Dr. Patrick Filippi is a Lecturer in Precision Crop Management at the School of Life and Environmental Sciences, University of Sydney. He is affiliated with the Precision Agriculture Laboratory and the Sydney Institute of Agriculture. His work focuses on integrating remote sensing, machine learning, and geostatistics to address challenges in precision agriculture, particularly in crop yield modeling, soil mapping, and environmental monitoring. Research interests include precision agriculture technologies, soil science applications, data-driven crop management, and the use of satellite and proximal sensing for agricultural decision-making. He has contributed to projects funded by the Grains Research and Development Corporation (GRDC) and the University of Sydney, focusing on spatial variability in crop production, soil constraints, and machine learning interpretability. Key achievements include developing the LimeSoDa dataset for soil mapping and winning the 2016 CSIRO AgData Challenge Hackathon. His grants span topics like nitrogen fixation mapping in legumes and frost/heat management analytics. Filippi collaborates closely with industry to translate research into practical tools for farmers. Awards: 2nd Place CSIRO AgData Challenge Hackathon (2016) Labs: Precision Agriculture Laboratory (https://precision-agriculture.sydney.edu.au/) Grants: Includes Strategic Partnership Seeding Grants (2024), GRDC-funded projects (2022–2024), and Start-Up Research Funding (2024).
Steven P. French is a Professor of City & Regional Planning at Georgia Institute of Technology, affiliated with the College of Design. He has held leadership roles including Dean of the College of Design (2013–2021), Associate Dean for Research (2009–2013), and Director of the Center for Geographic Information Systems (1997–2011). His expertise spans natural hazards, sustainable development, land use planning, and GIS applications. French earned his Ph.D. in City & Regional Planning from the University of North Carolina at Chapel Hill and previously taught at California Polytechnic State University and Stanford University as a Visiting Professor. His research focuses on disaster resilience, urban sustainability, and infrastructure systems integration. He has advised over 50 Master’s students and graduated six Ph.D. students, with notable contributions to planning education and disaster risk assessment. French has led over 70 research projects, including NSF-funded studies on earthquake and flood hazards, and served as Social Science Thrust Leader for the Mid-America Earthquake Center. He is a Fellow of the American Institute of Certified Planners (FAICP). French’s work bridges interdisciplinary collaboration between planners, engineers, and scientists. His recent projects emphasize leveraging big data and GIS for urban decision-making, sustainable infrastructure design, and analyzing urban health impacts. He has authored/co-authored over 25 journal articles and four books, contributing to journals like the Journal of the American Planning Association.
Shan Yu is an Assistant Professor in the Department of Statistics at the University of Virginia. His research focuses on developing statistical and machine learning methods for large-scale, complex data, with applications in neuroimaging, genomics, spatial epidemiology, and health disparities. He employs advanced techniques including non/semi-parametric regression, functional data analysis, and distributed learning while emphasizing data privacy. Yu received his Ph.D. in Statistics from Iowa State University (2020), advised by Professors Lily Wang and Dan Nettleton, following a B.S. from the University of Science and Technology of China. His work bridges statistical methodology and real-world problems, addressing challenges in environmental science (e.g., nitrogen dioxide inequalities), public health (e.g., pandemic forecasting), and computational biology (e.g., genotype-environment interactions). He collaborates on tools like the GgAM R package for generalized geoadditive models and contributes to open-source projects such as fFLM for functional linear regression. Key research trends include spatially varying coefficient models, fusion learning for heterogeneous data, and integration of satellite data with environmental health studies. His publications span journals in statistics, epidemiology, and environmental science, reflecting interdisciplinary impact.
Douglas H Fisher is an Associate Professor of Computer Science and Computer Engineering at Vanderbilt University's School of Engineering. His research focuses on artificial intelligence, particularly machine learning, and computational sustainability. He holds a Ph.D., M.S., and B.S. in Computer Science from the University of California - Irvine. His work bridges AI with societal challenges, emphasizing sustainability, education technology, and cognitive modeling. Notable areas include integrating sustainability into computing curricula, leveraging AI for peer review systems (pReview), and exploring bias mitigation in neural networks. He has contributed to foundational machine learning techniques, such as rule induction for medical data analysis and decision tree optimization. Fisher's research spans interdisciplinary applications: from geospatial water resource modeling to MOOCs' social incentives. His educational contributions include blended learning frameworks and open educational resources advocacy. He has authored over 100 publications across AI, sustainability, and education, reflecting a commitment to both technical innovation and societal impact.
Stephen Lee is an Assistant Professor in the Department of Computer Science at the University of Pittsburgh, affiliated with Pitt Cyber. His research focuses on distributed systems, cyber-physical systems, and sustainability, emphasizing energy efficiency and cost optimization. Dr. Lee holds a PhD from the University of Massachusetts Amherst, a Master’s from Chennai Mathematical Institute, and a Bachelor’s from St. Stephen’s College, Delhi. He actively seeks students for his research group. Education: PhD, Computer Science, University of Massachusetts Amherst Master’s, Chennai Mathematical Institute Bachelor’s, St. Stephen’s College, Delhi Research Interests: Dr. Lee’s work integrates distributed systems, machine learning, and optimization to enhance sustainability. Key areas include IoT-enabled energy systems, emission-aware computing, and privacy-preserving frameworks. He leads projects like GreenWhisk (serverless emission reduction) and Sat2map (3D building modeling from satellite imagery). Recent Achievements: Best Paper Award in IEEE TPS 2024 DOE-funded Cyber Energy Center (2024) MCSI Seed Grant for Pitt building sustainability (2024) NSF Grant on sustainable distributed infrastructures (2023) Grants & Advising: Secured over $2M in grants, including NSF and DOE funding. Advises on energy-efficient systems and IoT security. Teaches CS 2510 (Operating Systems) and CS 1699 (Systems & Sustainability). Labs & Teams: Directs the Sustainable Systems Research Group, focusing on decarbonizing IT and optimizing renewable energy systems. Collaborates with industry partners on smart grid solutions and edge-cloud systems.
Ehud Sharlin is a Professor in the Department of Computer Science at the University of Calgary, Faculty of Science. His research focuses on Human-Computer Interaction (HCI) with specializations in human-robot interaction, tangible interfaces, virtual/augmented reality, and autonomous vehicle interactions. He holds a Ph.D. in Computing Science from the University of Alberta (2003), and M.Sc. and B.Sc. degrees in Electrical and Computer Engineering from Ben-Gurion University of the Negev (1997 and 1990). Teaches CPSC 481: Human-Computer Interaction I Recipient of the NSERC Discovery Accelerator Award (2019), ACM Creativity & Cognition Honourable Mention (2018), and multiple academic excellence awards Active in industry collaborations, particularly in medical simulation (e.g., VRSpineSim) and geosciences (e.g., PLANWELL) Research explores: Embodied interaction through robotics and wearables Autonomous vehicle-pedestrian communication systems Immersive tools for creative and professional domains Accessibility in human-technology interfaces Publications span over 100 peer-reviewed works, emphasizing design methodologies, user experience in XR systems, and ethical considerations in sociotechnical systems. His work bridges technical innovation with human-centered design principles.
Professor Peter Macreadie is a global leader in marine science and sustainability at RMIT University, where he serves as Director of the Centre for Nature Positive Solutions and founder of the Blue Carbon Lab. He holds a professorial appointment in the School of Science and has held prior roles at Deakin University (2016–2024). His research focuses on leveraging nature-based solutions to mitigate climate change, including blue carbon ecosystems (mangroves, seagrasses, tidal marshes) and teal carbon innovations. He leads interdisciplinary projects in ecosystem restoration, coastal protection, and natural capital accounting, collaborating with governments, industries, and communities. Macreadie’s work spans over 250 publications in top journals like Science and Nature Climate Change , and he has attracted over $35M in research funding. His awards include the 2023 Frontiers Planet Prize and 2020 Premier’s Sustainability Award. He emphasizes translating science into actionable policies and practices, addressing challenges like microplastics, offshore infrastructure decommissioning, and citizen science engagement. Research Themes: Blue Carbon, Climate Mitigation, Ecosystem Restoration Key Projects: Mangrove restoration cost-benefit analysis, ocean alkalinity enhancement, and hybrid green-grey infrastructure He actively supervises PhD and industry projects, such as investigating microplastic impacts on blue carbon systems and feasibility of ocean alkalinity projects. His work aligns with UN Sustainable Development Goals 13 (Climate Action), 14 (Life Below Water), and 15 (Life on Land).
Xinyi Liu is a Professor of Archaeology and Associate Chair of the Department of Anthropology at Washington University in St. Louis. She holds a PhD from the University of Cambridge. Her research focuses on plant domestication, agricultural origins, and prehistoric food globalization, with a particular emphasis on millet and the prehistory of China. She leads fieldwork projects across the Tibetan Plateau, Hexi Corridor, Inner Mongolia, Central Asia, and Eastern Europe. Her work bridges archaeology with environmental science, using stable isotope analyses, archaeobotanical methods, and geospatial modeling. She is affiliated with the Laboratory for the Analysis of Early Food-Webs (LAEF), which examines nutrition-ecology interactions in diverse environments including the Tibetan Plateau and the Lower Yangtze region. Dr. Liu serves on editorial boards for journals like Environmental Archaeology and Archaeological Research in Asia and chairs the International Work Group for Paleoethnobotany. Her recent studies highlight millet's ecological significance and its role in achieving modern food security. Her publications (2020-2024) analyze prehistoric crop management strategies, animal domestication genetics, and the socio-environmental impacts of early food globalization. These works emphasize East Asian contributions to global prehistory and the interplay between ancient culinary practices and biodiversity. Dr. Liu's lab collaborates internationally, combining bioarchaeological data with modern ecological insights to address contemporary sustainability challenges. She has advised numerous graduate students and contributes to courses on environmental archaeology, bio-molecular approaches, and culinary globalization's deep history.
A. Stewart Fotheringham is a Regents' Professor of Computational Spatial Science and Director of the Spatial Analysis Research Center (SPARC) at Arizona State University’s School of Geographical Sciences and Urban Planning. He is also a Distinguished Sustainability Scientist at the Julie Ann Wrigley Global Institute of Sustainability. His research focuses on spatial data analysis using statistical, mathematical, and computational methods, with expertise in spatial interaction modeling and local statistical analysis, particularly multiscale geographically weighted regression (MGWR). He has conducted substantive research in health geography, crime patterns, retailing, migration, and transportation. Affiliations: ASU’s Institute for Social Science Research, National Academy of Sciences, Academia Europaea Education: Ph.D., M.A. (McMaster University), B.Sc. (Aberdeen University) Awards: Science Foundation Ireland Research Professorship (2004), over $15 million in funding His research interests include spatial statistics, geographic information science, and the development of methodologies to analyze spatial heterogeneity. He has authored 12 books and nearly 200 publications, emphasizing reproducibility in geospatial research and advancing computational tools like MGWR. Recent work examines spatial voting dynamics, housing valuation, and health disparities using local modeling techniques. He advises on grants, serves on the Transportation Research Board’s Executive Committee, and contributes to global sustainability initiatives.
Jonathan W. Chipman is an Adjunct Assistant Professor at Dartmouth College and Director of the Citrin Family GIS/Applied Spatial Analysis Laboratory. He holds an A.B. from Dartmouth College and M.S./Ph.D. from the University of Wisconsin-Madison. Specializing in geospatial science, his work integrates remote sensing, GIS, and spatial analysis to study environmental and social systems. Research focuses include lake optical properties via satellite imagery, land-use changes in Egypt/China, vegetation dynamics in southern Africa, and socio-spatial segregation patterns in the US. Education: A.B., Dartmouth College M.S., University of Wisconsin-Madison Ph.D., University of Wisconsin-Madison Research Interests: Chipman applies geospatial tools to environmental challenges, including climate change impacts on glaciers, land-cover transformations, and socio-environmental linkages. His work bridges disciplines like hydrology, ecology, and public health through innovative GIS methods. Recent projects explore tropical glacier dynamics, greenspace health correlations, and malaria endemicity patterns. Key Article Trends: Publications emphasize remote sensing applications in glaciology, environmental toxicology, and socio-environmental systems. Themes include satellite-based monitoring of river systems, glacier classification in High Mountain Asia, and GIS-driven analysis of human health exposures tied to land cover. Lab & Collaborations: Leads the Citrin Lab, focusing on applied spatial analysis. Courses taught include GEOG 54 (Geovisualization) and EARS 77 (Environmental GIS). Active in 3D landscape modeling collaborations via SketchFab and Google Scholar.
Anders Koed Madsen is a Professor at the Department of Culture and Learning, Faculty of Humanities and Social Sciences, Aalborg University. He is affiliated with the Technoanthropological Laboratory and leads research initiatives including AI for the People and MASSHINE. His work centers on digital methods, urban belonging, smart cities, and citizen science, often integrating ethnographic and participatory approaches. His research interests lie at the intersection of technology and society, focusing on digital placemaking , urban sensing , pragmatist philosophy , and inclusive urban planning . He explores how digital tools can be used to understand lived experiences in cities, especially among marginalized communities. His methodological focus includes participatory digital methods, geospatial photovoice, and computational ethnography. The recent articles highlight a consistent trend toward using digital and ethnographic methods to study urban life, technology assessment, and democratic participation. Themes include generative AI , digital epistemology , friction in machine reasoning , and inclusive city planning . His work increasingly incorporates large language models and open-source toolkits to democratize research and planning processes. Scientific Awards: European Union Prize for Citizen Science (2023) World Summit Awards (WSA) shortlist, Urban Belonging Project (2024) Ziman Award 2020: TANTlab AAU Talent (2018) Videnskabsministeriets EliteForsk-rejsestipendium (2011) Anders Koed Madsen has been actively involved in research grants and collaborative projects such as the Urban Belonging Project , Digital Placemaking and Soft City Sensing Research Network , and GE-AI: Generative Ethnographic AI . He frequently collaborates with interdisciplinary teams and institutions like IT University of Copenhagen and Gehl Architects. He advises on public engagement and has contributed to national and international discourse on digitalization and urban futures. He is a core member of the Technoanthropological Laboratory , which fosters interdisciplinary research on technology and society. The lab supports initiatives in digital methods, citizen science, and urban innovation. Madsen also contributes to public understanding through media engagement and workshops, promoting humanistic perspectives in technological development.
Natalia Andrienko is a Professor of Computer Science at City University London and Lead Scientist in the Knowledge Discovery department at Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme. Her work bridges visual analytics with mobility data science and machine learning, focusing on human-in-the-loop systems for pattern discovery and spatiotemporal data exploration. Professor, Computer Science, City University London (2013-present) Lead Scientist, Knowledge Discovery, Fraunhofer Institute (1997-present) Research interests center on visual analytics methodology for spatiotemporal data, human-centered machine learning, and mobility pattern analysis. She develops frameworks for interactive dashboards, trust visualization in ML, and semantic exploration of location-based data, with a focus on scalable and privacy-respecting techniques. Her recent publications investigate hybrid human-machine discovery of movement patterns, contextual visual analytics for multivariate events, and the integration of temporal periodization with spatial analysis. Articles emphasize applications in sports analytics, transportation systems, and collaborative visual analysis workflows. Key collaborations include work with Gennady Andrienko and Salvatore Rinzivillo. She has contributed to journals like Visual Informatics , IEEE Transactions on Visualization and Computer Graphics , and International Journal of Cartography , maintaining active research output across visual analytics, mobility science, and geospatial data modeling.
Brian M Deal serves as a Professor of Landscape Architecture within the School of Architecture at the University of Illinois at Urbana-Champaign, holding additional appointments in Urban and Regional Planning, the European Union Center, the Center for Latin American and Caribbean Studies, and the National Center for Supercomputing Applications (NCSA). His expertise bridges sustainable planning theory, energy systems, and spatial modeling to develop practical decision-support tools for community development and climate resilience. His educational foundation includes a PhD in Regional Planning (2002), Master of Architecture (1997), and BS in Architectural Studies (1983), all earned at the University of Illinois at Urbana-Champaign. Prior academic experience encompasses a decade of professional architecture practice and senior research at the Army Construction Engineering Research Laboratory (CERL), where he specialized in sustainable military facility design using spatial simulation. Deal's research centers on sustainable planning systems and climate adaptation, with current projects examining urbanization impacts on Korean rural amenities, advancing the University of Illinois' climate action plan (iCAP), and developing next-generation 'sentient' planning support systems. His work integrates land-use modeling, energy systems analysis, and decision-support technologies to address complex urban environmental challenges through interdisciplinary collaboration. Recent publications reveal a pronounced shift toward data-driven sustainability solutions, featuring AI applications for carbon-neutral planning, multi-scaled green infrastructure optimization, and socio-ecological modeling. Key themes include urban carbon sequestration, post-pandemic park dynamics, and climate-resilient coastal design, demonstrating consistent innovation in translating theoretical frameworks into actionable planning tools for real-world implementation. Professor Deal's scientific awards and honors were not detailed in the provided text. As faculty mentor to the Student Sustainability Committee and chair of campus sustainability planning efforts, Deal actively guides student development and institutional policy. His leadership of the LEAM Laboratory and SEDAC involves managing research grants focused on urban resilience, energy systems, and climate adaptation, fostering partnerships with government agencies and community organizations to deploy planning tools that directly impact community decision-making processes. Deal directs the Land Use Evolution and Impact Assessment Modeling (LEAM) Laboratory and Smart Energy Design Assistance Center (SEDAC), leading interdisciplinary teams in developing spatial simulation models and decision-support systems. His operational leadership extends to authoring the university's climate action plan and chairing campus sustainability committees, positioning him at the nexus of academic research, institutional policy, and community engagement for sustainable urban futures.
Bernhard Jenny is an Associate Professor at Monash University's Faculty of Information Technology, specializing in immersive visualization and geospatial data. He holds a PhD in Cartography from ETH Zurich and has held previous roles at Oregon State University and RMIT University. His research focuses on virtual reality (VR), augmented reality (AR), and cartographic innovations for geospatial data representation. Education: Doctor of Sciences in Cartography, ETH Zurich (2010) Postgraduate Certificate in Computer Science, ETH Zurich (2005) Master of Science in Surveying, EPFL (2000) Research Interests: Combines cartography, computer graphics, and human-computer interaction to explore VR/AR applications for geospatial data. Current work includes immersive analytics, terrain visualization, adaptive map projections, and storytelling with geospatial data. Recent Articles: Focus on ambient occlusion for terrain shading, grammars for immersive visualization transitions, and AR/VR interfaces for spatial data. Awards: Henry Johns Award (2007, 2011, 2012) ETH Medal (2010) Best Paper Honorable Mentions (ACM CHI, DIS) Grants & Projects: Leads initiatives like the 'Immersive Analytics' extension and 'National Geographic Relief Shading' project. Collaborates on neural networks for cartographic relief shading and sustainable development goals (SDGs). Labs & Teams: Heads the Embodied Visualisation Lab at Monash, focusing on immersive analytics and geovisualization tools.
Daniel Kühbacher is a Tutor and researcher at the Chair of Environmental Sensing and Modeling at Technische Universität München (TUM). He specializes in developing high-resolution urban emission inventories for CO2, CH4, and co-emitted species, and leads the setup of a 100-sensor CO2 network in Munich to assess sector-specific emission factors. His work bridges environmental monitoring, sensor technology, and urban climate science. Teaching roles include tutoring the Environmental Sensing and Modeling lecture and advanced seminar, as well as the joint practical course Gemeinschaftspraktikum MST . Research focuses on integrating traffic simulation data, mobile measurement units, and flux footprint modeling to quantify urban greenhouse gas emissions. Education: M.Sc. in Environmental Engineering Affiliations: Member of the ICOS Cities project and contributor to the ICOS Science Network Publications emphasize urban GHG monitoring innovations, including sensor network optimization, flux measurement validation, and inventory intercomparison studies. His work supports policy-relevant insights into emission hotspots and mitigation strategies. Currently develops the SCOUT project for street-level carbon observatories and explores human respiration emissions using mobile network data.
