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Nils GehlenborgView profile

Associate Professor

• Biomedical Informatics
• Data Visualization
• Genomics
• +3 more

Nils Gehlenborg is an Associate Professor of Biomedical Informatics at Harvard Medical School and Director of the Master of Medical Sciences in Biomedical Informatics (MMSc-BMI) program. His research focuses on developing computational methods and visualization tools for biomedical data analysis, with applications in cancer genomics and precision medicine. Education : PhD from the University of Cambridge, with predoctoral training at the European Bioinformatics Institute (EMBL-EBI). Research Interests : Integration of algorithmic approaches with advanced data visualization techniques to support sense-making in biology. Key areas include tools for large-scale cancer genomics (e.g., The Cancer Genome Atlas), reproducible research in epigenomics, and collaborative software development. He co-founded BioVis and VIZBI , leading initiatives to advance biological data visualization standards and practices. Grants & Funding : NIH Community Data Hub for Integrative Visualization (U24OD038421) NIH Grammar-Driven Genomic Data Visualization (R01HG011773) NIH Integrative Visualization of Spatiotemporal Tumor Atlases (R33CA263666) Labs & Teams : Leads the Gehlenborg Lab and contributes to projects like the Caleydo visualization framework and the HuBMAP consortium.

Rob WorleyView profile

Research Fellow

• Robotics
• Autonomous Systems
• Sensor Networks
• +3 more

Dr. Rob Worley is a Research Fellow at the University of Sheffield’s School of Electrical and Electronic Engineering since 2022, following his PhD studies initiated in 2018. His research focuses on robot navigation and localization within buried pipe networks, with a particular emphasis on acoustic and visual sensing technologies. He leads the Pipebot Patrol project, advancing autonomous inspection systems for water and sewer infrastructure. His work integrates state estimation, artificial intelligence, and robotics to address challenges in feature-sparse underground environments. Worley’s research interests span robot localization algorithms, SLAM (Simultaneous Localization and Mapping), and sensor fusion, with applications to cylindrical pipe networks. His projects leverage cylindrical regularity and hybrid metric-topological models to enhance navigation accuracy. Notable contributions include acoustic echo localization using microphone arrays and visual SLAM techniques for sewer networks. He has published extensively on topics like error detection in particle filters and condition monitoring in underground pipes. Advising and grants: While no specific advisees are listed, his projects likely involve collaborative research teams. He has contributed to the Pipebots initiative since its inception, focusing on localization and sensing advancements. Labs/Teams: Active member of the University of Sheffield’s robotics research group, contributing to the development of autonomous inspection technologies for infrastructure maintenance.

• High Performance Computing
• Parallel Computing
• Computer Architecture
• +3 more

Wolfgang E. Nagel is a Professor of Computer Science and Director of the Center for Information Services and High-Performance Computing (ZIH) at Technische Universität Dresden. Since 2001, he has held the Chair for Computer Architecture, leading research in parallel computing and high-performance systems. Previously, he served as Dean of the Computer Science Department (2006–2009) and Director of the High-Performance Computing Center (ZHR) at TU Dresden (1997–2005). His professional experience includes roles at the Research Center Jülich and the California Institute of Technology (CACR). Education : 1985: Diplom-Informatics in Computer Science, RWTH Aachen 1993: Dr. rer. nat. in Computer Science, RWTH Aachen Research Focus : Nagel’s work centers on high-performance computing (HPC), parallel system architectures, and performance analysis tools like VAMPIR. He has contributed to exascale computing roadmaps, cache architecture studies, and scalable application development frameworks. His interdisciplinary projects span computational biology (e.g., endocytosis modeling) and physics simulations. Leadership Roles : Chair of Gauss-Allianz e.V. (since 2008) Member of DFG Commission for Computer Infrastructure (2005–2012) Advisory Board roles for HLRS Stuttgart and FIZ Karlsruhe Grants & Collaboration : His leadership in ZIH and ZHR has driven infrastructure development for German HPC networks. He coordinates national and international initiatives in computational infrastructure and education. Labs/Teams : Directs ZIH, a central hub for Dresden’s HPC services, supporting research across engineering and natural sciences.

Nori JacobyView profile

Assistant Professor

• Cognitive Science
• Computational Neuroscience
• Music Cognition
• +3 more

Nori Jacoby is an Assistant Professor in the Department of Psychology at Cornell University and a Research Group Leader at the Max Planck Institute for Empirical Aesthetics in Frankfurt. His research examines how internal representations shape sensory and cognitive abilities through computational approaches, cross-cultural studies, and large-scale behavioral experiments. Ph.D. from Hebrew University of Jerusalem (Edmond and Lily Safra Center for Brain Sciences) Postdoctoral training at MIT, UC Berkeley, and Columbia University Research areas include: Computational modeling of human perception Cross-cultural analysis of musical cognition Collective behavior in social networks Recent publications focus on: Global rhythm perception patterns Machine learning alignment with human cognition Oral transmission mechanisms in music evolution Scientific awards: NSF grant for collaborative creativity research Presidential Scholar in Society and Neuroscience Lab: Cornell Computational Cognition (CoCoCo) Lab

Chaoqun NiView profile

Assistant Professor

• Science of Science
• Science Policy
• Scholarly Data Analytics
• +3 more

Chaoqun Ni is an Assistant Professor at the Information School (iSchool) at the University of Wisconsin-Madison and co-director of the Metascience Research Lab. She is affiliated with the Data Science Institute, Holtz Center for Science & Technology Studies, and the Center for Demography of Health and Aging (CDHA). Her research focuses on the Science of Science, Science Policy, and Scholarly Data Analytics, using large-scale data to inform science policy and understand academic practices. She holds a Ph.D. in Information Science (minor in Statistics) from Indiana University Bloomington, and M.S. and B.S. degrees in Information Systems from Wuhan University. Her work examines gender disparities in academia, academic workforce dynamics, and interdisciplinary research barriers. She teaches courses in database management, data visualization, and research methods. Ni recently secured an NSF grant to study HBCU faculty mobility and retention and mentors Ph.D. students interested in metascience, science policy, and data science. Her lab, the Metascience Research Lab, explores transformative questions about the scientific enterprise and its societal impacts. Key research themes include peer review systems, academic career trajectories, and the role of parenthood in gender gaps in academia. Her interdisciplinary approach combines bibliometrics, statistical analysis, and computational methods to address challenges in science policy and scholarly communication.

• Database Management
• Transaction Management
• Replication
• +4 more

Alan Fekete is a Professor of Enterprise Software Systems in the School of Computer Science at the University of Sydney. He holds a BSc (Hons) from the University of Sydney and a PhD from Harvard University's mathematics department. With over 30 years at the University of Sydney, he has made significant contributions to database systems, distributed computing, and computing education. His research focuses on improving software systems' state-of-practice, particularly in transaction management, replication, and cloud computing. Education background: BSc(Hons) from the University of Sydney, PhD in Mathematics from Harvard University. Research interests include database management (transaction systems, replication), cloud computing, distributed systems, software engineering, and computing education. His teaching spans enterprise software architecture, data models, and systems analysis. He has supervised 13 doctoral students and contributed to curriculum development, notably in Java programming and cloud workforce training. Recent publications explore transactional frameworks, database benchmarking, and concurrency control. He is a Distinguished Scientist of ACM and a member of IEEE and Australian Computer Society. His work on robust rolling-upgrades and cloud storage benchmarking addresses modern system challenges. Fekete's teaching innovations include data-centric curricula and frameworks for self-assessment in programming education.

Laura I. TomaView profile

Professor

• Computer Science
• Geographic Information Systems (GIS)
• Algorithms
• +4 more

Laura I. Toma is a Professor of Computer Science at Bowdoin College. Her research focuses on cache-efficient algorithms for large geospatial data, particularly applications in GIS such as terrain analysis, visibility, flooding, and least-cost-path surfaces. She emphasizes resource-efficient approaches backed by theoretical guarantees and practical implementation, with a goal of contributing to open-source GIS software. Education: PhD (2003), MS (2001) from Duke University; BS & MS (1997) from University Politehnica of Bucharest, Romania. Affiliations: Department of Computer Science, Bowdoin College; previously supported by NSF Award 0728780 (2007–2013). Teaching: Courses include Algorithms, GIS Algorithms, Data Structures, and High-Performance Computing. Research Interests: Computational geometry, I/O-efficient algorithms, parallel computing, geospatial data processing, and algorithm optimization. Her work bridges theory and practice, addressing challenges in massive terrain datasets. Key Contributions: Developed algorithms for viewshed computation (SIGSPATIAL 2018), Terracost for least-cost paths (ACM GIS 2006), and I/O-efficient flow modeling (GeoInformatica 2003). Awards: NSF funding (2007–2013), Best Paper Award at ACM SIGSPATIAL GIS 2009 (collaborative work). Students: Advised over 20 graduate and undergraduate researchers, including honors theses on viewsheds, grid simplification, and algorithmic self-efficacy studies. Labs/Teams: Collaborates on Bowdoin's High-Performance Computing (HPC) initiatives and contributes to open-source GIS projects like GRASS.

Marc VeletzosView profile

Professor

• Earthquake Engineering
• Bridge Engineering
• Disaster Recovery
• +4 more

Marc Veletzos is a Professor of Civil Engineering at Merrimack College, specializing in earthquake engineering, disaster recovery, and resilient infrastructure design. He holds additional roles as a Fulbright Senior Scholar (Nepal, 2018), Director-at-Large of the Earthquake Engineering Research Institute’s New England Chapter, and Structures Specialist with FEMA’s Massachusetts Task Force 1. Veletzos earned his Ph.D., M.S., and B.S. in Structural Engineering from the University of California, San Diego. His research focuses on three core areas: 1) improving bridge resilience in extreme events through emergency response planning and rapid restoration techniques, 2) developing earthquake-resistant designs for vernacular buildings in developing countries (e.g., Nepal), and 3) advancing understanding of seismic behavior in segmental bridges through large-scale testing and simulations. His work is supported by organizations like Caltrans and the National Cooperative Highway Research Program (NCHRP). His publications highlight contributions to bridge assessment guidelines, smart app development for emergency situations, and innovative seismic retrofitting methods. Recent work emphasizes global collaboration, including workshops in Hawaii and Nepal to transfer knowledge to local communities. He has also pioneered service-learning initiatives linking academic programs with real-world disaster response efforts. Awards: BSCES College Educator of the Year (2023) McKniff Service Award (2017) ExCEEd Teaching Fellow (2009) James Cooper Best Paper Award (2008) Grants & Partnerships: NCHRP, Caltrans, U.S. Education Foundation/Nepal, FEMA Veletzos leads Merrimack College’s efforts in STEM education innovation, integrating national best practices into a liberal arts environment to enhance student retention and engagement. His work bridges academic research, community service, and policy development to create sustainable solutions for global challenges.

Clinton L. JefferyView profile

Professor

• programming languages
• program execution monitoring
• automatic debugging
• +2 more

Clinton L. Jeffery is a Professor and Chair in the Department of Computer Science at New Mexico Institute of Mining and Technology. He holds a B.S. (1987), M.S. (1989), and Ph.D. (1993) in Computer Science from the University of Washington and University of Arizona. His research spans programming languages, program execution monitoring, and software visualization. Key research areas : Design and implementation of programming languages (Unicon, Godiva) Program execution monitoring and debugging (Alamo, UFO) Collaborative virtual environments and MMO-style games Visualization of dynamic program behavior Publication trends focus on programming language design, debugging methodologies, and software visualization. His 2021 book Build Your Own Programming Language emphasizes language development, while earlier works explore runtime verification, thread models, and graphical programming. Professional roles : General Chair, AADEBUG 2005 Co-Chair, FLOSS mini-tracks at HICSS (2010-2014) Program Committee Member for ACM SAC, SEKE, and ICICS Reviewer for journals and NSF panels Campus Liaison, USENIX Association

• Data Engineering
• Data Mining
• Data Visualization
• +7 more

Musa Jafar is an Associate Professor of Business Analytics & CIS in the School of Business at Manhattan College, where he has been since August 2014. He holds a Ph.D. in Systems Engineering from the University of Arizona, along with multiple Master's degrees in Management Information Systems, Systems Engineering, and Mathematics from the University of Arizona and American University of Beirut. His teaching focuses on Data Mining, Data Visualization, Database Management Systems, and OpenSource Web Development. His research interests center on data engineering, visual analytics, and developing tools for non-algorithmic programmers to analyze digital humanities data. He has held previous academic positions at West Texas A&M University (as Phil Gensler Professorship holder), the University of Arizona, and Washington State University. His professional experience includes roles as a Senior Software Engineer at IBM and Bell Communications Research. Key awards include the 2017 Tate Award Finalist (NACRA), 2016 Distinguished Paper Award (CONISAR), and the 1996 President's Club Performance Award (US West Communication). His work emphasizes tool development for data analytics, curriculum innovation, and social media analysis. He actively participates in academic conferences, delivering workshops on topics like HTML5/WebGL visualization, R-based data analytics, and SQL Server BI tools. No specific grants are highlighted in the text, but his professorships and awards reflect sustained academic contribution.

Jan LorenzView profile

Assistant Professor

• Computational Social Science
• Social Data Science
• Opinion Dynamics
• +9 more

Jan Lorenz is an Assistant Professor of Social Data Science at the School of Business, Social & Decision Sciences, Constructor University Bremen. His research focuses on computational social science and agent-based modeling, addressing socio-economic systems, opinion dynamics, segregation, and collective decision-making processes. Dr. Lorenz earned a Diploma in Mathematics from the University of Bremen in 2003 and a PhD in Mathematics in 2007, both from the University of Bremen. He habilitated in Computational Social Science at Jacobs University Bremen in 2017. His research interests include data-driven agent-based modeling, social cohesion, opinion formation, polarization, and segregation processes. He employs tools such as large-scale data analysis, experiments, and mathematical modeling, focusing on topics like voting systems, consensus algorithms, and systemic risk. His work intersects mathematics, computational methods, and social sciences, with a focus on complex systems and network analysis. Recent publications explore theoretical and empirical applications of agent-based modeling, including calibrating opinion dynamics models and analyzing ethnic segregation patterns in urban areas. He also investigates the impact of transparency on voting behavior and the dynamics of social cohesion across societies. In addition to his research, Dr. Lorenz teaches in the Master's program in Data Science for Society and Business, focusing on data visualization and computational social science. He has organized multiple summer schools on topics like computational social science of conflicts, migration, and social cohesion, fostering interdisciplinary collaboration among researchers.

Sampath JayarathnaView profile

Associate Professor

• Neuro-Information Retrieval
• Data Science
• Human-Computer Interaction
• +5 more

Sampath Jayarathna is an Associate Professor in the Department of Computer Science at Old Dominion University, part of the College of Science. His research focuses on Neuro-Information Retrieval, Data Science, and Human-Computer Interaction, with a particular emphasis on eye tracking, biometrics, and wearable devices. He holds a Ph.D. from Texas A&M University and has been at ODU since 2018. Jayarathna has received multiple accolades, including the NSF CAREER Award in 2021 and the ODUAA New Faculty Award. His work bridges disciplines, applying computational techniques to understand user behavior and develop adaptive interfaces for accessibility. Education: Ph.D. in Computer Science (Texas A&M University, 2016), M.S. (Texas State University, 2010), B.S. (University of Peradeniya, Sri Lanka, 2006). Prior to ODU, he was on the faculty at Cal Poly Pomona. Research Interests: Neuro-Information Retrieval (eye tracking, EEG, oculomotor systems), Data Science (multi-modal sensing, user interest modeling), Human-Computer Interaction (recommender systems, accessibility for visually impaired users). His lab develops tools like the Neuro Information Retrieval and Data Science Lab, supported by grants such as NSF CAREER and COVA-CCI. His recent work includes enhancing accessibility for blind users in e-commerce and data visualization, detecting deceptive web advertisements, and real-time cognitive load analysis via pupillary metrics. He has authored over 50 publications in top-tier venues like IEEE Transactions and ACM conferences. Awards include the 2025 COS Outreach Award, 2023 NSF S&CC-PG grant, and the 2021 Provost's Award for Mentoring. He advises numerous students, with a focus on inclusive technologies and interdisciplinary research. Labs/Teams: Leads the Neuro Information Retrieval and Data Science Lab, collaborating on projects like distributed eye-tracking systems (DisETrac) and gaze analytics dashboards. Active in grants involving disinformation detection and secure IoT applications.

• Computer Networking
• Wireless Communications
• Network Virtualization
• +5 more

Thierry Turletti is a Professor at INRIA with extensive research in computer networking, wireless communications, and network virtualization. His work focuses on network emulation, software-defined networking, 5G networks, and content-centric networking with numerous publications spanning over two decades. His primary research interests include developing advanced network emulation frameworks that maintain high fidelity in distributed environments, optimizing wireless network performance through innovative ray tracing techniques, and creating robust programmable networks with optimal failure recovery. His work bridges theoretical networking concepts with practical implementations, particularly in the areas of mobile edge computing and 5G network optimization. Recent publications demonstrate a clear trend toward solving practical networking challenges in large-scale distributed environments, with emphasis on network emulation fidelity, wireless signal propagation modeling, and network function placement. His research spans broad disciplines including computer networking, telecommunications engineering, and distributed systems, with specific focus on radio frequency mapping, network monitoring, and mobile network optimization. Dr. Turletti has been instrumental in developing network experimentation frameworks and tools that enable researchers to conduct realistic network testing in controlled environments. His work on Distrinet and Sophia-node represents significant contributions to the field of network testbeds and emulation platforms.

• Medical Education
• Simulation-Based Education
• Interprofessional Simulation
• +5 more

Dawn Taylor Peterson is an Associate Professor at the Heersink School of Medicine, Department of Medical Education, and holds joint appointments in the School of Health Professions (Department of Health Services Administration) and the School of Nursing (Nursing Academic Support) at The University of Alabama at Birmingham (UAB). She also serves as Director of the Office of Interprofessional Simulation for Innovative Clinical Practice under the Office of the Provost. Dr. Peterson holds a PhD in Instructional Design, an Educational Specialist degree, and a Master of Arts in Education. She is a certified TeamSTEPPS® Master Trainer and has over 25 years of experience in education, including 12 years specializing in simulation-based learning. Her research focuses on debriefing methods, interprofessional simulation, and faculty development in healthcare education. Notable projects include developing simulation models for medical students (e.g., the Simulation Teaching Associate program) and implementing large-scale interprofessional poverty simulations to address healthcare disparities. She has pioneered approaches like Rapid Cycle Deliberate Practice (RCDP) for advanced life support training and led studies on simulation-enhanced interprofessional education outcomes. Dr. Peterson’s work spans diverse healthcare disciplines, with recent publications exploring trends in simulation scholarship through text mining and evaluating the impact of simulation on learner perceptions of critical topics like acute radiation syndrome and poverty’s health effects. Her teaching includes courses on simulation design, methodology, and quality improvement in healthcare. Professional Activities: Member of the Healthcare Educators Academy (2019–present). Grants & Leadership: Directed UAB’s Office of Interprofessional Simulation since 2022, overseeing initiatives to integrate simulation across health professions training. Labs/Teams: Leads the Office of Interprofessional Simulation, which coordinates interprofessional activities across UAB’s health sciences schools.

Guy MeadowsView profile

Research Professor

• Geophysical Fluid Dynamics
• Environmental Forecasting
• Hydrodynamics
• +3 more

Guy Meadows is an Emeritus Director and Research Fellow at the Great Lakes Research Center (GLRC) and holds the rank of Research Professor in Mechanical Engineering-Engineering Mechanics (MAE) at Michigan Technological University. He also serves as an Adjunct Professor in Geological and Mining Engineering and Sciences (GMES). His career spans over three decades, including 35 years at the University of Michigan, where he held leadership roles such as Director of the Ocean Engineering Laboratory and the Marine Hydrodynamics Laboratories. He joined Michigan Tech in 2012 to establish the GLRC, focusing on integrating scientific understanding with engineering solutions for marine environments. Education: PhD in Marine Science, Purdue University, 1977 MSE in Mechanical Engineering, Michigan State University, 1974 BSE in Mechanical Engineering, Michigan State University, 1972 Research Interests: Meadows specializes in geophysical fluid dynamics, environmental forecasting, and experimental hydrodynamics in the Great Lakes and coastal oceans. His work emphasizes large-scale field experimentation, autonomous monitoring platforms, and underwater acoustic remote sensing. He has contributed to policy development for coastal management and climate change adaptation. Publications: His most recent articles focus on freshwater radar applications, autonomous surface vessels, and glacial-hydrological interactions. These reflect his dual emphasis on technological innovation and environmental science. Advising & Grants: As a leader in interdisciplinary initiatives, Meadows has directed institutes like the M-STEM Academy and collaborated on federal research programs. His work often involves partnerships with NOAA and other agencies. Labs & Teams: He leads the GLRC, a hub for interdisciplinary marine research, and develops advanced technologies like the BathyBoat autonomous vessel for environmental monitoring.