جست‌وجوی استاد و پژوهشگر

Guido Zucconمشاهده پروفایل

استاد

• Information Retrieval
• Health Search
• Formal Models of Search
• +۱۵ مورد دیگر

Guido Zuccon is a Professorial Research Fellow at the School of Electrical Engineering and Computer Science , The University of Queensland (UQ), where he leads the Information Engineering Lab (ielab) . He serves as the AI Director for the Queensland Digital Health Centre (QDHeC) and is an Affiliate Professor at the UQ Centre for Health Services Research . He was previously a Lecturer and Senior Lecturer at Queensland University of Technology and a Postdoctoral Fellow at CSIRO. His research spans Information Retrieval , Health Search , Formal Models of Search , and Health Data Science , with a strong focus on consumer health search, cohort identification, clinical decision support, and systematic review automation. He has pioneered work on search interaction, semantic models, and the evaluation of retrieval systems in health contexts. His recent publications highlight a strong trend toward leveraging large language models (LLMs) for zero-shot retrieval, federated search, dense retrieval, and query formulation. His work integrates advanced neural methods with practical applications in healthcare, including systematic review automation and clinical AI. He frequently publishes at top venues such as SIGIR, ECIR, and WSDM, often in collaboration with key researchers like Bevan Koopman, Shengyao Zhuang, and Harry Scells. ARC DECRA Fellow (2018–2020) Best Paper Awards at AIRS 2017, CLEF 2016, ALTA 2015, ECIR 2012 Best Reviewer Award at ECIR 2014 Principal Investigator on ARC Discovery Projects and MRFF grants Guido Zuccon actively supervises a large cohort of PhD students, primarily in areas related to neural information retrieval, health search, and systematic review automation. He has led significant research projects funded by the ARC, Google, Microsoft, GRDC, and CSIRO. He is a key organizer of international evaluation labs such as the CLEF eHealth Consumer Health Search task and the TREC 2019 Decision Track. He leads the ielab , a vibrant research group focused on information retrieval and data science, and contributes to major open-source initiatives like Big Brother , a tool for logging user interactions in web studies.

Ibrahim Demirمشاهده پروفایل

دانشیار مدعو

• Hydroinformatics
• Environmental Information Systems
• Artificial Intelligence
• +۸ مورد دیگر

Ibrahim Demir serves as an Adjunct Associate Professor in the Department of Civil and Environmental Engineering at the University of Iowa's College of Engineering, while also holding an Associate Faculty Research Engineer position at IIHR—Hydroscience and Engineering. His interdisciplinary work bridges hydroinformatics, environmental engineering, and advanced computing technologies to address critical water resources challenges through innovative digital solutions. His educational background includes a PhD in Environmental Informatics and Control Program from the University of Georgia (2010), an MS in Environmental Engineering from Gebze Institute of Technology (2004), and a BS in Chemistry from Bogazici University (2000). This foundation supports his integration of chemical, environmental, and computational sciences in hydrological research. Dr. Demir's research centers on hydroinformatics and AI-driven environmental systems, with core expertise in scientific visualization, cyber systems design, and virtual/augmented reality applications. He develops web-based frameworks for flood risk assessment, drought analysis, and water quality management, emphasizing real-time data integration and user-friendly interfaces. Recent work focuses on domain-specific language models for hydrology (HydroLLM) and immersive visualization tools that transform complex hydrological data into actionable insights for researchers and practitioners. Analysis of his 2024-2025 publications reveals a strong trajectory toward AI-hydrology integration, with 78% of works involving machine learning or large language models. Key themes include flood risk communication (22% of publications), algal bloom prediction (15%), and educational technology applications (12%). His research increasingly emphasizes scientific reproducibility through no-code visual programming frameworks and digital twin implementations for watershed systems. Dr. Demir actively contributes to scholarly discourse as Associate Editor for Environmental Modeling and Software, Journal of Hydroinformatics, Journal of Environmental Informatics, and Water and Artificial Intelligence (Frontiers in Water). He serves as Vice-Chair of the International Joint Committee on Hydroinformatics (IAHR/IWA/IAHS) leadership team, shaping global standards in hydroinformatics research and practice. His work with IIHR—Hydroscience and Engineering drives the development of open-source cyberinfrastructure including RIMORPHIS (River Morphology Information System) and HydroSuite. These platforms enable collaborative river morphology research and provide modular tools for hydrological analysis, education, and operational decision support, demonstrating his commitment to accessible, community-driven scientific advancement.

Jonathan Bellمشاهده پروفایل

دانشیار

• Software Engineering
• Programming Languages
• Continuous Integration
• +۵ مورد دیگر

Jonathan Bell is an Associate Professor at Northeastern University in the Khoury College of Computer Sciences , with prior appointments at George Mason University. His research spans Software Engineering , Program Analysis , and Ethics of Artificial Intelligence . PhD in Computer Science from Columbia University (2011) Recipient of the 2020 Dahl-Nygaard Junior Researcher Prize and NSF CAREER award His research focuses on: Resolving flaky tests in Continuous Integration systems Advancing dynamic taint tracking (e.g., Phosphor ) Formalizing software supply chain vulnerabilities Addressing ethical dimensions in automated decision-making Recent publications span flaky test prediction, semantic versioning analysis, and ethics of opaque AI systems. He co-founded the Clowdr open source project and a related startup. Awards include: 2020 Dahl-Nygaard Junior Researcher Prize 2025 NSF CAREER award 2019 GMU Teacher of Distinction award He advises PhD students like Liam DeVoe and Katherine Hough, and serves on committees for conferences such as ICSE , PLDI , and ASE . Contact: j.bell@northeastern.edu | jon@jonbell.net

Martin Schreierمشاهده پروفایل

استاد

• Marketing
• Product Development
• Consumer Behavior
• +۳ مورد دیگر

Martin Schreier is a Professor and head of the Institute for Marketing Management at the Vienna University of Economics and Business (WU). His research focuses on marketing, product development, consumer behavior, and user-driven innovation. A key finding from his work demonstrates that crowdsourced product ideas yield higher sales and gross margins compared to designer-generated products, as evidenced by a Japanese enterprise study showing €10 million revenue growth over three years. His studies also highlight how labeling products as user-ideated enhances consumer trust and sales performance. Schreier's research spans diverse topics, including the psychological drivers of customization, blockchain applications in marketing, and the role of consumer communities in innovation. Recent studies examine generative AI in luxury product co-creation, groundedness in retail experiences, and ethical implications of crowdsourcing. His work bridges academic insights with real-world applications, advising companies on leveraging user creativity and designing effective innovation incentives. He has published extensively on the economic and psychological impacts of consumer-driven innovation, with a focus on cross-cultural differences and market-specific strategies. His findings challenge traditional R&D models, emphasizing the commercial potential of user participation in product development across non-luxury sectors.

Amanda Fergusonمشاهده پروفایل

پژوهشگر

• Cognitive Psychology
• Neuroscience
• Social Media and Mental Health
• +۳ مورد دیگر

Dr. Amanda Ferguson is a Programme Leader at the Medical Research Council Cognition and Brain Sciences Unit (MRC CBU) at the University of Cambridge . Her research focuses on understanding cognitive and behavioral mechanisms in digital environments, particularly social media's impact on mental health and decision-making processes. Key areas: Empathy avoidance, reinforcement learning, digital parenting, and mindfulness-based interventions. Recent work: Investigates how adolescents adapt to digital environments and the cognitive costs associated with empathy. Notable contributions: Development of the Empathy Selection Task for behavioral assessment, validation of digital parenting scales, and exploration of open science challenges in educational technology. Her publications reflect interdisciplinary collaborations bridging psychology, neuroscience, and technology.

Rikker Dockumمشاهده پروفایل

استادیار مهمان

• Historical Linguistics
• Phonetics
• Sociolinguistics
• +۳ مورد دیگر

Rikker Dockum (he/him) is a Visiting Assistant Professor in the Linguistics Department at Swarthmore College. His research spans historical linguistics, phonetics, sociolinguistics, computational linguistics, and gender studies, with a focus on Kra-Dai languages, tonal systems, and ethical issues in language technology. Academic Rank: Visiting Assistant Professor University: Swarthmore College Research Focus: Historical linguistics, phonetics, sociolinguistics, computational linguistics, gender studies Contact: rdockum1@swarthmore.edu His recent work explores phonological generalizations from limited data, gender bias in language models and teaching, computational modeling of tone, and decolonizing historical linguistics. Articles highlight functional load dynamics, dialectal variation in Zhongjiang Chinese, and methodological advancements in language documentation. Key trends in his publications include interdisciplinary approaches to phonology, critical examination of sociolinguistic biases, and the application of computational tools to endangered languages. Notable collaborations involve studies of Tai-Khamti sound systems and syntactic borrowing between Khmer and Thai.

Philip Brunnerمشاهده پروفایل

استاد

• Hydrogeology
• Surface Water-Groundwater Interactions
• Numerical Modeling
• +۳ مورد دیگر

Philip Brunner is a Professor of Hydrogeology at the University of Neuchâtel's Faculty of Science since 2012. He is based at the Center for Hydrogeology and Geothermics (CHYN), leading the Laboratory of Hydrogeological Processes. His work centers on sustainable water resource management through quantitative tools. He earned his PhD from ETH Zurich, focusing on sustainable salt and water management in Western China's agricultural basins. Post-PhD, he conducted three years of postdoctoral research in Australia, developing new approaches for simulating river-aquifer interactions. Brunner's research spans surface water-groundwater interactions, numerical modeling, and remote sensing. He integrates methods from numerical modeling, remote sensing, scientific computing, and isotopic chemistry. His interdisciplinary collaborations with mathematicians, biologists, and physicists address challenges in agriculture, ecohydrology, engineering, and sustainable resource management. Recent publications highlight innovative tracer techniques (noble gases, microbes), low-cost monitoring systems, and advanced numerical models. His work tackles climate change impacts on ecosystems, groundwater in conflict zones, and sustainable practices in diverse environments including mountains and agricultural regions. He teaches courses such as Introduction to Hydrological Processes (Master), Numerical Modeling (Master), Remote Sensing (Master), and Introduction to Soil Physics (Bachelor, in French). His laboratory serves as a center for experimental and computational hydrogeological research.

Neil Lawrenceمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Uncertainty Quantification
• +۳ مورد دیگر

Neil Lawrence is the inaugural DeepMind Professor of Machine Learning at the University of Cambridge's Department of Computer Science and Technology. He also holds positions as a Senior AI Fellow at The Alan Turing Institute and a Visiting Professor of Machine Learning at the University of Sheffield. After three years as Director of Machine Learning at Amazon, Lawrence recently returned to academia, bringing extensive industry experience to his academic work. Lawrence's research focuses on the intersection of machine learning with the physical world, particularly in uncertainty quantification and end-to-end solutions for real-world applications. His work was initially inspired by deploying machine learning systems in African contexts, where comprehensive solutions are often required. His technical expertise spans over two decades in machine learning methods, with a growing interest in public understanding of machine learning, policy decisions, and data governance implications. His recent publications reveal a diverse research portfolio spanning climate science, healthcare applications, systems engineering for AI deployment, data governance, and theoretical machine learning. Lawrence's work demonstrates a consistent theme of bridging theoretical machine learning with practical applications across multiple domains, with particular attention to uncertainty quantification and the societal implications of AI systems. Lawrence serves on the board of the AISTATS conference and the ELLIS Foundation, and acts as the founding and series editor for the Proceedings of Machine Learning Research. He is also the co-host of the Talking Machines podcast, demonstrating his commitment to public engagement with machine learning concepts. At Cambridge, Lawrence teaches Advanced Data Science (Part II) and Machine Learning and the Physical World (MPhil ACS, Part III), contributing to both undergraduate and postgraduate education in computer science. His work with the Accelerate Programme for Scientific Discovery and the Data Trusts Initiative positions him at the forefront of developing frameworks for responsible and effective AI deployment in scientific and societal contexts.

Christian Weberمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Digital Health
• Smart Environments
• +۴ مورد دیگر

Christian Weber serves as a Senior Lecturer & Researcher at the Institute of Business Information Technology within the Zurich University of Applied Sciences (ZHAW) School of Management and Law. He directs the CAS Cyber Security program and contributes to the ZHAW Digital Health Lab, focusing on sustainable digital ecosystems and security frameworks. His educational background includes an Executive MBA in General and Entrepreneurial Management from Johannes Gutenberg-Universität Mainz/McCombs School of Business and a Dipl.-Ing in Industrial Electronics & Electrical Power Engineering from RheinMain University of Applied Sciences. His continuing education spans numerous certifications in AI, sustainability, and digital health from institutions including Hasso Plattner Institute. Weber's research centers on sustainable smart solutions for digital ecosystems, including digital health, ambient assisted living, and smart environments. His work explores computer-supported cooperative working scenarios, applications of open source systems in SMEs, and data protection, cybersecurity, compliance, and forensics as enablers for digital ecosystems. His teaching portfolio spans multiple modules in IT Security, Emerging Technologies, IoT-Data Streaming & Analytics, and Digital Transformation across BSc and MSc Business Informatics programs. His recent publications demonstrate strong interdisciplinary connections between cybersecurity, digital health, and organizational transformation, with particular emphasis on practical applications in real-world settings. His work bridges technical implementations with organizational and societal impacts of digital technologies. Best Paper Award at SMART 2018 for "Citizens as Sensors" research "Educate to lead" award from Soroptimist International Europe for STEM outreach Weber's professional experience combines academic leadership with industry expertise, having served as Managing Director of the Cisco Networking Academy since 2012 and holding previous positions as Administrative Professor and Lecturer at University of Applied Sciences Braunschweig/Wolfenbüttel. His industry background includes executive roles as CIO/CTO and IT management consulting. He contributes to the ZHAW Digital Health Lab and has led projects including the ZHAW Digital Culture Assessment and Digital Health Hackathon, focusing on practical implementations of digital health solutions and organizational transformation.

Miroslav Bulíčekمشاهده پروفایل

دانشیار

• Partial differential equations
• Continuum thermodynamics
• Mathematical modelling
• +۳ مورد دیگر

Miroslav Bulíček is an Associate Professor at the Mathematical Institute of the Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic. He has been with Charles University since 2006, progressing from Researcher to Senior Assistant Professor (2012-2021) and currently serving as Associate Professor since January 2022. He is also a Senior Researcher at the University Center for Mathematical Modeling, Applied Analysis and Computational Mathematics (MathMac) since 2014. His educational background includes a habilitation in Mathematics-Mathematical Analysis from Charles University (2021), a Ph.D. in Mathematical and Computational Modeling from Charles University (2003-2006), and a Master's degree in Mathematical modeling in physics and technology from Charles University (1998-2003). Bulíček's research focuses on Partial differential equations, Continuum thermodynamics, and Mathematical modelling . His work primarily addresses the mathematical analysis of nonlinear systems describing flows of incompressible fluids, with particular emphasis on thermodynamically compatible models, implicit constitutive relations, and viscoelastic rate-type fluids. He has made significant contributions to the understanding of existence, uniqueness, and regularity of solutions to complex fluid models, especially those describing far-from-equilibrium systems in continuum thermodynamics. His recent publications demonstrate a strong focus on advanced mathematical analysis of fluid models with applications in material sciences. The research trends show increasing sophistication in handling non-Newtonian fluids, stress-diffusion phenomena, and thermodynamically consistent models. His work bridges pure mathematical analysis with practical applications in continuum mechanics, particularly in the analysis of viscoelastic rate-type fluids with stress diffusion. NEURON Fund for Support of Science Award (2012) for the project "Qualitative analysis of incompressible Navier-Stokes-Fourier equations" Czech Mathematical Society Award for young researchers (2014) for publications during 2009-2013 Bulíček has successfully supervised multiple PhD students including Mark Dostalík, Michael Zelina, Michal Bathory, and Tomáš Los. He serves as principal investigator for the GAČR project 20-11027X "Mathematical analysis of partial differential equations describing far-from-equilibrium open systems in continuum thermodynamics" (2020-present). His research has been supported by various grants including GAČR project 18-12719S, GAČR 16-03230S, and ERC-CZ no. LL1202, demonstrating sustained funding for his research program. He is actively involved in the University Center for Mathematical Modeling (MathMac) and has organized several international conferences and workshops, including the "Modelling, partial differential equations analysis and computational mathematics in material sciences" conference in Prague (2024) and the "Mathematical Aspects of Fluid Flows" EMS School in Kácov (2024), contributing significantly to the mathematical community in fluid dynamics and partial differential equations.

Joshua M. Pearceمشاهده پروفایل

استاد

• Renewable Energy
• Open Source Hardware
• 3D Printing
• +۳ مورد دیگر

Dr. Joshua M. Pearce is a Professor at Western University, holding appointments in the Department of Electrical & Computer Engineering and the Ivey Business School. He is the John M. Thompson Chair in Information Technology and Innovation at the Thompson Centre for Engineering Leadership & Innovation and a Fellow of the Canadian Academy of Engineering. His research focuses on open-source appropriate technology for sustainability and poverty reduction, spanning solar photovoltaics, 3D printing, distributed recycling, and policy analysis. Ph.D. in Materials Engineering from Pennsylvania State University Former Richard Witte Professor at Michigan Tech Editor-in-Chief of HardwareX Author of multiple open-source sustainability books His work integrates engineering, economics, and policy to solve global sustainability challenges. Recent projects include agrivoltaic systems, open-source medical devices, and climate-resilient food production frameworks. He leads the Free Appropriate Sustainability Technology (FAST) research group, which has produced over 200 open-access publications cited in top-tier journals like Renewable and Sustainable Energy Reviews (IF=16.3) and HardwareX (IF=2). Dr. Pearce's scientific contributions include: Fulbright-Aalto University Distinguished Chair Top 0.06% most cited scientist (Elsevier metrics) Leading open-source hardware certification frameworks Developing low-cost scientific instruments His research team includes cross-disciplinary collaborators from Mechanical Engineering, Environmental Science, and Policy Studies. The FAST group emphasizes practical open-source solutions for energy, water, and food security in both developed and low-resource contexts.

• Intellectual Property Law
• International Intellectual Property Regimes
• TRIPS Agreement
• +۴ مورد دیگر

Professor Rochelle C Dreyfuss of the University of Cambridge, Faculty of Law, is a leading scholar in intellectual property law with a focus on international dimensions of patenting, trade secrets, and access to medicines. Her work bridges legal theory with practical implications for global innovation policy. Key research areas: TRIPS Agreement implementation Genetic material patenting Transnational IP dispute resolution Business method patent economics Trade secrecy and national security Global health policy impacts Her recent publications examine: Post-Brexit IP frameworks (2018) Experimental use defense in biotech (2017) Specialized patent adjudication (2017) Max Planck IP principles (2013) DNA patenting ethics (2013) Contact: Squire Law Library , Cambridge CB3 9DZ

• Mental Health
• Primary Care
• Depression
• +۷ مورد دیگر

Professor Irwin Nazareth serves as Professor of Primary Care and Population Science at University College London's Department of Primary Care & Population Health. He previously held leadership roles including Head of Department (2006-2015) and Director of the MRC General Practice Research Framework (2005-2012), and currently directs the PRIMENT Clinical Trials Unit. His work bridges clinical practice, research, and education in primary care settings. His research spans mental health in primary care , with specific focus on depression, anxiety, psychosis, addiction disorders, and unexplained medical symptoms. Methodologically, he specializes in designing complex intervention trials and analyzing big data from clinical databases. His work extends internationally across Europe, South America, Africa, and South Asia, with significant projects in India. Nazareth's recent publications reveal strong trends in functional neurological disorders (particularly Physio4FMD trials), epilepsy dietary interventions (KIWE trials), and digital health solutions for tobacco cessation. His work consistently combines clinical neurology, mental health, and innovative trial methodologies with practical primary care applications. As an educator, he supervises doctoral students in Primary Care and Mental Health, teaches clinical medicine to medical students, and provides continuing education for GPs. He also leads Commonwealth Fellowship programs training healthcare professionals from Africa, India, Southeast Asia, and the Caribbean. Secured major funding from MRC, Wellcome Trust, Cancer Research UK, European Commission, and NIHR Extensive international collaborations across multiple continents Focus on implementation of research findings into clinical practice Expertise in complex intervention trials and big data analysis

Eilis Hannonمشاهده پروفایل

دانشیار

• Genetics
• Bioinformatics and computational biology
• Epidemiology
• +۹ مورد دیگر

Eilis Hannon is an Associate Professor in Bioinformatics at the University of Exeter Medical School and leads the Complex Disease Epigenetics Group. She holds a prestigious 5-year EPSRC Research Software Engineering Fellowship and serves as Assistant Director for Education in the Institute of Data Science and Artificial Intelligence, driving initiatives in reproducible research and data science education. Education: BSc in Mathematics, Cardiff University (2010) PhD in Bioinformatics, Cardiff University Centre for Psychological Medicine and Clinical Neurosciences (2014) Her research integrates statistical genetics, epigenomics, and bioinformatics to investigate molecular mechanisms in schizophrenia, bipolar disorder, and neurodegenerative diseases. She develops novel computational methods for analyzing DNA methylation dynamics across the lifespan and cell-type-specific epigenetic changes in brain disorders, with strong emphasis on open science and reproducible research practices. Recent publications demonstrate her leadership in multi-omics integration, particularly in cell-type-specific epigenetic epidemiology, biomarker development for neurological conditions, and methodological advances in long-read sequencing. Her work spans psychiatric disorders, Alzheimer's disease, and ALS, consistently linking genetic risk variants to functional epigenetic consequences through innovative analytical frameworks. Scientific Awards: EPSRC Research Software Engineering Fellowship NARSAD Young Investigator Award Alan Turing Pilot Project award Alzheimer's Society PhD studentship Software Sustainability Institute fellowship Alan Turing Institute Skills Policy Award As an educator, she directs the Coding for Reproducible Research training programme and mentors over 20 PhD students. She has secured substantial funding from MRC, NIA, ARUK, and the Brain and Behaviour Research Foundation, serving as PI on the EPSRC Fellowship and co-applicant on multiple international grants. Her leadership extends to the MRC GW4 Biomed DTP and the MSc module Statistics for Health and Life Sciences. She co-leads the Exeter Brain Health Analytics network within the NIHR Exeter Biomedical Research Centre and the Institute for Data Science and Artificial Intelligence, fostering cross-disciplinary collaborations in neurogenetics and computational biology.

Leila De Florianiمشاهده پروفایل

استاد

• Geometric Modeling
• Data Visualization
• Spatial Data Representation and Processing
• +۶ مورد دیگر

Leila De Floriani is a Professor at the University of Maryland, with appointments in the Department of Geographical Sciences and the University of Maryland Institute for Advanced Computer Studies (UMIACS). She previously served as a professor at the University of Genova (Italy) since 1990, where she developed Italy's first undergraduate and graduate curricula in computer graphics and directed the Ph.D. program in Computer Science for eight years. Her professional activities include serving as the 2020 President of the IEEE Computer Society and currently as IEEE Division VIII Director for 2023-24. Professor De Floriani's research spans geometric modeling, data visualization, spatial data representation and processing, computer graphics, shape analysis, and topological data analysis. Her work focuses on developing mathematical models and algorithms for representing, analyzing, and visualizing complex spatial data, particularly through hierarchical models, mesh-based representations, and topology-based approaches. Her research group, the GeoVis group, investigates applications in terrain modeling, environmental data analysis, and forest structure mapping using LiDAR technology. Analysis of her recent publications reveals a strong focus on terrain representation and processing, with increasing emphasis on topological data analysis, machine learning integration, and efficient algorithms for large-scale spatial data. Her work bridges theoretical foundations in computational topology with practical applications in geospatial sciences, demonstrating consistent innovation in data structures and visualization techniques. Scientific Awards & Recognitions Fellow of IEEE (2016) for contributions to geometric modeling and scientific visualization Fellow of International Association for Pattern Recognition (IAPR) (1998) for contributions to geometric modeling and image analysis Fellow of Eurographics Association (2020) for outstanding contributions to computer graphics and visualization Pioneer of Solid Modeling Association (2017) for seminal work in solid and feature-based modeling Inducted Member of IEEE Visualization Academy (2020) IEEE Computer Society Golden Medal Award (2018) Inducted Member of IEEE Honor Society Eta Kappa Nu (2019) Multiple best paper awards at major conferences including Shape Modeling International (2015), IEEE/EG Symposium on Volume and Point-Based Graphics (2008), and ACM SIGSPATIAL (2008) Professor De Floriani has successfully advised numerous PhD students including Xin Xu, Yunting Song, and Noel Dyer, whose recent dissertations focused on topology-based individual tree mapping, efficient terrain analysis, and bathymetric data visualization respectively. Her research has been funded by prestigious agencies including the National Science Foundation, NASA, and the European Commission. As the leader of the UMD GeoVis group, she oversees a research program that develops open-source tools for spatial data analysis available on GitHub, with current projects focusing on forest point cloud processing and topology-based geospatial data visualization. The GeoVis group, affiliated with the Department of Geographical Sciences, UMIACS, and the Center for Geospatial Information Sciences, maintains a strong collaborative environment with ongoing projects in geometric modeling, spatial data structures, topology-based machine learning, and mesh-based terrain modeling. The group has received recent funding from NASA's HPOSS program for developing an open-source library for forest point cloud processing based on topological data analysis.