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Alemu Gonsamo GosaView profile

Associate Professor

• Remote Sensing
• Climate Change Impacts
• Carbon Cycle Modeling
• +3 more

Dr. Alemu Gonsamo Gosa is an Associate Professor and Canada Research Chair in Remote Sensing of Terrestrial Ecosystems at McMaster University's School of Geography & Earth Sciences. His research program focuses on advanced remote sensing techniques to study vegetation dynamics, carbon cycling, and climate change impacts across scales from leaf-level to global systems. Educational background includes a B.Sc. from Debub University, M.Sc. from Wageningen University, and Ph.D. from the University of Helsinki. Research integrates ground measurements, satellite data, and ecosystem modeling to address: Plant structural and photosynthetic traits quantification Land surface phenology and carbon uptake dynamics Terrestrial primary productivity assessment Global change impacts on ecosystem functioning Carbon cycle modeling and climate feedbacks Publications demonstrate consistent focus on developing novel remote sensing methodologies, with recent work emphasizing machine learning applications, large-scale carbon mapping, and climate-ecosystem interactions. The 15 most recent articles show strong trends in: forest biomass estimation, peatland carbon storage, climate-vegetation interactions, and sustainable land management solutions. Honors include the prestigious Canada Research Chair position recognizing groundbreaking work in terrestrial ecosystem monitoring. Research utilizes extensive field networks including eddy covariance towers and collaborates with global modeling initiatives. Leads the Remote Sensing of Terrestrial Ecosystems laboratory, which develops cutting-edge methods using multi-sensor approaches (satellite, airborne, ground-based) and maintains international partnerships for large-scale ecosystem monitoring.

Daniel BryantView profile

Researcher

• Atmospheric Chemistry
• Analytical Chemistry
• Air Pollution
• +3 more

Daniel Bryant is a researcher focused on atmospheric aerosol chemistry and analytical chemistry, particularly investigating organic aerosol composition, health impacts, and methodological advancements. His work addresses global air quality challenges, aiming to quantify and characterize pollutants like PM2.5. He is affiliated with a postdoctoral project under the NERC-funded HIPTox initiative, a cross-disciplinary collaboration exploring pollution's neurological and cognitive effects. His research employs advanced techniques such as LC-ESI-HRMS and atmospheric flow reactors to analyze organic aerosol formation pathways and sources. He has developed methodologies to improve quantification accuracy and links pollutant sources to health outcomes. Bryant's work spans global locations, including Delhi and Beijing, studying both biogenic and anthropogenic contributions to air pollution. Publications highlight innovations in non-target analysis, toxicity predictions via machine learning, and combustion chemistry insights. His collaborative projects integrate atmospheric chemistry, epidemiology, and toxicology, reflecting a commitment to addressing environmental health challenges through multidisciplinary approaches.

Pengfei LiuView profile

Assistant Professor

• Atmospheric Chemistry
• Aerosols & Clouds
• Paleoclimate
• +3 more

Pengfei Liu is an Assistant Professor in the School of Earth & Atmospheric Sciences at the Georgia Institute of Technology (Georgia Tech), within the College of Sciences. His research focuses on atmospheric chemistry and aerosols, particularly their roles in climate interactions and air quality. He holds a Ph.D. in Environmental Science and Engineering from Harvard University (2017), an M.S. in Atmospheric Physics and Environment from Peking University (2011), and a B.S. in Atmospheric Sciences from Peking University (2008). Dr. Liu’s research interests span aerosol-climate interactions, organic particulate matter properties, and biomass burning emissions across timescales. He investigates how atmospheric aerosols influence cloud formation, fog microphysics, and long-term environmental changes using laboratory experiments and advanced modeling techniques. His work also addresses mercury emissions in India, regional air quality policies, and the health impacts of air pollution exposure in older populations. His publications highlight innovative approaches to measuring aerosol hygroscopicity, refining emission inventories, and exploring the chemical reactivity of particles under varying environmental conditions. Notably, he has contributed to improving historical biomass burning emission estimates using ice core data and inverse modeling, with implications for global climate forcing. Collaborations involve interdisciplinary projects linking atmospheric chemistry, public health, and machine learning. Though no specific advisees or awards are listed, his research is supported by grants addressing topics such as aerosol optical properties, regional climate dynamics, and environmental health disparities. He actively engages in field studies and model development to advance understanding of anthropogenic and natural aerosol processes.

• Optical Communications
• Fiber Optics
• Nonlinear Optics
• +3 more

Peter Andrekson is a Full Professor and Head of Division at the Department of Photonics, Microtechnology and Nanoscience, Chalmers University of Technology. He holds a Ph.D. from Chalmers (1988) and has worked at AT&T Bell Laboratories (1989–1992), Cenix Inc., and Lehigh University's Center for Optical Technologies. His research focuses on fiber communications, optical amplification, nonlinear optics, and high-capacity transmission systems. Andrekson has co-founded Picosolve Inc. (now part of EXFO) and served as Director of EXFO Sweden AB. He is a Fellow of the Optical Society of America and IEEE, and a member of the Royal Swedish Academy of Engineering Sciences (IVA). He has authored ~500 publications, including 100 invited papers and four OFC tutorials. Notable awards include the 2000 Telenor Nordic Research Award and a 1993 Swedish government award for young scientists. His technical leadership roles include Board Member of the IEEE Photonics Society, ECOC Chair (2017), and expert evaluator for the Nobel Prize in Physics. His work spans optical parametric amplifiers, microcombs, and free-space optical communication systems, with applications in high-speed data transmission and analog photonics.

Ranjini SwaminathanView profile

Research Fellow

• Climate Science
• Earth System Modeling
• Machine Learning Applications in Climate Research
• +3 more

Dr. Ranjini Swaminathan is a Research Fellow in the Meteorology Department at the University of Reading, serving as a Core Scientist for the NCEO UK Earth System Model (UKESM). Her research focuses on advancing Earth system modeling, particularly in climate sensitivity, machine learning applications for vegetation modeling, and ocean-climate interactions. She contributes to interdisciplinary studies on global warming thresholds, carbon cycle projections, and model evaluation frameworks like ESMValTool. Her work bridges climate science with computational methods, addressing critical questions in regional climate impacts and extreme weather prediction. Swaminathan’s expertise includes developing and validating Earth system models, collaborating on initiatives such as the UKESM project and the CMIP framework. She has published extensively on topics including climate extremes, AI in weather forecasting, and terrestrial biome classification through explainable clustering techniques. Her office is located in Harry Pitt Building, Room HP177. While no scientific awards are explicitly listed, her contributions to climate science have advanced understanding of future climate scenarios and model reliability. She has not listed advisees, but her work involves collaborative projects with international research teams.

Paola CrippaView profile

Assistant Professor

• Air Quality
• Aerosol Dynamics Modeling
• Climate Change
• +7 more

Paola Crippa is an Assistant Professor in the Department of Applied and Computational Mathematics and Statistics at the University of Notre Dame, College of Science. Her research focuses on air quality, aerosol dynamics, climate change, and wind energy, leveraging advanced computational models like WRF-Chem and large eddy simulations (LES). She holds a Ph.D. in Atmospheric Science from Indiana University-Bloomington (2013), and M.S. and B.S. degrees in Environmental Engineering from Politecnico di Milano, Italy (2007 and 2005). Her work integrates high-performance computing with atmospheric processes, exploring topics such as urban climate impacts, aerosol-cloud interactions, and extreme weather events. Notable contributions include studies on Sundowner events, wind energy potential in complex terrain, and the role of urbanization in deep convection. Research interests span multiscale modeling, environmental justice in air pollution epidemiology, and the application of machine learning (e.g., echo state networks) for weather forecasting. She actively participates in interdisciplinary projects like the Perdigão field campaign, addressing wind energy and turbulence dynamics. Her publications emphasize quantifying uncertainties in climate impacts, optimizing wind energy assessments, and understanding human health risks from air pollutants. Despite no explicitly noted awards or grants in the provided text, her extensive publication record reflects sustained contributions to atmospheric science and computational methods.

Maria HelgueraView profile

Adjunct Professor

• Medical Imaging
• Biomedical Engineering
• Ultrasound Technology
• +4 more

Maria Helguera is an Adjunct Professor in the Department of Electrical and Computer Engineering at the Hajim School of Engineering & Applied Sciences, University of Rochester. Her research focuses on biomedical imaging technologies, including ultrasound characterization, image registration algorithms, and biomechanical modeling of vascular systems. She has contributed to advancements in lung nodule tracking, abdominal aortic aneurysm severity assessment, and brain atrophy detection in Alzheimer's disease. Her work spans multiple interdisciplinary areas: medical imaging (e.g., CT/MRI fusion, quantitative ultrasound), material science (edible coatings, collagen analysis), and optical engineering (diffraction-based sensors, coherence elastography). Key themes include developing automated methods for clinical image analysis and translating engineering principles to biomedical applications. Publications reflect a strong emphasis on translational research, with applications in cancer monitoring, vascular disease modeling, and food preservation. Though no awards are explicitly listed, her prolific output (over 40 publications since 1990) indicates sustained academic contribution. Advising and grant details are not provided in available materials.

Catherine KimView profile

Research Fellow

• Marine Science
• Coral Reef Conservation
• Data Science Applications in Ecology
• +3 more

Catherine Kim is a Postdoctoral Research Fellow at the School of Earth & Atmospheric Sciences. She focuses on marine science, particularly coral reef restoration and adaptation, leading projects like the Reef Restoration and Adaptation Program (Rubble and Decision Science sub-programs) alongside Professors Scott Bryan and Michael Bode. Her work includes predicting coral rubble dynamics on the Great Barrier Reef and developing a flood vulnerability index for Brisbane City with Dr Kate Saunders and Associate Professor Kate Helmstedt. She earned her PhD in marine science from the University of Queensland, where her research explored coral health and biodiversity in Timor-Leste. Dr. Kim’s research interests span coral reef ecology, geospatial analysis, and disaster risk assessment. She actively promotes STEM diversity through initiatives like R Ladies Brisbane and the Wonder of Science program. Notable achievements include a 2022 Queensland Women in STEM Awards Finalist recognition and grants totaling over AUD 100,000, including the Society for Conservation Biology Small Grant and the Elodie Sandford Explorer Award. Education: PhD (University of Queensland). Affiliations: Centre for Data Science, Coral Reef Ecosystems Laboratory, Brisbane Floods Hackathon leadership. Outreach: Co-organizer of Geospatial Community and R Ladies Brisbane, Young Science Ambassador (Wonder of Science). Her scientific contributions include advancing AI-driven coral reef monitoring and advocating for linguistically inclusive academic publishing. Current projects emphasize bridging geospatial science with environmental conservation to address climate change impacts.

• Earth Observation
• Remote Sensing
• Climate Change
• +5 more

Professor Heiko Balzter is a Professor of Physical Geography and Director of the Institute for Environmental Futures at the University of Leicester's School of Geography, Geology & the Environment. He chairs the UKRI Landscape Decisions Programme, coordinating 70 projects, and is a leading member of the National Centre for Earth Observation. His research focuses on earth observation techniques for environmental monitoring, deforestation, climate change, and land use dynamics. He has received notable awards including the Royal Society Wolfson Research Merit Award (2011), Royal Geographical Society’s Cuthbert Peek Award (2015), Copernicus Masters Award (2017), and Leicestershire Live Innovation Award (2023). His work integrates satellite data with ecological models to address global challenges like carbon sequestration, biodiversity conservation, and sustainable land management. Research interests include remote sensing of biomass, forest degradation, and environmental vulnerability. He collaborates internationally on projects such as the LULUCF Scientific Steering Committee for the UK National Greenhouse Gas Account. His recent work emphasizes interdisciplinary approaches to landscape decisions, balancing ecological, agricultural, and energy demands while advancing net-zero strategies. Key contributions include developing tools like Pyeo for near-real-time forest monitoring and frameworks for deforestation-free supply chains using Copernicus data. Awards: Royal Society Wolfson Research Merit Award (2011) Royal Geographical Society’s Cuthbert Peek Award (2015) Copernicus Masters Award (2017) Leicestershire Live Innovation Award (2023) Advising and grants focus on interdisciplinary landscape solutions, with grants from UKRI and EU programs. His work with the Institute for Environmental Futures and National Centre for Earth Observation drives innovative applications of Earth observation to address climate and biodiversity crises. Ongoing projects include analyzing biomass dynamics in African savannahs, oil spill detection via SAR imagery, and modeling climate impacts on disease spread.

Roberto FurfaroView profile

Professor

• Guidance, Navigation and Control
• Machine Learning in Aerospace
• Space Situational Awareness
• +7 more

Roberto Furfaro is a Professor in the Department of Systems and Industrial Engineering and the Department of Aerospace and Mechanical Engineering at the University of Arizona, College of Engineering. He serves as Deputy Director of the Space, Security, Safety & Sustainability Center (S4C) and is a key figure in space situational awareness and planetary exploration systems. His educational background includes a Laurea Degree (MS equivalent) in Aeronautical Engineering from the University of Rome 'La Sapienza' (1998) and a PhD in Aerospace Engineering from the University of Arizona (2004). His research spans guidance and control of planetary landers, machine learning applications in space systems, hypersonic vehicle G&C, and systems engineering for small body proximity operations. He leverages advanced AI, particularly reinforcement learning and deep learning, to solve complex aerospace challenges. The recent publications reflect a strong trend toward intelligent, autonomous systems in spaceflight, especially using deep reinforcement learning for planetary landing, guidance under uncertainty, and space-based object tracking. His work bridges control theory, astrodynamics, and artificial intelligence. 2021 Da Vinci Fellow, College of Engineering AIAA Associate Fellow (2022) AAS Fellow (2021) Asteroid 133474 Roberto Furfaro named in honor of OSIRIS-REx contributions Prof. Furfaro has served as PI or Co-PI on over $80M in research grants from NASA, AFRL, and DoD. He has advised numerous students and leads research teams in autonomous space systems and machine learning applications. He is the Target Follow-up Working Group lead for the NASA NEO Surveyor Mission and was Systems Engineering Lead for SPOC during OSIRIS-REx Phase B-D. He is actively involved in professional service as Associate Editor for IEEE Transactions on Aerospace and Electronic Systems and technical member of the AIAA Astrodynamics Committee and AAS Space Surveillance Committee.

Javier Garcia-Heras CarreteroView profile

Associate Professor

• Air Traffic Management
• Flight Planning under Uncertainty
• Convective Weather Prediction
• +12 more

Javier Garcia-Heras Carretero is an Associate Professor in the Department of Aerospace Engineering at Universidad Carlos III de Madrid (UC3M), where he conducts research and teaches in air traffic management, flight planning, and AI applications in aviation. He is a member of the Aerospace Engineering Research Group. Research Interests: His work focuses on enhancing air traffic flow management through machine learning and optimization, particularly in mitigating weather-related disruptions. Key areas include robust 4D flight planning under uncertainty, convective weather prediction, continuous climb operations, and environmental impact reduction in aviation. He integrates AI models such as LSTM and CNNs to forecast thunderstorms and optimize traffic flow. Recent Publication Trends: His most recent articles (2023–2024) emphasize deep learning for pre-tactical convection prediction, fast stochastic flight path simulation under uncertainty, and AI-driven hotspot detection in air traffic due to weather. These works reflect a strong trend toward data-driven, real-time decision support systems in ATM using neural networks and parallel computing. Scientific Awards: No specific awards are mentioned in the provided text. Advising and Grants: He supervises BSc and MSc theses, including one on data science techniques for weather mitigation in ATFM. He has led multiple research projects as Principal Investigator, including Collaborative Learning for Intelligent Meteorological Aviation (2024–2027) and Donut proyect (2019–2022). He has participated in numerous EU-funded projects such as KAIROS, REFMAP, ECONTRAIL, and ISOBAR, as well as industry collaborations with Airbus, Boeing, and SENASA. Labs and Teams: He is part of the Aerospace Engineering Research Group at UC3M, focusing on ATM systems, trajectory optimization, and digital aviation technologies. His team collaborates internationally on projects involving AI, weather forecasting, and sustainable aviation.

• Geological Modeling
• 3D Geophysical Modeling
• Structural Geology
• +3 more

Lachlan Grose is a Research Fellow at Monash University's School of Earth Atmosphere and Environment, specializing in advanced geological and geophysical modeling. His work focuses on integrating machine learning, 3D structural analysis, and geophysical inversion techniques to address challenges in subsurface resource management and tectonic understanding. Key projects include the Three-dimensional Bayesian Modelling of Geological and Geophysical data (ARC-funded) and development of the LoopStructural software, a time-aware 3D geological modeling platform. Grose also contributes to industry collaborations like the AMIRA P1249 project on ore body knowledge modeling. Research interests span structural geology, igneous intrusion modeling, FAIR data principles, and geophysical inversion methods. He has led efforts to improve usability of Loop3D and pioneered machine learning applications for geological structure imaging. Leading developer of LoopStructural (open-source 3D modeling framework) Primary investigator on usability improvements for geoscientific workflows Recipient of ARC and industry grants totaling over AUD 3M Supervises PhD candidates focusing on interdisciplinary geoscience problems Recent publications emphasize transdimensional inversion methods, FAIR data integration, and application of machine learning to geophysical datasets. His work bridges academic research with industrial subsurface resource challenges.

• High-energy astrophysics
• Machine learning
• Statistical methods
• +7 more

Dr. Sabrina Einecke is a Grant-Funded Researcher (B) at the School of Physics, Chemistry and Earth Sciences , University of Adelaide , with over a decade of experience in high-energy astroparticle physics, machine learning applications, and statistical methods. Leading research in Cherenkov Telescope Array (CTA) science and commissioning Developing software for gamma-ray emission modeling of supernova remnants Advancing machine learning techniques for astrophysical data analysis Her work spans active galactic nuclei , transients , cosmic-ray acceleration , and telescope site quantification in Australia. She serves as a Chief Investigator on ARC LIEF and DVCR-funded projects. The 9 most recent publications highlight her expertise in gamma-ray astronomy, statistical inference, and interdisciplinary collaborations, with significant impact on CTA design and PeVatron identification.

Sarah AaronsView profile

Assistant Professor

• Isotopic Geochemistry
• Low Temperature Geochemistry
• Paleoclimatology
• +12 more

Sarah Aarons is an Assistant Professor in the Geosciences Research Division at Scripps Institution of Oceanography, University of California San Diego. Her research focuses on understanding the geochemical evolution of Earth's surface through isotopic analysis of natural materials such as mineral dust, sediments, and rocks. Education: Ph.D. in Geology, University of Michigan (2016) M.S. in Earth and Environmental Sciences, University of Michigan (2012) B.S. in Geological and Environmental Sciences, Stanford University (2009) Her primary research interests include Isotopic Geochemistry, Low Temperature Geochemistry, Paleoclimatology, Atmospheric Aerosols, and Climate Sciences . She applies radiogenic and non-traditional stable isotope techniques to study dust provenance, weathering processes, and biogeochemical cycling in modern and ancient environments. Field sites span polar regions including Alaska and Antarctica, with a strong emphasis on clean lab methodologies and mass spectrometry. The recent publication trends reflect a consistent focus on using isotope systems (Sr-Nd, Li, Mg, Ca, K, REEs) to trace dust sources, reconstruct paleoenvironments, and understand nutrient delivery to oceans. Her work bridges marine, atmospheric, and terrestrial geochemistry, with strong implications for climate change and Earth system dynamics. Scientific Awards: Sarah Aarons leads the Climate & Earth Surface Geochemistry Group , which conducts field-based and laboratory-intensive research. She advises a team of early-career scientists and graduate students, overseeing projects funded by federal and institutional grants focused on dust-climate interactions, cryospheric geochemistry, and Earth surface processes. Her lab emphasizes interdisciplinary collaboration, open data practices, and integration of physical and chemical measurements. Labs and Research Groups: Climate & Earth Surface Geochemistry Group, Scripps Institution of Oceanography

• Artificial Intelligence
• Machine Learning
• Federated Learning
• +3 more

Tommaso Ruga serves as a Lecturer in the Department of Computer Engineering, Modellistica, Elettronica e Sistemistica (DIMES) at the University of Calabria, Italy. He teaches core courses including Data Base Systems for Management Engineering, Fundamentals of Computer Science for Mechanical Engineering, and Data Analytics for Business for Management Engineering programs in the 2025 academic year. His research centers on Artificial Intelligence applications across critical domains, with primary focus on healthcare innovation (cancer detection, pandemic forecasting, Alzheimer's diagnosis), sustainable agriculture (cassava disease detection, smart farming), and cultural heritage preservation . Key methodologies include federated learning, explainable AI frameworks, and deep learning architectures designed to address real-world challenges like dataset bias in dermatology and energy forecasting for sustainable communities. Analysis of his 15 most recent publications (2023-2025) reveals a cohesive trajectory: 60% target healthcare applications (particularly oncology and neurology), 25% focus on agricultural and environmental systems, and 15% address cultural heritage and tourism. His work consistently emphasizes technical explainability and ethical considerations , notably in mitigating racial bias in medical imaging datasets and developing transparent AI models for clinical decision support. Dr. Ruga operates within the University of Calabria's Department of Computer Engineering, Modellistica, Elettronica e Sistemistica, which provides the computational infrastructure for his AI research. His collaborations frequently involve co-authors Caroprese, Vocaturo, and Zumpano across multiple publications, indicating established research partnerships within the institution.