Dr. Stan Ahalt serves as the inaugural Dean of the UNC School of Data Science and Society (SDSS) and holds a professorship in the Department of Computer Science at UNC-Chapel Hill. He previously directed the Renaissance Computing Institute (RENCI) and currently acts as its executive advisor. Additionally, he is the associate director of informatics and data science at NC TraCS, the translational research institute at UNC. His academic journey includes a 22-year tenure as professor of electrical and computer engineering at Ohio State University and leadership roles at the Ohio Supercomputer Center. Ahalt’s research focuses on applying data science to societal challenges such as healthcare, climate, and judicial reform. Key initiatives include the National Consortium for Data Science and the iRODS project, which advanced enterprise data management systems. Ahalt has secured over $34.5M in grants to lead high-impact projects like the NHLBI BioData Catalyst (unifying biomedical data), the NCATS Translator (accelerating clinical discovery), and the NIH HEAL Initiative (ensuring FAIR data standards). He mentors students across doctoral and master’s programs, teaching data science fundamentals in courses like COMP 116: Introduction to Scientific Programming. His work emphasizes interdisciplinary collaboration, evidenced by roles in RENCI, NC TraCS, and the SDSS. Ahalt’s contributions span cyberinfrastructure development, educational innovation, and translational research, positioning UNC as a national leader in data science.
Dr. Jeremy Guest is the Levenick Professor in Civil and Environmental Engineering (and courtesy appointment in Chemical & Biomolecular Engineering) at the University of Illinois Urbana-Champaign (UIUC). He serves as Associate Director for Research at the Institute for Sustainability, Energy, and Environment (iSEE) and leads the Center for Advanced Bioenergy and Bioproducts Innovation (CABBI). His research focuses on advancing circular bioeconomies through sustainable sanitation systems, resource recovery from wastewater, and biofuel/bioproduct development from lignocellulosic biomass. Guest's work emphasizes Quantitative Sustainable Design (QSD) methodologies to bridge engineering innovation with policy and investment decisions. Education: PhD in Environmental Engineering (University of Michigan, 2012); MS (Virginia Tech, 2007); BS (Bucknell University, 2005). Research interests include wastewater treatment innovation, nutrient recovery, bioenergy systems design, and sustainable agriculture practices. Key contributions include the EcoRecover phosphorus recovery process, the QSDsan modeling platform, and leadership in CABBI's $262.5M DOE-funded initiative. Guest has secured funding from NSF, US EPA, USDA, and the Bill & Melinda Gates Foundation. Recognitions include the NSF CAREER Award, 2021 James J. Morgan Early Career Award, and the Paul L. Busch Award. He advises over 15 graduate students and leads multiple high-impact projects like the NEWgenerator sanitation system and oilcane biorefinery integration. Lab/Group: Guest Research Group focuses on experimental, computational, and policy-oriented research to solve global sustainability challenges. Current projects address algae-based wastewater treatment, fecal sludge management in low-income regions, and precision fermentation systems development.
Anil Madhavapeddy serves as Professor of Planetary Computing at the University of Cambridge's Department of Computer Science and Technology and directs the Cambridge Centre for Carbon Credits (4C). A Fellow of Pembroke College, he integrates systems research with environmental conservation through the Computer Laboratory's Environment and Energy Group. His career spans industry leadership (NetApp, Citrix, Intel), academic appointments (Cambridge, Imperial, UCLA), and entrepreneurial ventures (XenSource, Unikernel Systems, Docker). Madhavapeddy earned his PhD at Cambridge's Computer Laboratory in 2006. His research bridges computational systems and planetary-scale environmental challenges, with deep expertise in open-source development (OCaml, Xen, Docker, OpenBSD) and technology strategy advising for organizations including Zededa, Tezos Foundation, and Tarides. His work centers on environmental computing and climate informatics, leveraging distributed systems and functional programming to develop sensing infrastructure for conservation. Recent projects focus on carbon credit systems, AI-driven biodiversity monitoring, and sustainable computing architectures that minimize ecological footprints while maximizing analytical capability. Analysis of his 2025 publications reveals a concentrated effort on AI-integrated conservation tools, privacy-preserving carbon accounting, and energy-efficient computing. Key themes include spatial networking for ecological data, LLM-enhanced evidence retrieval in conservation science, and novel metrics for extinction risk assessment—demonstrating computational innovation applied to urgent planetary boundaries. No scientific awards were documented in the source material. Madhavapeddy advises multiple technology firms on strategic development while leading the Cambridge Centre for Carbon Credits, though specific grant funding details remain unreported. He actively contributes to the Environment and Energy Group at Cambridge's Computer Laboratory and directs the interdisciplinary Cambridge Centre for Carbon Credits (4C). His open-source leadership spans critical infrastructure projects including OCaml, Xen, and Docker, fostering collaborative development communities that underpin modern cloud and container technologies.
Jim Thatcher is an Assistant Professor at the College of Earth, Ocean, and Atmospheric Sciences (CEOAS) at Oregon State University. He serves as editor of Cartographic Perspectives , a leading journal in cartography. His research focuses on the intersection of technology, society, and environment, particularly examining how data and spatial technologies operate within capitalist systems. Key areas include Critical GIS, Critical Cartography, and Digital Political Ecology. Thatcher's current projects explore equitable coastal flood risk modeling using topological data analysis, mapping infrastructural legacies of slavery in the Pacific Northwest, and creating accessible disaster response maps for non-English speakers in Oregon. He also investigates spectral governance for rural internet access, cartography's societal role, climate education through board games, and geographic influences on electoral districting. His research emphasizes critical approaches to spatial data, questioning representational practices and power dynamics embedded in geospatial technologies. Recent work includes analyzing Bitcoin mining's environmental impacts on hydropower systems and examining the World Bank's renewable energy mapping through Critical Data Studies. Thatcher actively mentors graduate students and encourages interdisciplinary inquiries blending critical social theory with computational methods. Thatcher has authored numerous articles and co-authored Data Power (Pluto Press, 2022), an open-access exploration of data's role in societal control and resistance. His scholarship bridges critical geography with emerging technologies, advocating for ethical and equitable spatial practices in an increasingly data-driven world.
Luc Anselin is the Stein-Freiler Distinguished Service Professor of Sociology and the College at the University of Chicago. He serves as Director of the Center for Spatial Data Science and Senior Fellow at NORC, with affiliations in the Department of Sociology and the Committee on Quantitative Research Methods in Social, Behavioral, and Health Sciences. B.S., Vrije Universiteit Brussel, 1975 M.S., Vrije Universiteit Brussel, 1976 M.A., Cornell University, 1979 Ph.D., Cornell University, 1980 Anselin is a pioneer in spatial data science, spatial econometrics, and computational social science. His work bridges quantitative geography, regional science, and computer science, with applications in urban studies, economic analysis, and health research. His recent publications focus on spatial regimes, software ecosystems like GeoDa and PySAL, stigma analysis in public health, and computational methods for urban equity. These reflect interdisciplinary trends in spatial statistical modeling, open-source development, and geospatial policy evaluation. Scientific recognition includes: Fellow, Regional Science Association International (2004) Walter Isard Prize (2005) William Alonso Memorial Prize (2006) National Academy of Sciences (2008) American Academy of Arts and Sciences (2011) Anselin has led major grants and directed institutions like the GeoDa Center for Geospatial Analysis and Computation at Arizona State University. He has mentored interdisciplinary collaborations across sociology, economics, and data science. His laboratories and teams include the Center for Spatial Data Science at the University of Chicago and the GeoDa Center at Arizona State University, fostering innovation in geospatial computation and open-source spatial analytics.
Dr. Dennis Buckmaster is a Professor in Agricultural & Biological Engineering at Purdue University, serving as Dean's Fellow for Digital Agriculture. He holds a B.S. from Purdue University and M.S./Ph.D. from Michigan State University. His research focuses on digital agriculture, machine systems engineering, and data science applications in farming. He co-coordinates the Agricultural Systems Management program and teaches courses like Computing Technology with Applications and Ag Tech and Innovation. He leads the Open Ag Technology and Systems Center (OATS Center), advancing open-source solutions for agriculture through platforms like ISOBlue and OADA. His work integrates IoT, robotics, and machine learning to optimize crop production, livestock management, and farm decision-making. He has authored over 150 publications on precision agriculture technologies. Professional memberships include American Society of Agricultural and Biological Engineers and Fluid Power Society. He emphasizes data interoperability, edge computing, and bridging engineering with agricultural practices through collaborative frameworks like LATTICE and Meta Ag.
Patrick Kastner is an Assistant Professor at the School of Architecture and holds an adjunct appointment at the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. He directs the Sustainable Urban Systems Lab, focusing on environmental performance simulation and urban decarbonization. His work emphasizes software tools for sustainable urban decision-making, such as Eddy3D, a microclimate modeling toolkit widely adopted in academia and practice. Education: Ph.D. and M.S. in Systems Science and Engineering, Cornell University (2022, 2021) M.S. in Sustainable Building Science, Technical University of Munich (2017) B.S. in Energy Engineering, University of Erlangen–Nuremberg (2012) Research Interests: Environmental performance simulation, urban decarbonization, machine learning applications in urban systems, spatial analysis, and software development for sustainability. His work integrates computational fluid dynamics (CFD), surrogate modeling, and data-driven approaches to address urban climate challenges. Key Projects: Leads the Vertically Integrated Project SMUR (Surrogate Modeling for Urban Regeneration), fostering interdisciplinary collaboration across Georgia Tech. Developed Eddy3D, which streamlines microclimate simulations for architects and urban planners. Grants & Advising: Engages students from sophomore to graduate levels in sustainability research. Teaches at Cornell and UPenn previously. Advises on projects blending engineering, urban design, and climate science. Labs & Teams: Director of the Sustainable Urban Systems Lab, focusing on software tools for sustainable urban transformation. Collaborates with industry partners and global institutions on decarbonization strategies.
Filip Biljecki is an Assistant Professor jointly appointed at the Department of Architecture within the College of Design and Engineering and the Department of Real Estate at the NUS Business School, National University of Singapore. He is the founder and principal investigator of the NUS Urban Analytics Lab and was awarded the prestigious NUS Presidential Young Professorship in 2020. With over 150 peer-reviewed publications, his research bridges geomatic engineering, geospatial technologies, and urban data science to advance digital twins and data-driven urban planning. Dr. Biljecki's educational background includes: PhD in 3D GIS (cum laude), Delft University of Technology, Netherlands (2017) MSc in Geomatics, Delft University of Technology, Netherlands (2010) BSc in Geodesy and Geoinformatics, University of Zagreb, Croatia (2008) His research interests focus on emerging urban data sources, particularly urban imagery, and their application in 3D city modeling, digital twins, and GeoAI. He explores how crowdsourcing and open science can inform cutting-edge techniques for urban sensing and analytics at city-scale. His work significantly contributes to establishing smart cities through innovative methods that integrate recent advancements in computer science, geomatics, and urban data science. Analysis of his recent publications reveals a strong focus on street view imagery applications for urban analytics, digital twin development, and geospatial AI. His research spans multiple domains including urban morphology, environmental assessment, public health applications, and urban comfort analysis. The interdisciplinary nature of his work is evident in collaborations with researchers from diverse fields, producing impactful studies that address complex urban challenges through innovative methodological approaches. His notable scientific achievements include: Annual Teaching Excellence Award (ATEA), 2025 College Educator Award AY2023/2024, 2025 Urban Informatics Paper of the Year Award, 2023 Top 2% scientists worldwide (Stanford University), 2021 Presidential Young Professorship (NUS), 2020 As an educator, Dr. Biljecki has supervised dozens of students leading to publications in leading journals and placements at top universities and organizations. He has delivered talks at over 120 universities and organizations worldwide including MIT, Stanford, Harvard, and ETH Zurich. His research is supported through various grants and affiliations including his role as Principal Investigator at the Future Cities Lab Global at the Singapore-ETH Centre. The NUS Urban Analytics Lab, which he established, brings together scholars from diverse disciplines to drive research on making cities smarter and more data-driven. The lab has developed innovative tools like ZenSVI for street view imagery analysis and has produced influential research on urban digital twins, urban morphology, and GeoAI applications. Through his leadership, the lab continues to pioneer methods that advance data-driven urban planning and smart city development.
Xiaocheng Shang is an Associate Professor in Mathematical Optimisation and Data Science at the University of Birmingham's School of Mathematics. His research focuses on numerical methods for stochastic differential equations, with applications in computational mathematics, statistics, physics, and data science. He is affiliated with the Optimisation and Numerical Analysis Group, Statistics and Data Science Group, and the Institute for Data and AI. Shang holds a PhD in Applied and Computational Mathematics from the University of Edinburgh (2016) and completed postdocs at the University of Edinburgh, Brown University, and ETH Zurich before joining Birmingham in 2019. His academic achievements include fellowships from The Alan Turing Institute, the LMS Emmy Noether Fellowship, and the EUniWell Leadership Fellowship. He has secured funding from EPSRC, the Royal Society, and the Isaac Newton Institute. Shang is actively involved in supervising PhD students and co-organizing research initiatives such as the Data Science and Computational Statistics Seminar. Research interests include structure-preserving integrators, Bayesian sampling techniques, and machine learning applications in dynamical systems. His work bridges numerical analysis, probability theory, and multiscale modeling in materials science. Recent projects involve neural networks for complex dynamical systems and numerical algorithms for deterministic/stochastic systems.
Beata Csatho PhD is a Professor in the Department of Earth Sciences at the University at Buffalo, affiliated with the College of Arts and Sciences. Her research focuses on remote sensing, glaciology, climate change, and geophysics. She holds a PhD in Geophysics from the University of Miskolc, Hungary (1993). Her work integrates geophysical, remote sensing, and climatic data to study ice sheet dynamics and cryospheric changes. She leads the Remote Sensing lab and teaches courses like GLY 465/565 (Environmental Remote Sensing) and GLY 325 (Geophysics). Recent research emphasizes Greenland and Antarctic ice dynamics, ICESat-2 validation, and developing tools like Ghub for collaborative glaciology. She advises PhD and Master's students and collaborates on major projects like ISMIP7 and IceBridge. Her lab focuses on advancing laser altimetry, DEM correction, and cryosphere observation techniques.
Ross Meentemeyer is a Professor and Director of the Center for Geospatial Analytics at North Carolina State University, affiliated with the Department of Forestry and Environmental Resources in the College of Natural Resources. He holds a Ph.D. in Geography from the University of North Carolina, Chapel Hill (2000) and a B.S. in Geography from the University of Georgia (1993). His research focuses on geospatial analytics, ecological forecasting, biological invasions, and forest health, with a strong emphasis on integrating geospatial data and modeling to address environmental challenges. Dr. Meentemeyer's work includes developing decision-support tools for pest management, climate adaptation, and land-use planning. Notable projects involve forecasting invasive species spread via international trade, creating open-source geospatial platforms, and modeling floodplain development risks. He collaborates extensively with federal agencies like USDA, DOI, and NPS to translate research into practical solutions. His grants include multi-million dollar NSF and USDA-funded initiatives addressing plant disease pandemics, agricultural pest threats, and geospatial infrastructure development. Key outcomes include the PAdb system for pandemic prediction and the FUTURES model for urbanization forecasting. He also leads efforts to enhance stakeholder engagement through participatory modeling tools like Tangible Landscape. Research contributions span 20+ years, with over 100 peer-reviewed articles on topics like viewscape modeling, river water dynamics, and wildfire-epidemic interactions. His work bridges ecological and social sciences, emphasizing actionable solutions for sustainable land management and climate resilience.
Dr. Alastair Key serves as Director of Studies in Archaeology and Official Fellow in Archaeology at Queens' College, University of Cambridge. His research bridges Paleolithic archaeology, stone tool technology, and hominin behavioral evolution through experimental and computational approaches. Director of Studies and Official Fellow at Queens' College, Cambridge Specializes in Paleolithic stone tool analysis, Acheulean technology, and hominin adaptation Conducts experimental archaeology and computational modelling to assess tool functionality Key's research focuses on Acheulean handaxe production , lithic microwear patterns , and ergonomic constraints in prehistoric tool use . He has extensively published on topics including glacial-stage hominin occupations , Oldowan toolmakers , and machine learning applications to archaeological analysis . His recent publications (2025-2023) span diverse subfields: Acheulean chronology , hominin tool use biomechanics , experimental projectile testing , and computational morphometric methods . The work often integrates multidisciplinary datasets and open-source analytical tools to address fundamental questions about human technological evolution. Current research directions include stone tool sharpness quantification , handaxe social signaling potential , and cross-species tool use comparisons through primate studies.
Gabriele Facciolo is a Professor at the Centre Borelli, ENS Paris-Saclay, France. He is a Senior Member of the Institut Universitaire de France (IUF) and holds an Innovation Chair (2025). His research focuses on image and video processing, remote sensing, and super-resolution techniques. Current affiliations: Centre Borelli (ENS Paris-Saclay), Institut Universitaire de France His research explores advanced algorithms for satellite stereo pipelines, real-time deblurring, denoising, and explainable AI systems for legal evidence enhancement. He coordinates projects like ANR SURECAVI (Super-resolution for visible camera systems) and ANR IMPROVED (video enhancement for judicial use), with recent work on Gaussian Splatting for Earth Observation and multi-date satellite super-resolution. Notable scientific achievements include the IGARSS 2025 Top 10 Student Paper Award and leadership in projects funded by ANR (€890k) and Prime Minister's entities (SGDSN/ANSSI). His work bridges computational imaging, defense applications, and digital forensics. Project leadership: SURECAVI, IMPROVED, BOFOR Key technologies: GPU acceleration, real-time processing, optical flow estimation, RPC refinement Gabriele actively contributes to open-source tools like S2P (Satellite Stereo Pipeline), MGM (MultiGlobal Matching), and OMNIflip. He teaches in the Master MVA program and collaborates across institutions (ENPC, UPF).
Ben Mather is a Research Fellow in the School of Geosciences at The University of Sydney, specializing in geodynamic modeling and Earth system processes. He leads the EarthByte Group's efforts to integrate numerical models with geophysical data, focusing on volcanic systems, groundwater dynamics, and critical mineral exploration. His work bridges geoscience and climate change mitigation strategies, influencing national and international policy discussions. Education: PhD in Earth Science, The University of Melbourne (2016) Bachelor of Science (Hons), Monash University (2011) Diploma of Film and Television, Monash University (2010) Research Interests: Enigmatic volcanic activity patterns and their tectonic drivers Groundwater flow pathways under climate extremes Carbon sequestration via tectonic processes Development of open-source geodynamic tools like Stripy and PyCurious Notable Projects: Project Volcanoes Downunder: Investigating volcanic chains in the Tasman Sea Groundwater modeling for southeastern Australia's aquifers Thermal structure studies in Ireland and Australia using Bayesian inversion His computational frameworks, built on PETSc and Python, enable large-scale simulations of Earth's thermal and hydrological systems. Mather actively engages in public science communication through media interviews and educational workshops.
Christian Igel is a Professor at the Department of Computer Science, University of Copenhagen, and serves as director of the SCIENCE AI Centre . He is also a co-lead of the Pioneer Centre for Artificial Intelligence in Denmark. His academic journey includes a Doctoral degree from Bielefeld University (2002) and a Habilitation degree from Ruhr-University Bochum (2010). Igel is a Juniorprofessor (2002–2010) and has held editorial roles at journals like KI - Künstliche Intelligenz and Artificial Intelligence Journal . Doctoral degree: Faculty of Technology, Bielefeld University, Germany (2002) Habilitation degree: Department of Electrical Engineering and Information Sciences, Ruhr-University Bochum, Germany (2010) His research spans Machine Learning , focusing on Support Vector Machines , Evolution Strategies , Reinforcement Learning , Deep Neural Networks , and PAC-Bayesian Analysis . He applies these methods to Environmental Monitoring , Medical Diagnostics , and Climate Research . Recent publications highlight work on adversarial machine learning , environmentally sustainable AI , and tree resource mapping using deep learning. His scientific awards include being a ELLIS Fellow . Igel’s software tools like Shark , woody , and Multi-Planar UNet are widely used in research and industry. Notable grants and collaborations involve projects with European Lab for Learning and Intelligent Systems (ELLIS) , SCIENCE AI Centre , and international teams in Denmark , Germany , and France . His lab leadership emphasizes open-source frameworks and reproducible research. Editorial Roles: German Journal on Artificial Intelligence , Evolutionary Computation Journal , Artificial Intelligence Journal Software Projects: Shark , woody , Multi-Planar UNet , U-Time Collaborations: SCIENCE AI Centre , Pioneer Centre for Artificial Intelligence , European Lab for Learning and Intelligent Systems
