Farah Kamw is an Assistant Professor in the Department of Computer Science at Wayne State University. With a PhD in Computer Science (2019) from Kent State University, her expertise spans 18 years of software development, academic teaching, and research in information visualization and database management. Education : PhD (Kent State), MSc (University of Zakho), BSc (University of Baghdad) Her research focuses on Information Visualization and Visual Analytics of spatial-temporal data, particularly through 8 publications (2013-2021) addressing urban mobility patterns, trajectory analysis, and geospatial data integration. She has developed several open-source visual analytics tools including TrajAnalytics and SparseTrajAnalytics, applying both document and graph database techniques. Farah teaches core Computer Science courses such as Algorithm Design , Programming Languages , and Database Systems . Her technical skills include Python, C++, Java, SQL, NoSQL databases, and GIS technologies.
Eugene Kennedy is a Professor in the Department of Educational Research at Louisiana State University's College of Human Sciences & Education. Holding a PhD in Educational Research Methodology from the University of South Carolina (1990), Kennedy's career spans academic research, state education departments, and technical consulting roles. His work focuses on educational effectiveness, psychometrics, and technology integration in education. Bachelor's: Sociology, Benedict College (1977) Master's: Educational Statistics & Measurement, University of Iowa (1982) PhD: Educational Research, University of South Carolina (1990) Kennedy's research interests include educational research methodology , psychometrics , school effectiveness , STEM education , data-driven decision making , and learning analytics . His recent publications demonstrate increasing focus on AI's role in education and data-driven strategies for improving educational outcomes. His academic work shows trends in educational technology integration , quantitative research methods , and STEM equity initiatives . Key themes include using data mining for educational insights, technology tools for school leadership, and innovative teaching strategies to improve student outcomes. Kennedy has participated in grants including: Co-PI for Evaluation proposal for the EBRPS American Recovery and Reinvestment Act Program (2010-2011) PI for Longitudinal Study with University of Louisiana Lafayette (2008-2009) Contact: ekennedy@lsu.edu | 221 Peabody Hall | 225-578-2193
François Pomerleau is a full-time Professor at the Department of Computer Science and Software Engineering at Université Laval since 2017. His research focuses on 3D environment reconstruction , autonomous navigation , search-and-rescue robotics , and scientific methodology in robotics . He has held postdoctoral fellowships at the University of Toronto and Université Laval, with technology transfer experience at Alstom Inspection Robotics and Robotiq. Ph.D. in Mechanical Engineering (2013) from ETH Zurich M.Sc. in Electrical Engineering (2009) and B.Ing. in Computer Engineering (2006) from Université de Sherbrooke His research integrates robotics , computer science , and environmental monitoring , with a focus on point cloud registration , Lidar-based SLAM , and trajectory planning for unstructured environments. Recent work includes UAV-assisted terrain awareness , exposure time emulation for vision algorithms , and multi-season datasets for autonomous navigation . François’s recent publications emphasize 3D mapping , SLAM robustness , and environmental adaptation across forestry, subarctic, and alpine domains. His team develops tools for autonomous vehicles , search-and-rescue , and industry 4.0 . Scientific awards include Best Robotic Vision Paper Awards at CRV 2016 and 2020, a Best Paper Award at the ICRA 2024 Workshop, and recognition as a Distal Fellow of the NSERC Canadian Robotics Network (NCRN). He collaborates with industry partners like Robotiq and serves as Associate Editor for IEEE Robotics and Automation Letters , Frontiers in Robotics and AI , and IROS , while contributing to international program committees for robotics conferences.
Arnab Nandi is a Professor of Computer Science and Engineering at The Ohio State University, with a courtesy appointment in Biomedical Informatics. He holds leadership roles including Steering Committee Member for the Human-in-the-Loop Data Analytics (HILDA) Workshop and has served as Workshops co-chair for SIGMOD 2025-26 and Demonstrations co-chair for SIGMOD 2024. His research focuses on bridging human interaction and data infrastructure, spanning database systems, human-in-the-loop data analytics, and next-generation query interfaces. Nandi's work emphasizes interactive data exploration through projects like DICE (Distributed Interactive Cube Exploration), GestureDB (Querying Beyond Keyboards), and Omni (Multimodal Data Exploration). His recent research explores integrating LLMs into database education, augmented reality interfaces for data analytics, and multimodal approaches to video querying. Nandi has received numerous honors including the NSF CAREER Award, Google Faculty Research Award, IEEE TCDE Early Career Award, and the University's Alumni Award for Distinguished Teaching. He was also named to Columbus Business First's '40 under 40' and became an ACM Distinguished Member in 2024. As an educator, he teaches courses including CSE 3241 (Introduction to Database Systems), CSE 5242 (Advanced Database Systems), and CSE 5251 (Introduction to Software Startups). His educational innovations include DBTutor, which integrates LLMs into database systems education. At Ohio State, Nandi co-founded the OHI/O Program, which fosters tech culture through hackathons, and The STEAM Factory, an interdisciplinary research collaboration network. Prior to academia, he was founder and CEO of Mobikit, a connected vehicles data analytics startup acquired by Azuga Inc. (a Bridgestone company). His research has been supported by the NSF and industry partnerships, with applications spanning precision agriculture (CropFusion), clinical data pipelines (ICARUS), and interactive visualization systems (Perceptvis).
Isabella "Izzi" Hinks serves as a Teaching Assistant Professor in the Computer Science Department at the University of North Carolina at Chapel Hill. She completed her Ph.D. in Geospatial Analytics at NC State University's Center for Geospatial Analytics in 2024, where she was advised by Dr. Josh Gray. Her academic journey began with dual B.Sc. degrees in Computer Science and Environmental Science, along with a minor in Statistics and Analytics, all earned at UNC Chapel Hill. Dr. Hinks' research focuses on developing innovative algorithms to estimate the adaptive potential of small-scale agriculture in poverty-affected regions. Her work combines computer science expertise with environmental applications, particularly in using remote sensing technologies and deep learning techniques to monitor smallholder farming systems. She has made significant contributions to understanding how smallholder farmers can enhance their climate resilience through strategic adaptations, leveraging both satellite data and field observations. Her publication record demonstrates a consistent focus on applying advanced computational methods to agricultural monitoring challenges. The most recent articles show a progression from basic field boundary mapping using deep learning toward more sophisticated analyses of climate adaptation impacts on smallholder resilience. Her work increasingly integrates multiple data sources, including satellite imagery, household surveys, and on-the-ground measurements, to create comprehensive assessment frameworks for agricultural systems in developing regions. Among her notable recognitions is the Gladys West Award from the Center for Geospatial Analytics' fourth annual CGA Awards, received in January 2023. Her research on deep learning-based smallholder field delineation was featured in an NC State University News article in April 2023, highlighting the practical significance of her work. Dr. Hinks has been actively involved in several research initiatives, including work with the RESCuE Consortium in Thailand monitoring coastal ecosystem rehabilitation and supporting underserved communities during the Covid-19 pandemic through Curamericas Global. She was also a founding member of Acta Solutions, a tech start-up focused on helping local governments optimize decisions using constituent data. Her presentations at major conferences like the AGU Fall Meeting demonstrate her growing prominence in the field of geospatial analytics for agricultural applications.
Dr. Tamas Mona is a Postdoctoral Research Associate in the Department of Plant Sciences at the University of Cambridge , affiliated with the Epidemiology and Modelling Group . His work focuses on environmental suitability models for large-scale epidemiological forecasting, particularly in wheat rust outbreaks across Africa, the Middle East, and Asia. Collaborations include the UK Met Office, CIMMYT, and institutions in Ethiopia, Kenya, Bangladesh, and Nepal. PhD in Environmental Sciences (2019), Eötvös Loránd University MSc in Meteorology (2013), Eötvös Loránd University BSc in Physics with Meteorology (2011), Eötvös Loránd University Research interests integrate meteorological applications with epidemiological models to predict crop disease outbreaks. Key projects involve tracking transmission pathways for stem rust pathogens and analyzing how irrigation creates green bridges for intercontinental pathogen spread. Publications emphasize environmental science and computational epidemiology . Current collaborations span Sub-Saharan Africa (EIAR, ATI, KARLO) and South Asia (BWMRI, NARC) through initiatives like the Global Food Security IRC . Modeling frameworks developed by Mona contribute to policy advisory systems for emerging pest threats, aligning with DEFRA and UK government strategies.
Xochizeltzin Castañeda-Camacho serves as Assistant Professor of Environmental Studies at St. Olaf College in Northfield, Minnesota, teaching Remote Sensing and GIS, Mixed Methods for Environmental Analysis, and Introduction to Environmental Studies. Previously, she held a postdoctoral position at CIGA-UNAM and collaborated with Mexico's National Commission of Protected Areas. Her academic background includes: Ph.D. in Geography, University of Texas at Austin (2023) Dr. Castañeda-Camacho specializes in human-environment geography, focusing on protected areas, socio-ecological systems, and habitat conservation in arid lands. Her research analyzes land degradation patterns and habitat loss in northern Mexico's protected areas using mixed methods, geospatial technologies, and community engagement, with emphasis on field-based assessment of vegetation cover changes and socio-ecological resilience. Her publications—including a 2024 book chapter on arid protected areas—demonstrate expertise spanning geography, environmental science, and conservation biology, with recurring themes in protected areas management, arid lands ecology, and spatial analysis of habitat fragmentation across her seven peer-reviewed works. Scientific recognition: American Geographical Society Council Fellowship (2020) She has directed seven undergraduate theses in Mexico and actively promotes academic collaboration through the American Association of Geographers, currently chairing its Protected Areas Specialty Group (2025-2026). Her research integrates university expertise with government agencies, local communities, and students to address environmental challenges in vulnerable ecosystems. Dr. Castañeda-Camacho maintains active field research in northern Mexico while developing community-engaged methodologies at St. Olaf College, emphasizing practical applications of geospatial analysis for conservation planning.
Andreas Mastrosavvas is a Senior Research Fellow in Census Innovation at the Research Department of Epidemiology and Public Health at University College London (UCL). He works with the Centre for Longitudinal Study Information and User Support (CeLSIUS) to advance the use of UK Census data for public good research. PhD in Social Sciences, Cardiff University MSc in Data Science and Analytics, Cardiff University His research focuses on: Administrative data integration Spatial analysis methodologies Quasi-experimental designs for social research Neighbourhood effects and social networks Public policy evaluation Election dynamics Key projects include: Harmonisation of UK Census commuting data (1991-2011) Creation of Tolbert-Sizer commuting zones for England & Wales Development of stable local authority district classifications Methodological expertise spans: Directed and gross commuting flow analysis Resident workforce estimation Geospatial clustering techniques Boundary harmonisation across census years
Sara Heydari is a Visiting Professor in the Department of Computer Science at Aalto University , Finland. Her research focuses on analyzing egocentric social networks, human behavior through digital traces, and mobility patterns during disruptions, combining computational methods with social science perspectives.
Keenan Gibbons is a Lecturer in Environment Sustainability and Development at the University of Michigan’s School of Environment, Art, and Society. A licensed landscape architect and urban design professional based in Detroit, he specializes in sustainable green infrastructure, parks, streetscapes, and innovative stormwater management strategies. With expertise in digital media, parametric modeling, and FAA-certified drone operations, he conducts research on urban heat island effects supported by the Landscape Architecture Foundation. Education Master of Landscape Architecture, Ball State University Bachelor of Science in Horticulture, Michigan State University His research interests integrate environmental sustainability with urban design , focusing on climate resilience through drone-based thermal imaging and low-impact construction . Publications highlight his work on UAV thermal disparity visualization and community-driven urban regeneration , including notable projects like Riverside Park Detroit . He received the LAF Deb Mitchell Research Grant for his heat wave visualization toolkit. Keenan’s projects include concrete-free construction for fences, decks, and planters, emphasizing reclaimed materials and DIY innovation . His work has been featured in CNN , The Weather Channel , and professional journals like MiASLA SITES . As an educator, he bridges environmental theory with hands-on design practice , often involving community stakeholders in his projects.
Lisa Grant Ludwig is a Professor in the Department of Population Health and Disease Prevention at the University of California, Irvine (UCI). She is a nationally recognized expert in earthquake science, focusing on translating geophysical research into policy for disaster risk reduction. Her work bridges seismology, public health, and policy implementation. PhD in Geology with Geophysics minor (Caltech) MS in Environmental Engineering Science (Caltech) BS in Applied Environmental Earth Science (Stanford) Dr. Ludwig's research centers on earthquake dynamics, particularly along the San Andreas Fault, advancing disaster resilience through innovative nowcasting techniques using AI and machine learning. Her publications demonstrate expertise in seismic hazard modeling, geodetic imaging, and community preparedness studies. Recent publications highlight AI-enhanced earthquake prediction (QuakeGPT), temporal-spatial nowcasting models, and applications of geodetic data for crustal deformation analysis. These works integrate machine learning with traditional seismological methods to improve hazard forecasting. President of Seismological Society of America NASA 2012 Software of the Year Medal Featured on Science magazine cover Congressional Testimony provider Active Federal Advisory Committee member Her interdisciplinary approach combines geophysics, public health policy, and computational science. Current projects focus on earthquake nowcasting, fault zone analysis, and developing accessible geospatial tools like GeoGateway for disaster response.
Miguel Mahecha is Professor of Environmental Data Science and Remote Sensing at the University of Leipzig, where he serves as Institute Head of the Institute for Earth System Science and Remote Sensing. He is also affiliated with the Remote Sensing Centre for Earth System Research, a collaboration between Leipzig University and the Helmholtz Centre for Environmental Research (UFZ). Mahecha is a member of the German Centre for Integrative Biodiversity Research (iDiv) and serves as Principal Investigator in the Centre for Scalable Data Analytics and Artificial Intelligence. Additionally, he is a Fellow of the European Laboratory for Learning and Intelligent Systems and co-spokesperson for the National Research Data Infrastructure for Earth System Sciences (NFDI4Earth). Full Professor for Modelling Approaches in Remote Sensing, University of Leipzig (since 03/2020) Research Group Leader: Empirical Inference in the Earth System, Max Planck Institute for Biogeochemistry, Jena (12/2012 - 03/2020) PostDoc, Max Planck Institute for Biogeochemistry, Jena (10/2009 - 11/2012) PhD in Environmental Sciences, ETH Zürich (06/2006 - 09/2009) Diploma in Geoecology, Bayreuth University (10/2000 - 04/2006) Mahecha's research focuses on understanding ecosystem responses to climate extremes and human-environment relationships during these events. He investigates macro-ecological dynamics and ecosystem functioning using data-driven methods and high-dimensional Earth observations. A key contribution is his co-development of the Earth System Data Cube concept, which integrates empirical methods with theoretical understanding to analyze complex Earth system interactions. His work spans biogeography, ecosystem functioning, and advanced data science methodologies for environmental monitoring. His recent publications demonstrate a strong emphasis on analyzing compound climate extremes, particularly heatwaves and droughts, and their impacts on ecosystems. Mahecha has pioneered methods using Earth System Data Cubes to integrate diverse environmental datasets, enabling novel insights into biosphere-atmosphere interactions. His research increasingly incorporates artificial intelligence and machine learning approaches to understand spatiotemporal patterns in ecological systems, with applications in real-time forest monitoring and biodiversity assessment. Fellow of the European Laboratory for Learning and Intelligent Systems Co-spokesperson for NFDI4Earth (National Research Data Infrastructure for Earth System Sciences) Mahecha leads multiple significant research projects including Digital Forest (real-time forest monitoring), NFDI4BioDiversity, and XAIDA (extreme events: AI for Detection and Attribution). His work receives funding from diverse sources including EU, DFG, and Stiftungen Inland. He collaborates extensively with the German Centre for Integrative Biodiversity Research (iDiv) and the Centre for Scalable Data Analytics and Artificial Intelligence. His research group, Earth System Data Science (ESDS), focuses on developing methods to extract valuable information from long-term environmental observations to understand coupled Earth system dynamics. At the Remote Sensing Centre for Earth System Research, Mahecha's ESDS group investigates how ecosystem functions respond to climate extremes, societal vulnerability to environmental hazards, and nonlinear interactions in coupled Earth systems. The group leverages citizen science data, remote sensing observations, and advanced computational methods to address pressing environmental questions.
Dr. Paweł Kwaśnicki is an Assistant Professor at the Department of Analytical and Engineering within the Faculty of Natural and Technical Sciences, John Paul II Catholic University of Lublin. His research focuses on advanced photovoltaic technologies, particularly third-generation solar cells, quantum dots, and transparent conductive oxides. He has contributed to scalable electrodeposition methods for platinum nanoparticles in dye-sensitized solar cells and explored TiO₂-based nanocomposites for energy applications. Research Trends: Specializes in photovoltaic materials (perovskite, TiO₂), thin-film deposition, and circular economy strategies for waste-to-energy systems. Key Collaborations: Works with institutions like Agricultural University of Krakow and ML System S.A. Laboratory. Supervisory Roles: Serves as a PhD thesis supervisor and has guided numerous bachelor's and master's theses on topics ranging from diet impacts to microplastics in food.
Kavita Bala is the 17th Provost of Cornell University and a Professor of Computer Science. She previously served as the inaugural Dean of the Cornell Ann S. Bowers College of Computing and Information Science, leading its transition to a degree-granting college by 2025, and as Chair of Cornell’s Department of Computer Science. Her academic leadership includes expanding faculty, establishing research programs like the Bowers CIS Undergraduate Research Experience (BURE), and securing a new research facility for computing and information science. Education: B.Tech (IIT Bombay), M.S. and Ph.D. (MIT, Computer Science) Bala’s research focuses on computer vision, artificial intelligence, and computer graphics , with groundbreaking work in material and style recognition using deep learning. Her innovations in crowdsourced training data and differentiable rendering have advanced visual search technologies and translucent material modeling, powering her startup GrokStyle. She pioneered AI techniques applied to environmental monitoring through projects like MONITRS and AllClear , addressing Earth observation challenges. Her scientific awards include: American Academy of Arts and Sciences (2025) SIGGRAPH Computer Graphics Achievement Award (2020) IIT Bombay Distinguished Alumnus Award (2021) ACM Fellow (2019) SIGGRAPH Academy Fellow (2020) As Provost, Bala drives strategic initiatives like the Cornell AI Initiative , creating interdisciplinary minors in AI and AI in Society, and establishing the Schmidt AI in Science postdoctoral program. She co-chaired a task force for generative AI guidelines in education.
Fedor Dokshin is an Assistant Professor in the Department of Sociology at the University of Toronto, Downtown Toronto (St. George) campus. His research bridges computational social science with environmental and political sociology, focusing on energy transitions, partisan dynamics, and social network structures. Key research areas include racial and income disparities in solar photovoltaic adoption, policy feedback mechanisms in renewable energy programs, and partisan influences on environmental decision-making. Fields of Study: Computational and Quantitative Methods, Environmental Sociology, Political Sociology, Social Networks Areas of Interest: Computational social science, Energy and the environment, Political polarization Research Trends: Dokshin's publications reveal a focus on energy justice, behavioral diffusion models, and political polarization. His work combines computational methods with environmental policy analysis, examining how socioeconomic factors and partisan identities shape renewable energy adoption. Articles demonstrate geographic heterogeneity in opposition to extraction projects, digital discourse analysis techniques, and institutional dynamics affecting scholarly knowledge production. Methodological Emphasis: Utilizes large-scale data analysis, spatial modeling, and automated textual analysis to explore energy-environment-society intersections. Research highlights the tension between technical solutions and social equity in energy transitions, with recurring themes of policy design, public engagement, and networked political behavior.
