014/2016). Earlier contributions focused on ocean data systems (2009-2012) and grid computing for climate modeling (2006-2009). Awards & Grants: No specific awards listed, but his sustained contributions to major projects like GODAE and MELODIES reflect institutional recognition. Active in grant-funded initiatives related to environmental data infrastructure. Labs/Teams: Collaborates with teams at the National Oceanography Centre, NASA, and European climate initiatives. Core contributor to projects managed by organizations like ESA and the UK's Natural Environment Research Council (NERC).

Uwe RoehmView profile

Associate Professor

• Distributed Data Management on Modern Hardware
• Integrated Machine Learning with Databases
• Interactive Big Data Analytics
• +5 more

Associate Professor Uwe Roehm is a faculty member at the University of Sydney's School of Computer Science, specializing in database systems and big data analytics. He holds a PhD from ETH Zurich and joined the University of Sydney in 2004. His research focuses on distributed data management, integrating machine learning with databases, and scalable data processing for bioinformatics. Education: PhD in Computer Science, ETH Zurich (2002) Diplom-Informatics (MSc equivalent), University of Passau Research Interests: Database Systems and Transaction Processing Human-Centred Data Management Freshness-Aware Scheduling (FAS) Big Data Analytics and Cloud Computing Key Projects and Contributions: Developed Serialisable Snapshot Isolation (SSI), implemented in PostgreSQL Created the Master of Data Science program at the University of Sydney Recipient of the 2018 ACM SIGMOD Test of Time Award Awards: 2018 ACM SIGMOD Test of Time Award 2013 Dean's Award for Outstanding Teaching 2008 ACM SIGMOD Best Paper Award Teaching and Grants: Teaches courses on database systems, data science platforms, and cloud computing Principal Investigator on ARC-funded projects, including Linkage and Discovery grants Labs and Teams: Leads the Database Research Group and contributes to the Human-Centred Technology Research Cluster at the University of Sydney.

• Computer Science
• Cybersecurity
• WebAssembly Security
• +3 more

Weihang Wang is a Volunteer Assistant Professor in the Department of Computer Science and Engineering at the University of Southern California (USC), part of the School of Engineering and Applied Sciences. His research focuses on WebAssembly security, program analysis, and static/dynamic analysis frameworks. He holds a PhD and has published extensively on topics like WebAssembly obfuscation, decompilation techniques, and flaky test mitigation. Research interests include cybersecurity, software engineering, and the application of AI in program analysis. His work addresses challenges in cross-compilation for WebAssembly, decompilation accuracy, and automated detection of security vulnerabilities in web applications. Notable projects include WaSCR (side channel repairer), WBSan (bug detection), and Wefix (flaky test automation). He has received NSF travel grants for IEEE Security Development (SecDev) conferences in 2022 and 2023. His articles span 2010–2025, showing sustained contributions to web security, compiler optimization, and program transformation. His work intersects with practical applications like ad-blocking systems (Adhere) and bird flu outbreak prediction using migration data (2010–2013). Grants and awards include NSF funding for travel and research, reflecting his active role in academic conferences. He is affiliated with USC's computer science department and maintains an active Google Scholar profile with over 30 publications listed.

Stephen RamseyView profile

Associate Professor

• Computational Systems Biology
• Bioinformatics
• Precision Medicine
• +6 more

Stephen Ramsey, an Associate Professor at Oregon State University, holds dual appointments in the School of Electrical Engineering and Computer Science (College of Engineering) and the Department of Biomedical Sciences (Carlson College of Veterinary Medicine). With a PhD in Physics from the University of Maryland, his postdoctoral training in computational genomics at the University of Washington, and professional experience at the Institute for Systems Biology and Center for Infectious Disease Research, Ramsey bridges computational methods with biomedical applications. Education : Ph.D., Physics, University of Maryland; M.S., Physics, University of Maryland; Sc.B., Mathematical Physics, Brown University Ramsey specializes in computational systems biology , focusing on bioinformatics , biomedical knowledge graphs , and precision medicine . His research integrates machine learning , gene regulatory network modeling , and multi-omics data analysis to address challenges in rare disease diagnostics , drug monitoring , and inflammatory disease mechanisms . Current work includes AI-driven biomedical translation and electrochemical biosensor development for non-invasive diagnostics . Recent publications highlight knowledge graph applications in translational biomedicine , causal network inference in clinical-environmental data integration , and cross-species cancer transcriptomics . His team develops tools like RTX-KG2 and PloverDB to standardize biomedical data sharing and semantic reasoning . Scientific Awards : 2019 Zoetis Award (Carlson College of Veterinary Medicine) 2016 NSF CAREER Award 2016 PhRMA New Investigator Award 2010 NIH K25 Mentored Quantitative Research Award Ramsey advises in computational biology courses (CS 446/546) and contributes to biomedical AI through projects like mediKanren for rare disease diagnostics . His NSF-funded research explores gene expression noise and regulatory network dynamics , while NIH and PhRMA grants support his translational medicine initiatives. He leads the Ramsey Laboratory , which develops graph-based reasoning tools for biomedical data translation and multi-omics integration . The lab's work spans comparative oncology models, electrochemical biosensors , and knowledge graph infrastructure for clinical decision support .

Josep CasanovasView profile

Professor

• Modelling and Simulation
• Internet and Information Systems
• Urban Mobility
• +4 more

Josep Casanovas is a Full Professor at the Statistics and Operations Research Department of the Technical University of Catalonia (UPC), affiliated with the Barcelona School of Informatics. He previously served as head of inLab FIB (2012-2020) and as dean (1998-2004) and vice-rector (2006-2011) of UPC, leading strategic initiatives in university governance and ICT policies. His research focuses on Modelling and Simulation , Internet and Information Systems , and Urban Mobility . He has led projects for the European Union, including C-ROADS Spain, REMEDiAL, and ECHORD++, addressing intelligent transport, software automation, and robotic innovation. Recent publications highlight his work on agent-based simulation for urban health, deep learning applications in traffic and energy savings, and wildfire management tools . He co-directs LogiSim and coordinates the Severo Ochoa Research Excellence Program at the Barcelona Supercomputing Center (BSC-CNS).

Dominik MoritzView profile

Assistant Professor

• Human-Centered Machine Learning
• Data Science
• Interactive Systems
• +6 more

Dominik Moritz is an Assistant Professor at the Human-Computer Interaction Institute (HCII) of Carnegie Mellon University and Machine Learning researcher at Apple. He leads the Data Interaction Group and develops systems for interactive data visualization. Ph.D. in Computer Science from University of Washington (2019) B.S. in Computer Science from Hasso Plattner Institute (2013) His research focuses on: Human-Centered Machine Learning Data Visualization Toolkits Interactive Systems Design Accessibility in Visual Analytics Scalable Web-Based Visualization Recent publications address visualization design knowledge formalization (Draco), cross-filtering frameworks (Mosaic), and accessibility evaluation (Chartability). He has received Best Paper Honors at VIS and EuroVis conferences. Professional Collaborations: Co-founder of Vega-Lite visualization grammar Collaborations with Jeff Heer, Bill Howe, Jock MacKinlay Projects with Microsoft Research and Google Research

Debra DavisView profile

Academic

• Human-Computer Interaction
• Applied Usability Studies
• Cognitive Psychology
• +2 more

Debra Davis is an Associate Teaching Professor at Florida International University , affiliated with the School of Computing and Information Sciences (2010–present) and serving as an Adjunct Faculty Member in the Department of Psychology (2010–present). She holds a Ph.D. in Cognitive Developmental Psychology (2004) and advanced degrees in Computer Science (2000) and Psychology (1996), with a minor in Statistics. Education : Ph.D., Cognitive Developmental Psychology (minor: Statistics), University of Texas at Austin (2004) M.S., Computer Science, Florida International University (2000) M.A., Developmental Psychology (minor: Statistics), University of Texas at Austin (1996) B.A., Psychology (minor: Computer Science), Florida International University (1993) Her research spans Human-Computer Interaction , Applied Usability Studies , and geospatial data systems, with expertise in real-time data integration, 3D visualization, and educational technology. She has contributed to spatial data platforms like Terrafly and advised on usability for grants and projects. Recent publications (1998–2001) focus on geospatial data systems, real-time search algorithms, and 3D satellite imagery. Awards include multiple Phi Kappa Phi Honor Society nominations, a research grant at UT Austin, and Dean’s List recognition. Professional Roles : Faculty Associate, NSF Industry-University Cooperative Research Center (2010–present) Principal Investigator, All Stars Effectiveness Research Project (2007–2008) Program Evaluator, Read 2 Succeed 21st Century Grant (2009–2010) Consultant, Collins Center of Public Policy (2008) Grant Reviewer for Miami-Dade County, Early Learning Coalition, and CASA (2005–2009)

Renato PajarolaView profile

Professor

• Computer Graphics
• Scientific Visualization
• 3D Modeling
• +5 more

Prof. Dr. Renato Pajarola is the Head of the Visualization and MultiMedia Lab at the Department of Informatics, University of Zurich. His research focuses on computer graphics, scientific visualization, and geometric processing, with applications in 3D scanning, point cloud analysis, and real-time rendering. He leads a team developing advanced visualization techniques for high-dimensional data, parallel rendering frameworks, and interactive systems for complex datasets. Key research areas include: 3D reconstruction of indoor environments Tensor approximation for volume visualization Interactive ray tracing and point cloud processing Parallel rendering frameworks (e.g., Equalizer) Scientific computing and sensitivity analysis His recent publications emphasize: High-dimensional data exploration using tensor methods Efficient rendering techniques for large-scale point clouds Integration of citizen-reported weather data for environmental analysis Prof. Pajarola’s lab collaborates on projects like VIAN (visual annotation tool for film analysis) and Terrender (web-based terrain visualization). His Erdős number is 3, reflecting interdisciplinary research connections in mathematics and computer science.

Jan Helge BøhnView profile

Associate Professor

• Rapid Prototyping
• Additive Manufacturing
• Geometric Modeling
• +5 more

Dr. Jan Helge Bøhn is an Associate Professor in the Department of Mechanical Engineering at Virginia Tech's College of Engineering, specializing in rapid prototyping, additive manufacturing, geometric modeling, and international engineering education. His work bridges global collaborative engineering with innovative product development processes. Ph.D., Computer and Systems Engineering, Rensselaer Polytechnic Institute (1993) M.S., Computer and Systems Engineering, Rensselaer Polytechnic Institute (1989) B.S., Computer Science, Rensselaer Polytechnic Institute (1988) His research focuses on additive manufacturing and global engineering design , with applications in transatlantic dual degree programs, automotive PLM, and haptic accessibility solutions. He has pioneered adaptive slicing techniques for 3D printing and developed international curricula frameworks. Dr. Bøhn's publications highlight trends in collaborative engineering education , 3D printing , and human-computer interaction , particularly for low-vision users and automotive sectors. 2018 : PACE Platinum Certification 2015 : Alumni Award for Excellence in International Outreach 2013 : Virginia Tech Scholar of the Week & PACE Silver Certification He has led international initiatives, received multiple teaching excellence awards, and collaborated on global PLM educational labs. His work impacts both engineering pedagogy and industrial practices.

Xiaolin HuView profile

Professor

• Modeling and Simulation
• Complex Systems Science
• Agent-Based Systems
• +3 more

Xiaolin Hu is a Professor in the Department of Computer Science at Georgia State University within the College of Arts & Sciences. His research focuses on modeling and simulation theory with applications in complex systems science, agent-based systems, and advanced computing environments. Ph.D. in Electrical and Computer Engineering, University of Arizona (2004) NSF CAREER Award recipient Senior member of IEEE and Society for Modeling and Simulation International (SCS) Associate editor for ACM Transactions on Modeling and Computer Simulation (TOMACS) and other journals SIMULATION: Transactions journal and International Journal of Modeling, Simulation, and Scientific Computing (IJMSSC) Dr. Hu's research spans three major areas: Dynamic Data-Driven Simulation (DDDS): Development of simulation frameworks that assimilate real-time data, particularly applied to wildfire spread prediction and autonomous systems. Multi-Agent Systems: Study of adaptive behaviors and coordination mechanisms for unmanned aircraft and social/public health systems. Advanced Computing: Implementation of parallel and cloud computing solutions for large-scale simulations. His recent publications (2025-2023) demonstrate a strong focus on integrating real-time data from UAVs and satellite systems into wildfire simulations, utilizing Bayesian methods for sequential data assimilation, and developing cloud-based simulation services. These works bridge computational modeling with environmental science applications. Scientific recognitions include: National Science Foundation (NSF) CAREER Award Dr. Hu has chaired multiple international conferences in modeling and simulation and leads the SIMS Lab at Georgia State University, which specializes in simulation technologies and their applications in diverse domains.

Nicolas LouvetonView profile

Associate Professor

• Human-Computer Interaction
• Cognitive Ergonomics
• Virtual Reality
• +4 more

Nicolas Louveton is an Associate Professor at the University of Poitiers, affiliated with the Center for Research on Cognition and Learning (CeRCA) within the School of Humanities and Social Sciences. His work bridges cognitive science and practical interface design across automotive, cybersecurity, and industrial contexts. His research focuses on Human-Computer Interaction , Cognitive Ergonomics , and Virtual Reality , with specific expertise in visual attention, multitasking performance, and driver behavior. Current projects include the RESISTECC initiative for cyber crisis management training, industrial VR maintenance scenarios (INTEROPS project), and autonomous vehicle trust studies (CMI project). Louveton's recent publications reveal a strong trend toward applied VR solutions for high-stakes environments, particularly in cybersecurity training effectiveness and driver-AI interaction. His work consistently applies cognitive ergonomics principles to measure mental workload, situational awareness, and usability in complex systems. As an educator, he leads the UX/UI Ergonomics Master's program and teaches courses on interface usability, visual perception, and UX research methodology. He also serves as Carnot Cognition correspondent for CeRCA laboratory. Supervises PhD candidates Marine Desvergnes and Deslande Liboutchi Pepe Formerly co-supervised Clarisse Lawson-Guidigbe (now Head of Web Editorial) Member of CNU 16 (Psychology and Ergonomics) 2019-2023 Co-head of Digital Interactive Games and Media Master's program 2018-2022

• Distributed Computing
• High-Performance Computing
• Parallel Systems
• +7 more

Tore Brox-Larsen is an Associate Professor in the Department of Informatics at UiT The Arctic University of Norway. He is actively involved in research and teaching, with a focus on distributed computing, high-performance systems, and visualization technologies. His work is centered on scalable systems for large displays, sensor networks, and remote data visualization, often in collaboration with interdisciplinary teams. His research interests include distributed and parallel computing, remote visualization over wide-area networks, large-scale display systems, health informatics, and Arctic monitoring technologies. He has contributed significantly to the development of systems for tiled display walls, genomics visualization, and sensor-based observatories. His work bridges theoretical computer science with practical applications in healthcare, environmental monitoring, and collaborative research environments. The most recent publications reflect a strong trend in applying computing technologies to real-world challenges, particularly in Arctic research and healthcare. His work emphasizes performance optimization, usability, and scalability in distributed systems. Topics span from low-level communication latency analysis to high-level collaborative visualization frameworks. Scientific Awards: No scientific awards mentioned in the provided text. Advising and Grants: There is no explicit information about students advised or research grants received. However, his extensive publication record and collaborative projects suggest active participation in funded research initiatives and potential mentorship of junior researchers and students. Labs and Teams: Tore Brox-Larsen is part of a long-standing research group at UiT involving Otto Anshus, John Markus Bjørndalen, and others, focusing on high-performance distributed systems. He has contributed to the development of the MultiStream system, scalable display walls, and the Arctic observatory sensor network. His work indicates involvement in both software and systems research teams, likely associated with UiT’s informatics infrastructure and high-performance computing initiatives.

• Building Automation
• Energy Management
• Query Optimization
• +7 more

Paulo Carreira is an Associate Professor at Instituto Superior Técnico , Universidade de Lisboa. His research focuses on Building Automation , Energy Management , and Data Integration , with a particular emphasis on Smart Urban Environments and Cyber-Physical Systems . Fields: Building Automation, Energy Management, Data Privacy, Query Optimization, ETL, Streaming Query Processing Research Trends : His recent work spans from SQL Injection Attacks in LLM-integrated systems to Multi-Paradigm Modeling for Cyber-Physical Systems. Publications highlight his expertise in Energy Efficiency in buildings and BIM Integration with real-time data. Scientific Awards : Best Student Paper Award Nomination for Best Paper Award

José María Alonso MoralView profile

Associate Professor

• Explainable Artificial Intelligence
• Trustworthy AI
• Machine Learning
• +3 more

Dr. José María Alonso Moral is an Associate Professor at the Department of Electronics and Computation of CiTIUS-USC (Research Center for Intelligent Technologies) at the University of Santiago de Compostela. With a PhD in Telecommunication Engineering from Universidad Politécnica de Madrid (2007) and a 'Doctor Europeus' distinction, he has held prestigious positions including Ramón y Cajal researcher (2018-2022), Juan de la Cierva postdoctoral researcher (2012), and served as President of the European Society for Fuzzy Logic and Technology (EUSFLAT) and Vice-Chair of IEEE Computational Intelligence Society's Explainable Fuzzy Systems Task Force. IEEE Senior Member Associate Editor: IEEE Computational Intelligence Magazine (Q1) and International Journal of Approximate Reasoning (Q2) Board Member: ACL SIGGEN (2019-2022) His research focuses on Explainable AI and Trustworthy Artificial Intelligence , particularly through interpretable fuzzy systems and natural language generation. Key contributions include the ExpliClas web service for decision tree explanations and JFML library for IEEE 1855-2016 fuzzy system modeling. Recent publications examine counterfactual explanations, fuzzy temporal constraint networks, and feature attribution faithfulness metrics. He leads projects like TRUST (Trustworthy AI) and ReproHum (NLP Evaluation Reproducibility), emphasizing human-centered AI design and cross-disciplinary applications in healthcare and education. As an educator, he developed high school workshops on explainable AI fundamentals through CiTIUS-USC's STEM outreach program. His technical work includes developing explainable classifiers for Alzheimer's disease progression and implementing fuzzy logic systems in embedded platforms like Arduino and Raspberry Pi.