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Darwyn CoxsonView profile

Professor

• Lichen Ecology
• Conservation Biology
• Biodiversity
• +12 more

Darwyn Coxson is a Professor in the Ecosystem Science and Management Program within the Faculty of Environment at the University of Northern British Columbia (UNBC). As a founding faculty member of UNBC, he has played a pivotal role in shaping academic and research initiatives, including serving as past Director of the Natural Resources and Environmental Studies Institute and as a member of the UNBC Board and Senate. He is actively involved in graduate education, supervising students in the NRES (Natural Resources and Environmental Studies) graduate programs. Dr. Coxson’s research centers on lichen ecology , particularly the symbiotic relationships between fungi and algae, and has expanded into conservation biology of inland temperate rainforest ecosystems in British Columbia. His work emphasizes the ecological significance of old-growth forests and has directly influenced land management practices in the region. Key research areas include biodiversity, forest management, environmental physiology, and the conservation of critical habitats. His recent publications reflect a strong focus on the inland temperate rainforest and interior wetbelt biomes , with studies assessing the viability of protected areas for lichen conservation and the ecological roles of ancient western redcedar stands. These works span disciplines such as ecology, biogeography, and environmental management, with subfields including habitat fragmentation, climate resilience, and ecosystem engineering. Dr. Coxson has held leadership roles in academic governance, including serving as past-President of the B.C. Confederation of University Faculty Members (CUFA-BA), representing post-secondary institutions across the province. While no formal scientific awards are listed, his policy impact and editorial contributions to major scientific references underscore his recognition in the field. He is currently accepting graduate students in the MSc and PhD programs in Biology under the NRES umbrella and is available as a media expert on topics related to lichen ecology and forest conservation. His research continues to bridge science and policy, advocating for sustainable management of British Columbia’s unique forest ecosystems.

Tamas MonaView profile

Researcher

• Epidemiology
• Plant Pathology
• Meteorology
• +5 more

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.

Somak DuttaView profile

Associate Professor

• Statistics
• Machine Learning
• Genomics
• +5 more

Somak Dutta is an Associate Professor at Iowa State University conducting interdisciplinary research at the intersection of statistical methodology, machine learning, and agricultural sciences. His work addresses critical challenges in plant breeding, genomics, and environmental modeling through innovative quantitative approaches. His academic foundation includes: PhD in Statistics, University of Chicago, 2015 M.Stat (First Division with Distinction), Indian Statistical Institute, Kolkata, 2010 B.Stat (Honours with Distinction), Indian Statistical Institute, Kolkata, 2008 Dr. Dutta specializes in developing advanced statistical frameworks for high-dimensional data analysis, Bayesian variable selection, and spatial modeling. His research directly impacts plant breeding programs through applications in phenotyping, haploid induction systems, drought response mechanisms, and genetic architecture studies across key crops including maize, soybean, and mungbean. He also contributes to meteorological science through machine learning applications for severe weather verification. Analysis of his 2023-2025 publications reveals two dominant research streams: (1) agricultural applications focusing on genomic selection, phenotyping technologies, and stress response modeling in crops, and (2) meteorological innovations applying machine learning to severe thunderstorm wind verification and precipitation forecasting. Both streams demonstrate his signature approach of developing novel statistical methodologies tailored to domain-specific challenges. No scientific awards were documented in the provided materials. Information regarding student advising, grant funding, laboratory infrastructure, or collaborative teams was not available in the source documentation.

Katharina EggenspergerView profile

Researcher

• Automated Machine Learning (AutoML)
• Hyperparameter Optimization (HPO)
• Tabular Machine Learning
• +1 more

Katharina Eggensperger is an Early Career Research Group Leader at the University of Tübingen , leading the AutoML for Science group within the Cluster of Excellence Machine Learning for Science . She previously completed her Ph.D. at the University of Freiburg under Frank Hutter and Marius Lindauer (2022), and actively contributes to the AutoML community through open-source tool development and competition leadership. Co-developer of AutoML.org tools Faculty member of IMPRS-IS Chair for multiple AutoML workshops/conferences (2019-2025) Her research focuses on automated machine learning (AutoML) with specific attention to: AutoML Systems Hyperparameter Optimization Tabular Machine Learning Scientific Applications of ML She has organized multiple AutoML schools and conferences, including serving as Program Chair for AutoML 2024 and Non-archival Track Chair for AutoML 2025. Her work emphasizes making machine learning accessible through automation while maintaining scientific rigor and interpretability, particularly for tabular data applications. Katharina actively recruits PhD students through IMPRS-IS and collaborates with institutions like the University of Freiburg and Cyber Valley .

Donato RomanoView profile

Associate Professor

• Bioinspired Robotics
• Biomimetic Robotics
• Animal-Robot Interaction
• +8 more

Donato Romano serves as Associate Professor at The BioRobotics Institute of Scuola Superiore Sant'Anna, Italy, where he coordinates the Bio-Robotic Ecosystems Lab and co-founded the spin-off company HUBILIFE srl. His interdisciplinary work bridges robotics, biology, and AI to develop biohybrid systems for biodiversity preservation, sustainable environmental management, and life support in extreme scenarios including space exploration. With over 90 publications and an H-index of 27 (Scopus, March 2025), he has established significant academic leadership through editorial roles across 12+ international journals. Romano's educational foundation includes advanced degrees with honors: an M.Sc. in Agriculture Science and Technologies (2014) and a PhD in BioRobotics (2018), both from Scuola Superiore Sant'Anna. His academic journey includes visiting scholar positions at Khalifa University and substantial industry-academia collaboration through HUBILIFE srl, which commercializes bioinspired devices for human daily life improvement. His research program focuses on bioinspired and biomimetic robotics with particular emphasis on animal-robot interaction, biohybrid systems, and natural intelligence. Key projects address critical global challenges: SENSORBEES develops biohybrid environmental surveillance for ecological monitoring; REGOLIFE investigates lunar soil-terrestrial organism interactions for space agriculture; and OCEAN ROBOCTO explores marine ecosystem solutions. This work demonstrates a strategic progression from fundamental behavioral studies toward applied ecological and extraterrestrial systems. Analysis of his recent publications reveals strong trends in AI-driven behavioral analysis, with deep learning increasingly applied to entomological studies and pest management. The research spans agricultural applications (precision monitoring traps, larval detection systems), ecological conservation (biodiversity surveillance), and extreme-environment adaptation (lunar regolith studies). A distinctive feature is the consistent integration of biohybrid approaches where living organisms and robotic systems create synergistic capabilities exceeding either component alone. Romano's scientific recognition includes election as Junior Fellow of the Italian Academy of Engineering and Technology (2025), the Lucani fuori dal Comune award (2024), and multiple best-thesis prizes. His editorial leadership spans high-impact journals including IEEE Transactions on Medical Robotics and Bionics and Pest Management Science, where he serves as Associate Editor. As principal investigator, Romano coordinates major international projects totaling over €15M in funding: HORIZON-EIC's SENSORBEES (2024-2029), ASI's REGOLIFE (2024-2027), National Geographic's OCEAN ROBOCTO (2024-2026), and PRIN's COSMIC (2023-2025). His teaching portfolio includes PhD courses in Biosystems for Biorobotics and M.Sc. instruction in Bionics Engineering at Scuola Superiore Sant'Anna and University of Pisa. The Bio-Robotic Ecosystems Lab under Romano's direction pioneers biohybrid technologies where living organisms and robotic systems create integrated solutions. Current initiatives include SENSORBEES' environmental monitoring swarms, REGOLIFE's moonworm colonization systems, and HUBILIFE's commercial vector-control devices. The lab maintains active collaborations with space agencies, agricultural institutes, and conservation organizations, positioning biohybrid systems as next-generation tools for planetary-scale challenges.

Camilo MoraView profile

Professor

• Climate Change Impacts
• Biodiversity Conservation
• Environmental Science
• +5 more

Camilo Mora is a Professor in the Department of Geography at the University of Hawaii at Manoa, where he maintains an active research laboratory and teaches courses on environmental issues, biogeography, and data analysis. His academic journey began with a BSc in Marine Biology from Universidad del Valle in Colombia (1999), followed by a PhD in Biology from the University of Windsor, Canada (2005). He completed postdoctoral fellowships at the University of Auckland (2005), Scripps Institution of Oceanography (2006-2008), and Dalhousie University (2008-2010). BSc, Marine Biology, Universidad del Valle, Colombia (1999) PhD, Biology, University of Windsor, Canada (2005) Postdoctoral Fellow, University of Auckland (2005) Postdoctoral Fellow, Scripps Institution of Oceanography (2006-2008) Postdoctoral Fellow, Dalhousie University (2008-2010) Mora's research spans interconnected lines focused on understanding biodiversity patterns and their modification by human activities, with particular emphasis on climate change impacts. His lab specializes in big data analytics applied to diverse environmental challenges including heatwaves, disease transmission, marine ecosystems, and even unconventional topics like Bitcoin's environmental footprint. The Mora Lab operates on a 'divide and conquer' approach to tackle large research questions by breaking data gathering into individual parts that can be concatenated into central databases. Mora has received the CSS Excellence in Research award (2014) for his significant contributions to environmental science. His influential publications include groundbreaking work on the global risk of deadly heat (2017), the projected timing of climate departure from historical variability (2013), and the finding that over half of known human pathogenic diseases can be aggravated by climate change (2022). CSS Excellence in Research (2014) Highly cited publications in Nature and Nature Climate Change Research featured in major international media outlets Development of innovative research methodologies for large-scale analyses Mora leads an active research group that engages students in the full scientific process from idea generation to publication. His approach to mentoring involves creating yearly classes where graduate students, professors, and international advisors collaborate to tackle significant research questions, with papers typically completed within a single semester. His Carbon Neutrality Challenge project, spearheaded by his daughter Asryelle Mora, provides a practical mechanism for individuals to offset carbon emissions through tree planting. The Mora Lab maintains a distinctive approach to environmental research, working on seemingly diverse topics from reef fishes to Bitcoin, united by their reliance on big data analytics. This interdisciplinary methodology has produced impactful research across multiple domains of environmental science and climate change impacts, establishing Mora as a significant contributor to our understanding of humanity's environmental challenges.

• Geomorphology
• Geomorphometry
• Geoinformatics
• +6 more

Leszek Ludwik Gawrysiak is a Professor at the Department of Geology, Soil Science, and Geoinformatics , affiliated with the Faculty of Earth Sciences and Spatial Management at Maria Curie-Skłodowska University in Lublin, Poland. His academic career includes habilitation in Earth and Environmental Sciences (2019), a PhD in Geomorphology (2003), and a master’s in Physical Geography (1993), all from UMCS. Education: Master’s in Physical Geography (1993), UMCS PhD in Geomorphology (2003), UMCS Habilitation in Earth and Environmental Sciences (2019), UMCS His research focuses on Geomorphology , Geomorphometry , and Geoinformatics , with applications in Loess Erosion , Gully Dynamics , and Environmental Risk Assessment . He employs GIS, LiDAR, and remote sensing techniques to analyze terrain segmentation, forest cover changes, and geomorphological impacts on land use planning. Projects include studies on extreme meteorological events, geopark development, and Polish-Belarusian-Ukrainian water policy in the Bug River basin. Recent publications emphasize Loess Landscapes , Proglacial Valley Morphology , and Gully Erosion , with methodological advancements in Digital Terrain Modeling and Geomorphon Analysis . His work bridges computational methods (e.g., GPU-accelerated topographic parameter evaluation) with field-based geomorphological studies in Svalbard and Eastern Europe. Scientific Awards: Award from the Polish Geomorphological Society for best PhD thesis (2002) Team Award from the Rector of UMCS (2010) Individual Award from the Rector of UMCS (2013) He has contributed to understanding Loess Area Geomorphodiversity , Forest Cover Dynamics , and Climate Change Impacts on landscapes. His collaborations span interdisciplinary studies in gully erosion, geotourism, and Holocene soil erosion rates. Contact: leszek.gawrysiak@mail.umcs.pl | Phone: +48 81 537 68 71

Frank CantersView profile

Professor

• Urban Remote Sensing
• GIS Applications
• Urban Form Dynamics
• +3 more

Frank Canters is a Professor of cartography, GIS, and remote sensing at the Department of Geography of Vrije Universiteit Brussel (VUB), leading the Cartography and GIS Research Group. His research focuses on urban remote sensing, spatial modeling of urban environments, and urban ecosystem services. He is renowned for pioneering the Canters projection, a minimum-error world map projection, and has contributed extensively to urban land-use mapping and decision-support systems for urban planning. His work spans over three decades, with 281+ publications and collaborations across multiple disciplines. Key areas include urban form dynamics, remote sensing applications for vegetation and land-use analysis, and spatial justice in green infrastructure distribution. He has supervised 83 students and developed tools like the Q-LavHA plugin for volcanic hazard modeling. Recent research highlights include integrating public perceptions into green space accessibility models, assessing allergenic potentials of urban greenery via LiDAR, and advancing machine learning approaches for urban vegetation mapping. His contributions bridge geospatial technologies with urban sustainability and policy.

Gyula Mate KovácsView profile

Research Fellow

• Remote Sensing
• Wetlands
• Artificial Intelligence
• +6 more

Gyula Mate Kovács is a Research Fellow (Postdoctoral Researcher) at the Department of Geosciences and Natural Resource Management, Faculty of Science, University of Copenhagen. His research is funded by the Novo Nordisk Foundation through the Global Wetland Center. Education Ph.D. in Remote Sensing of Wetlands, University of Copenhagen (2020–2024) M.Sc. in Geography and Geoinformatics, University of Copenhagen (2017–2019) B.Sc. in Environmental Management, Birkbeck University of London (2013–2017) Research Focus Dr. Kovács specializes in AI-driven remote sensing for wetland ecosystem analysis. His work integrates machine learning, deep learning, and satellite data fusion to quantify natural/anthropogenic impacts on wetlands at global scales. Key methodologies include time series analysis, cloud computing, and convolutional neural networks for applications like carbon mapping, water body detection, and land-use impact assessment. Publication Trends His 7 recent publications demonstrate a strong focus on wetland dynamics using satellite remote sensing, with themes spanning deep learning applications (CNN U-Net algorithms), greenhouse gas emissions in croplands, continental-scale wetland inventories, and ecosystem change detection. Research consistently employs advanced AI techniques to address environmental challenges in diverse regions like the Sahel and Europe. Funding & Affiliation Supported by the Novo Nordisk Foundation via the Global Wetland Center, his work advances wetland monitoring capabilities. He collaborates with international teams on projects involving satellite data processing and ecological modeling.

Enoch YeungView profile

Associate Professor

• Systems Biology
• Control Systems
• Machine Learning
• +7 more

Enoch Yeung is an Associate Professor in the Department of Mechanical Engineering at the University of California, Santa Barbara (UCSB). His research focuses on systems biology, control systems, machine learning, and data mining, with a particular emphasis on understanding how mechanical forces in DNA regulate gene dynamics and cell fate. He leads projects on distributed biological computing, data-driven control architectures, and synthetic biological systems design, supported by funding from DARPA, NSF, and the U.S. Army. Yeung holds a PhD in Control and Dynamical Systems from the California Institute of Technology and a BS in Mathematics from Brigham Young University. His work integrates methods from DNA biophysics, synthetic biology, microfluidics, and control theory to study genome organization and cellular decision-making. Recent projects include the DARPA Living Foundries program, the NSF Molecular Programming Project, and the AFOSR Biological Research Initiative. He has received numerous awards, including the NSF Early CAREER Award and Young Investigator Award from the U.S. Army. His lab conducts interdisciplinary research, including a 2024 Summer Synthetic Biology Workshop for high school students. Key research themes include DNA supercoiling dynamics, biophysical feedback control in cells, and scalable Koopman operator methods for analyzing complex biological systems. Lab Focus: Biological Control Lab explores DNA mechanics, synthetic biology, and data-driven modeling. Grants & Collaborations: PI on multi-institutional programs involving PNNL, DARPA, and NSF. Advisory Roles: Served on panels for DARPA, NIST, and the National Defense University.

Joni StorieView profile

Associate Professor

• Geomatics
• Remote Sensing
• GIS
• +6 more

Joni Storie is an Associate Professor in the Geography Faculty at the University of Winnipeg. She holds an office in Lockhart Hall (5L05) and teaches courses including Mapping in a Global World, Intro Remote Sensing, Advanced GIS, and Advanced Remote Sensing. Her research focuses on land-use/land-cover mapping, map automation with machine learning tools, spatial statistics, and terrestrial/aquatic resource management. Teaching expertise spans Regional & Physical Geography, Resource Conservation & Management, and Geomatics (GIS & Remote Sensing). Her work integrates geospatial technologies with environmental challenges, including flood mitigation, mangrove ecosystem analysis, and food environment patterning in urban areas. Research outputs emphasize remote sensing applications in coastal conservation, surface water detection, and vegetation dynamics. Over 13 peer-reviewed articles since 2004 demonstrate sustained academic contributions to geomatics and environmental geography. Current activities include advising on geomatics projects and contributing to the University of Winnipeg’s Geography program infrastructure.

Ed GrantView profile

Professor

• Chemical Physics
• Laser Spectroscopy
• Ultracold Plasmas
• +4 more

Ed Grant is a Professor in the Department of Chemistry at the University of British Columbia (UBC), Faculty of Science. He leads research in chemical physics, focusing on laser spectroscopy, ultracold plasmas, and Raman spectroscopy. B.A., 1969, Occidental College Ph.D., 1974, University of California, Davis Research Interests: Grant's work spans fundamental and applied domains. His team investigates ultracold plasmas using molecular beam techniques, revealing Coulombic interactions and strong correlations. In Raman spectroscopy, they develop instruments for microscale biological sample analysis and employ multivariate classification. Recent projects integrate quantum computing, machine learning, and environmental science (e.g., microplastics' atmospheric impact). Scientific Awards: R&D 100 Award (1998) Fellow of the American Physical Society (1992) Humboldt Research Award (1992, 2012) Kelly Award for Excellence in Undergraduate Teaching (1990) Fulbright Senior Scholar (1988)

Emily BurchfieldView profile

Assistant Professor

• Agricultural Systems
• Land Use Change
• Climate Adaptation
• +4 more

Dr. Emily Burchfield is an Assistant Professor in the Department of Environmental Sciences at Emory University, where she leads the FACES (Food, Agriculture, Climate, Environment, and Sustainability) Lab. Her research integrates social and environmental data to study agricultural sustainability, with projects focused on land use change, climate adaptation, and rural livelihoods. She holds a PhD in Environmental Engineering from Vanderbilt University and MA in Economics from the University of Louvain. Her work examines how agricultural systems adapt to climate change, the characteristics of productive and resilient farming, and drivers of cultivation and conservation behavior. Dr. Burchfield's research combines geospatial analysis with qualitative methods to understand agricultural transitions at multiple scales. Recent publications explore crop diversification, agricultural data practices, and rural livelihoods. Her group develops computational tools for agricultural analysis and collaborates with farming communities to support sustainable transitions.

Harriet D AllenView profile

Professor

• Biogeography
• Environmental Change
• Quaternary Studies
• +4 more

Professor Harriet D Allen is a leading academic in Physical Geography at the University of Cambridge, affiliated with the Department of Geography and Girton College. She holds dual roles as Professor of Physical Geography and Fellow/Tutor at Girton College since 2002. Her research focuses on Mediterranean ecosystems, biogeography, and environmental change with particular emphasis on remote sensing applications for landscape ecology and vegetation dynamics. Education: MA (Cambridge/Girton College), MSc (University of Calgary, Canada), PhD (Cambridge, focusing on Quaternary studies in Greece). She has held academic positions since 1986, including Senior Lecturer roles at Homerton College and current roles in Cambridge's Geography Department. Research Interests: Modeling Mediterranean shrubland ecosystems using LiDAR and multisensor data Vegetation response to Holocene and contemporary environmental changes Restoration of Mediterranean mosaic landscapes Ecological impacts of land use changes in Portugal and Greece Palaeoecological reconstruction using sedimentary records Advising & Grants: Supervised 3 PhD students (Amy McGuire, William Fletcher, William Simonson) focusing on Quaternary environments, forest structure, and landscape history. Active in curriculum development as Director of Undergraduate Teaching (2014–2022). Labs/Teams: Member of Climate & Environmental Dynamics and Biogeography & Biogeomorphology research groups. Collaborates with Plant Sciences Department on lidar applications. Leads fieldwork in Portugal, Switzerland, and Greece.

Anandamayee MajumdarView profile

Assistant Professor

• Spatial Processes
• Bayesian Computation
• Environmental Sustainability
• +7 more

Anandamayee Majumdar is an Assistant Professor in the Department of Mathematics at San Francisco State University (SFSU), part of the College of Science & Engineering. She holds a Ph.D. and M.S. in Statistics from the University of Connecticut and Michigan State University, respectively, and earlier degrees from the Indian Statistical Institute (I.S.I.). Her research focuses on spatial and spatio-temporal processes, Bayesian computation, and their applications in biology, health, environmental sustainability, ecology, economics, finance, and industry. She has developed robust statistical models for handling missing data, multivariate processes, and expert-informed modeling, particularly in contexts like tuna catch estimation during the pandemic and financial risk analysis. She is currently exploring expert-integrated spatio-temporal models and public health trends. Professional experience includes roles as Senior Statistician at the Inter-American Tropical Tuna Commission (2021–2023), Professorial positions at universities in Bangladesh and China, and visiting research at UC Davis. She serves as Associate Editor for Applied Stochastic Modeling in Business and Industry and reviews for journals like Computational Statistics and Data Analysis and Biostatistics . Majumdar has contributed to interdisciplinary collaborations, including soil property modeling in urban ecosystems, and has held leadership roles in academic committees, such as the Interdisciplinary M.S./Ph.D. programs at Arizona State University. She actively mentors students and seeks to involve undergraduates and graduates in research projects.