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Zeynep Işıl KalaylıoğluView profile

Professor

• Bayesian Statistics
• Environmental Statistics
• Health Statistics
• +3 more

Prof. Zeynep Işıl Kalaylıoğlu is a Professor of Statistics at the Department of Statistics, Middle East Technical University (METU), Ankara, within the Faculty of Arts and Sciences. She holds a Ph.D. in Statistics from North Carolina State University (2002) and has held roles including Associate Professor (2014–2022), Assistant Professor (2009–2014), and researcher at the National Cancer Institute (2002–2007). She has served in administrative roles such as Assistant to the Department Head and member of METU’s Wind Energy Research Center and Faculty Board. Ph.D.: Statistics, North Carolina State University, 2002 M.S.: Statistics with Computational Engineering minor, North Carolina State University, 1999 B.S.: Statistics with Computer Engineering minor, Middle East Technical University, 1995 Her research focuses on Bayesian statistical methodologies for environmental and health phenomena. Key areas include spatial/temporal modeling of atmospheric and ecological variables, prediction of migratory patterns (e.g., wind direction, bird movements), and risk modeling for breast cancer using mammogram data. She develops flexible models for circular and extremal data, emphasizing applications in ecology, epidemiology, and environmental science. Her recent publications address topics like goodness-of-fit tests for statistical distributions, predictive model selection for circular data, and Bayesian approaches for missing covariates in generalized linear models. Current projects include mobile apps for olive harvest optimization and frost预警 systems, reflecting her commitment to applied statistical solutions. Labs/Teams: She leads the BayeZian Research Group, collaborating with METU’s Ecosystem Research Center on interdisciplinary projects. Her teaching expertise spans mathematical statistics, Bayesian theory, and statistical inference at undergraduate and graduate levels.

Zoran ObradovicView profile

Professor

• Bioinformatics
• Healthcare informatics
• Data mining
• +12 more

Zoran Obradovic holds the prestigious L.H. Carnell Professorship of Data Analytics at Temple University where he serves as Professor in the Computer and Information Sciences Department and the Statistics Department. He also directs the Center for Data Analytics and Biomedical Informatics and maintains secondary appointments at Temple's Fox School of Business. Internationally, he serves as Research Professor at The Mathematical Institute of the Serbian Academy of Sciences and Arts, and as Visiting Professor at both the School of Medicine and School of Management at the University of Belgrade. His research spans multiple cutting-edge domains of data science: Bioinformatics and protein disorder prediction Healthcare informatics and clinical decision support systems Machine learning for complex networks and big data Spatial and temporal data analytics Applications in healthcare management, social networks, and earth science Dr. Obradovic pioneered research on intrinsically disordered proteins, earning multiple CASP awards. His work addresses challenges related to heterogeneous, spatial, and temporal data analytics with applications across healthcare, power systems, earth science, and social sciences. His research has been funded by prestigious organizations including NIH, NSF, DARPA, DOE, and industry partners. With approximately 450 publications and an H-index of 68 (over 33,000 citations), his scholarly impact is substantial. He serves as editor-in-chief of the Big Data journal and chairs the SIAM Data Mining conference steering committee, reflecting his leadership in the field. Scientific Recognition Elected Member of Academia Europaea (2015) Foreign Member of Serbian Academy of Sciences and Arts (2015) Asia-Pacific Artificial Intelligence Association Fellow (2021) Multiple best paper awards at international conferences Temple University's President's Outstanding Faculty Research Award (2009) Three consecutive CASP awards for protein structure prediction (2002-2006) Dr. Obradovic has mentored approximately 50 postdoctoral fellows and Ph.D. students, many of whom now hold positions at leading academic institutions and tech companies including Amazon, Facebook, IBM, Microsoft, and Uber. He has served on editorial boards for 13 journals and organized numerous international conferences in data mining and bioinformatics. His Center for Data Analytics and Biomedical Informatics develops advanced data science methods addressing real-world challenges in healthcare, science, engineering, and business applications, with active recruitment for Ph.D. students and postdoctoral researchers.

Peter ButcherView profile

Lecturer

• Immersive Analytics
• Human-Computer Interaction
• Data Visualization
• +4 more

Peter Butcher is a Lecturer in Human-Computer Interaction at Bangor University's School of Computer Science and Engineering. With a PhD in Computer Science from the University of Chester, he specializes in visualization techniques and immersive analytics, particularly focusing on Virtual Reality, Augmented Reality, and WebXR platforms. 2015-2020: PhD, Computer Science, University of Chester 2014-2015: MSc, Computer Science, Bangor University 2011-2014: BSc, Computer Science, Bangor University His research interests center on Immersive Analytics , Human-Computer Interaction , and Data Visualization . He explores how contextual awareness and multivocality in visualization can enhance user experience and data interpretation. His work spans from technical frameworks like WebXR to applications in e-lexicography and flood risk management. Recent publications highlight his contributions to collaborative platforms ( DashSpace ), attention-aware systems ( Attention-Aware Visualization ), and magic-inspired tools ( Wizualization ). He also investigates educational applications of visualization, particularly in critical thinking development. Scientific achievements include the Best Full Papers Honourable Mention at IEEE VIS 2021 and recognition as a Fellow of the Higher Education Academy (FHEA) via Bangor University's CPD Recognition Scheme. He actively supervises doctoral students in areas like AI for Legal Technologies and Multivocality in Visualization. Peter contributes to teaching modules on Web Technologies , Game Production , and High Performance Computing . He also co-founded Sim Broadcasts and serves as Chairman of Rethink Racing , demonstrating his engagement beyond pure academia.

• Statistical Physics
• Earthquake Fault Systems
• Computational Physics
• +4 more

Rachele Dominguez is an Associate Professor of Physics at Randolph-Macon College in Ashland, Virginia, where she teaches a broad range of courses including introductory physics, quantum mechanics, computational physics, and special topics like the physics of light and the atomic bomb. She holds a PhD in Physics from Boston University (2010), an MS from the University of Washington (2004), and a BS from the College of William and Mary (2002) in Physics and Philosophy. Her research focuses on statistical physics, particularly computational simulations of phase transitions and earthquake fault systems. Notable projects include modeling spatial symmetry breaking, earthquake fault dynamics, and complex networks. She has also pioneered coastal storm impact studies, developing the Cumulative Storm Impact Index (CSII) to assess beach erosion along the U.S. East Coast. Dr. Dominguez has been recognized with awards such as the Distinguished Chapter Award (2024), Omicron Delta Kappa Outstanding Advisor Award (2021), and the Frank Haig Prize (2015). Her teaching spans foundational courses to advanced labs and independent studies, emphasizing hands-on research and interdisciplinary problem-solving. Her work bridges computational methods with real-world applications, including collaborations on geophysical modeling and STEM education initiatives to recruit underrepresented students in the sciences.

Jin RuiView profile

Researcher

• Geographic Information Science
• Urban Artificial Intelligence (GeoAI)
• Spatial Data Science
• +5 more

Dr. Jin Rui is a Postdoctoral Research Associate at King’s College London’s Department of Geography within the School of Global Affairs, Faculty of Social Science & Public Policy. He holds a PhD in Spatial Planning (2024, Technical University of Dortmund), an M.Sc. in Architecture and Urban Planning (2020, Leibniz University Hannover), and a B.Sc. in Architecture (2018, China Academy of Art). His research focuses on spatial data science, urban AI, and GeoAI applications in smart cities and risk management. Key research areas include urban visual intelligence, GeoAI for disaster analysis, and quantitative urban planning using big data. He leads projects like the British Academy-funded Sinking Cities initiative and collaborates on digitalization and public health. He serves as a guest editor for Land and reviews for journals like Nature Cities . His work bridges theory and practice, offering policy insights on urban renewal, pedestrian-centered design, and sustainable mobility. He has delivered lectures at the University of Hong Kong and China Academy of Art on AI-driven urban planning.

Yohei KATOView profile

Research Fellow

• Community Development
• Urban Studies
• Empowerment
• +8 more

Yohei Kato is a Research Fellow at the Lee Kuan Yew Centre for Innovative Cities, Singapore University of Technology and Design (SUTD). He holds a PhD in Architecture and Sustainable Design (SUTD, 2023), an MSc in Community Development (University of California, Davis, 2015), and a BA in International Development (University of Tsukuba, 2013). His research focuses on community engagement, urban sustainability, and participatory methodologies. Key areas include empowerment mechanisms, mixed-methods research, social network analysis, and youth participation in urban design. He supports projects such as the 'Integrated Socio-Temporal Study of Outdoor Recreation Spaces in Singapore' and has contributed to initiatives in Japan, India, Bangladesh, and the US. Recent work explores how outdoor spaces influence social interactions and wellbeing, as well as strategies for inclusive built environments through participatory approaches. Education: PhD in Architecture and Sustainable Design (SUTD, 2023) MSc in Community Development (UC Davis, 2015) BA in International Development (University of Tsukuba, 2013) Research Themes: Community development and empowerment Urban design for inclusivity Photovoice & participatory methods Social network analysis Youth & children's participation Outdoor spaces and wellbeing Key Projects: Outdoor Recreation Spaces in Singapore study Placekeeping initiatives in Japan Landscape democracy analysis along Singapore’s Rail Corridor His work bridges academic research and practical urban planning, emphasizing collaborative frameworks to address contemporary challenges in community development and sustainable design.

• Applied Econometrics
• Applied Statistics
• Housing Economics
• +3 more

Ranjodh Singh is a Senior Lecturer at the School of Accounting, Economics and Finance within the Faculty of Business and Law at Curtin University. He holds a BSc (Hons) and PhD in disciplines relevant to his research focus. His teaching responsibilities include undergraduate and postgraduate courses in Data Analytics and Econometrics, and he supervises Honours, Masters, and PhD students in these areas. Ranjodh’s research interests center on Applied Econometrics , Applied Statistics , and Housing Economics . His work explores topics such as housing market dynamics, policy impacts on mental wellbeing, Indigenous mobility, and nonlinear econometric modeling. Recent studies include analyzing rental subsidy effectiveness, cannabis-tobacco consumption linkages, and post-pandemic housing demand shifts. His publications span leading journals like Housing Studies , International Journal of Housing Policy , and Journal of Population Economics . He frequently collaborates with researchers across disciplines, including economists, statisticians, and sociologists. His research has addressed policy-relevant issues such as rental affordability, remote infrastructure planning, and pandemic-driven economic shifts. Ranjodh’s contributions extend to major research initiatives like the AHURI Final Reports series, focusing on housing stress and Indigenous community needs. His methodologies blend traditional econometrics with machine learning advancements, as seen in his work on nonlinear models and forecast combinations.

Ruben ValbuenaView profile

Professor

• Remote Sensing
• LiDAR
• Forest Structure
• +7 more

Ruben Valbuena is a Professor at Bangor University, affiliated with the School of Natural Sciences and the Department of Forest Sciences. He is also recognized as an Honorary Professor, reflecting his significant contributions to forest science and remote sensing. His research leverages big data, particularly LiDAR and remote sensing, to analyze ecosystem structure, carbon stocks, and habitat suitability at landscape and community levels. His research interests lie at the intersection of ecology, remote sensing, and forest dynamics. He has pioneered the adaptation of Lorenz curves to quantify forest structural complexity, a methodological innovation recognized with the IUFRO 2019 Outstanding Doctoral Research Award. His work spans tropical and boreal forests, focusing on aboveground biomass estimation, forest disturbance detection, and ecosystem service modeling. He actively integrates airborne and satellite data, including NASA's GEDI mission, to develop scalable ecological models. The recent publications (2017–2023) reflect a consistent focus on LiDAR applications, forest structure, biomass modeling, and ecological theory. Key themes include the fusion of remote sensing technologies, the development of structural complexity indices, and the application of machine learning in forest inventory. His research increasingly addresses global challenges such as carbon monitoring, urban greening, and sustainable forest management. His scientific honors include: International Union of Forest Researchers (IUFRO) Outstanding Doctoral Research Award (2019) Early-Stage Researcher Prize “José L. Labrandero” (2017) Valbuena leads multiple research projects, including the European Forest Information Network (EFINET), AMAZECO (focused on Amazon ecosystem structure), and a KESS II PhD project with Forest Research. He has supervised at least one research student and maintains active collaborations across Europe and the Americas. His work is supported by grants from national and international funding bodies, enabling high-impact research in forest ecology and remote sensing. He is associated with key research initiatives and labs focused on remote sensing and forest ecosystem dynamics, contributing to large-scale projects that integrate field data with satellite and airborne observations.

Mateusz ZawadzkiView profile

Assistant Professor

• Historical GIS (HGIS)
• Spatial Humanities
• Old-Polish communication networks
• +3 more

Mateusz Zawadzki is an Assistant Professor at the Department of Geomatics and Cartography, Faculty of Earth Sciences and Spatial Management, Maria Curie-Skłodowska University (UMCS). He holds a Ph.D. in Geography (2019, UMCS) and an MA in History (2011, KUL). His career spans roles at UMCS (2017–present), GIS-Expert Sp. z.o.o. (2012–2017), and leadership in the "GIS across the border" research team (2013–2014). Education: Ph.D. in Geography (UMCS, 2019), MA in History (KUL, 2011) Employment: Assistant Professor (UMCS, 2021–present), Research Associate (UMCS, 2017–2021) His research focuses on Historical GIS (HGIS), Spatial Humanities, and reconstruction of Old-Polish communication networks using Web-GIS tools. He has contributed to digital repositories like Polegli1939.pl , analyzed 19th-century Polish military cartography, and explored WWII impacts on Białowieża Forest through interdisciplinary lenses. Recent publications address methodological challenges in multi-sheet historical map georeferencing and metadata frameworks for post-Paris Peace Conference boundary studies. He teaches GIS procedures, Web-GIS applications, and coordinates geoinformatics studies at UMCS. As a consultant for the "GIS in history" Dialog project (2018–2020) and coordinator of the DARIAH-PL digital infrastructure initiative (2021–2024), he bridges geospatial technology with humanities research. Collaborative works include Roman artifact mapping in Krajna region and 3D archaeological site modeling.

• Watershed Modeling
• Water Quality
• Agricultural Ecosystems
• +7 more

Rebecca Muenich is an Associate Professor in the Department of Biological & Agricultural Engineering at the University of Arkansas. Her research bridges watershed modeling, agricultural ecosystems, and the food-energy-water nexus, with a focus on surface hydrology, water quality, and climate impacts. She holds a Ph.D. (2015) and M.S. (2011) in Agricultural & Biological Engineering from Purdue University, and a B.S. in Biological Engineering (2009) from the University of Arkansas. Her research explores watershed and environmental modeling, agricultural management, urban agriculture, and climate impacts on water resources. Key interests include mitigating nutrient pollution, enhancing ecosystem services, and developing sustainable land-use strategies. Recent publications emphasize machine learning applications in environmental monitoring, phosphorus circularity, and climate-resilient water management. Muenich leads significant grants including a USDA NRCS project on PFAS in agriculture (2023-2027), NSF-STC’s Science and Technology for Phosphorus Sustainability (2021-2031), and DISES research on cyanobacterial blooms (2022-2025). She mentors students in her research group (Muenich Lab) and collaborates on interdisciplinary projects. Lori Libbert New Faculty Commendation (2024) Early Career Alumni Award, UA Engineering (2022) New Face of ASABE (2020) National Science Foundation Graduate Research Fellowship (2009)

Markus SchartauView profile

Researcher

• Marine Biogeochemical Modeling
• Plankton Dynamics
• Ocean Ecosystem Modeling
• +7 more

Markus Schartau is a Researcher in the Biogeochemical Modelling Research Unit at GEOMAR Helmholtz Centre for Ocean Research Kiel, where he has worked since 2013. His research focuses on marine biogeochemical modeling, plankton dynamics, and parameter optimization in ecosystem models. With over 69 publications spanning two decades, Schartau has established himself as a leading expert in marine biogeochemical modeling, particularly in the areas of model calibration, mesocosm experiment simulation, and plankton community dynamics. His research interests encompass uncertainty and trustworthiness of biogeochemical model results, species composition and size frequency structures of plankton, methods of parameter optimization and model selection, simulations of mesocosm experiments, physiological and ecological variations of plankton, and temporal and spatial variations of organic substances in coastal ocean areas and estuaries. Schartau's work often bridges theoretical modeling with experimental observations to improve our understanding of marine biogeochemical processes. The analysis of his recent publications (2020-2024) reveals a strong focus on marine biogeochemical modeling, with particular emphasis on plankton dynamics, carbon cycling, and the impacts of environmental change. His work spans multiple spatial scales from coastal systems to the global ocean and integrates approaches from data science, biogeochemistry, and ecosystem modeling. Key themes include model calibration techniques, mesocosm experiment analysis, marine particle dynamics, and the effects of ocean acidification on biogeochemical processes. Schartau actively participates in major research projects including OceanNETs (EU project), BASS (funded by DFG), ICEBERG (EU project), and μARC (funded by BMBF), demonstrating his integration into the international marine science community. His collaborative approach is evident in his extensive co-authorship network across multiple institutions and countries. His career trajectory shows progression from postdoctoral positions at Stony Brook University and the Alfred Wegener Institute to permanent research scientist roles at Helmholtz-Zentrum Geesthacht (now HEREON) and finally at GEOMAR. This path reflects his growing expertise and recognition in the field of marine biogeochemical modeling.

• High resolution Earth gravity field modeling
• Satellite gravimetry
• Time-variable gravity field analysis
• +13 more

Dr. Thomas Gruber is an Academic Director at the Institute for Astronomical and Physical Geodesy, Technische Universität München (TUM), where he leads research in high-resolution Earth gravity field modeling and satellite gravimetry. He is actively involved in major international projects including ESA’s GOCE, MAGIC, and QSG4EMT, as well as DFG-funded initiatives like NEROGRAV and UPLIFT. His work bridges theoretical geodesy with practical Earth observation applications. His primary research interests include: High-resolution gravity field modeling Satellite and quantum gravimetry Time-variable gravity and geophysical mass transport Sea level studies and altimetry Geodetic SAR for height system unification Future gravity mission concepts His recent publications focus on next-generation satellite missions, quantum sensors, and the integration of satellite and terrestrial gravity data. Trends indicate a strong emphasis on improving temporal and spatial resolution of gravity field models, with applications in climate monitoring, hydrology, and oceanography. He plays a key role in defining Essential Geodetic Variables (EGVs) and advancing global geodetic infrastructure through GGOS. Scientific contributions include leadership in: Development of global gravity models (e.g., XGM, GOCO) GOCE mission data processing and validation ESA and DFG project coordination International collaboration through IAG and GGOS He advises doctoral and master’s students and participates in national and international grant-funded research. He leads or contributes to teams working on: Gravity field combination and error modeling Quantum sensor simulation (CARIOQA-PMP) Geodetic SAR applications Sea level and mass transport analysis

• Agent-Based Modelling
• Urban Energy Systems
• Sustainable Development
• +6 more

Koen Van Dam is a Research Fellow at Imperial College London's Department of Chemical Engineering, part of the Urban Energy Systems group within the Faculty of Engineering. His work focuses on agent-based modelling of socio-technical systems to support decision-making in urban energy and transport infrastructure design. He leads the SEF05 Urban Energy Systems module in the Sustainable Energy Futures MSc program and co-organizes computational social science summer schools. Koen has held visiting researcher positions at the National University of Singapore and TU Delft, and previously served as president of Eurodoc (European council for doctoral candidates). Education: MSc in Artificial Intelligence (Vrije Universiteit Amsterdam), PhD from TU Delft (2009) with thesis on agent-based modelling of socio-technical systems. Research interests emphasize integrating spatial/temporal data across energy and transport sectors to model urban systems at multiple scales. Projects include: FCDO Climate Compatible Growth (CCG) project COP26 Rapid Response Facility technical lead EPSRC-funded Digital City Exchange (DCE) and IDLES projects resilience.io (DFID project) Key contributions include decision support tools for: Electric vehicle infrastructure planning Low-carbon energy systems Smart district design Post-pandemic urban resilience Awards: None explicitly listed, though his extensive project leadership indicates recognition in sustainability research. Advising: Supervised over 40 MSc/MEng projects on smart cities, energy demand, EVs, bioenergy, and resilient infrastructure. Active in education through master's course leadership and international summer schools. Labs/Teams: Affiliated with Energy Futures Lab, Network of Excellence in Air Quality, and the Artificial Intelligence Climate Compatible Growth initiative.

Mathias KneubühlerView profile

Senior Lecturer

• Remote Sensing
• Imaging Spectroscopy
• Earth Observation
• +7 more

Mathias Kneubühler is a Senior Lecturer and Scientific Section Head of Remote Sensing Spectroscopy at the Department of Geography, Faculty of Science, University of Zurich. He leads the Spectroscopy Lab and has been a key figure in advancing imaging spectroscopy and Earth observation research. He is actively involved in international remote sensing initiatives, including serving as the Swiss ESA-DOSTAG Delegate and Co-Chair of the EARSeL Special Interest Group on Imaging Spectroscopy. PhD in Remote Sensing, University of Zurich (1997–2002) MSc in Geography, University of Zurich (1992–1996) His research focuses on imaging spectroscopy , spectro-directional measurements , and ecosystem monitoring , with applications in plant phenology , biodiversity assessment , and land surface dynamics . He investigates how multi-angular and hyperspectral data can improve the understanding of vegetation structure, function, and environmental responses. His work integrates field spectroscopy, airborne and satellite remote sensing, and advanced data processing techniques. The recent publications highlight a strong trend in imaging spectroscopy for ecological applications, including plant trait mapping , camouflage detection , tree species identification , and phenology modeling . These studies often involve UAV and satellite data fusion, BRDF correction, and machine learning, demonstrating interdisciplinary innovation in remote sensing science. Co-Chair, EARSeL Special Interest Group on Imaging Spectroscopy (2016–present) President, Swiss Commission for Remote Sensing (2015–2020) Swiss ESA-DOSTAG Delegate (2004–2024) He has supervised several PhD and Master’s students, including Marius Vögtli, Christian Rossi, and Mojdeh Miraki, contributing to the next generation of remote sensing scientists. His leadership in organizing scientific workshops and campaigns underscores his role in fostering collaborative research. He is associated with the Spectroscopy Lab at the University of Zurich, which conducts cutting-edge research in spectro-directional measurements and environmental monitoring.

Frank KeutschView profile

Professor

• Atmospheric Chemistry
• Air Quality
• Climate Intervention/Geoengineering
• +6 more

Frank Keutsch is the Stonington Professor of Engineering and Atmospheric Science in the Paulson School of Engineering and Applied Sciences and Professor of Chemistry and Chemical Biology at Harvard University. He holds a joint appointment in both departments and is also a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study (TUM-IAS), where he collaborates with Prof. Jia Chen on air pollution and climate research since 2021. Dr. Keutsch received his PhD in Physical Chemistry from the University of California Berkeley and his Diplom in Chemistry from TU Munich. His academic journey bridges European and American institutions, reflecting his international research perspective and expertise in both fundamental chemistry and applied environmental science. Professor Keutsch's research focuses on understanding atmospheric chemical processes, particularly those related to air quality and climate change. His work combines laboratory experiments, field observations, and modeling to investigate fundamental mechanisms of anthropogenic influence on atmospheric composition. He specializes in photochemical oxidation processes of volatile organic compounds (VOCs) that produce tropospheric ozone and secondary organic aerosols (SOA), which affect human health and climate. His research spans from urban areas to remote tropical forests, from tropical oceans to polar regions, addressing critical environmental challenges across diverse spatial and temporal scales. His recent publications demonstrate a strong focus on air pollution monitoring, climate intervention strategies, and the development of novel measurement techniques. The research shows an increasing integration of machine learning approaches with traditional atmospheric science methods, as well as a growing emphasis on global applications of pollution monitoring technologies and the health impacts of atmospheric pollutants. 2015, LFUI Guest Professorship 2014, Vilas Mid-Career Investigator Award 2013, Vilas Associate Award 2012, Honored Instructor Award 2006, Camille and Henry Dreyfus Award Postdoctoral Program in Environmental Chemistry 2005, Camille and Henry Dreyfus New Faculty Award Hans Fischer Senior Fellowship (2021) As an active mentor, Professor Keutsch is accepting graduate students into his research group. His laboratory develops cutting-edge instrumentation for atmospheric measurements, including the FILIF (Formaldehyde Instrument using Laser-Induced Fluorescence), CHOCHO LIP (Laser-Induced Phosphorescence), EDB-MS (Electrodynamic Balance Mass Spectrometry), and DPOPS systems. These instruments have been deployed in numerous field campaigns across diverse environments worldwide, from forests in Michigan and Colorado to the Amazon rainforest and even Antarctica. His group's work on stratospheric aerosols, particularly related to climate intervention strategies, has gained significant attention in the scientific community.