Dr. Gaël Kermarrec is a researcher at the Boundary Layer Meteorology Group , part of the Institute of Meteorology and Climatology within the Faculty of Mathematics and Physics at Leibniz University Hannover . His work focuses on atmospheric turbulence, GNSS applications, and remote sensing for environmental monitoring. Boundary layer meteorology Turbulence theory GNSS signal processing Terrestrial laser scanning Climate change impacts Geodetic time series analysis His research integrates advanced mathematical models like LR B-splines and Matérn covariance with large eddy simulations to study: Atmospheric turbulence effects on optical/GNSS signals Hydrospheric mass loading Deformation analysis of terrain/port infrastructure Climatic sea-level changes Machine learning for remote sensing The 15 most recent articles (2025-2023) demonstrate his focus on: GNSS-based turbulence detection AI-enhanced climate mapping Advanced surface approximation techniques Multi-sensor data fusion Stochastic modeling of geodetic observations Environmental impacts on optical measurements He has developed tools like the Klimascanner QGIS plugin for urban climate resilience and contributes to: Understanding atmospheric scale lengths Improving TLS/GNSS deformation monitoring Analyzing hydrospheric changes Wavefront modeling Ionospheric corrections
Huy T Tran is an Assistant Professor in the Department of Aerospace Engineering at the University of Illinois at Urbana-Champaign's College of Engineering, with additional appointments at the Applied Research Institute. His research focuses on the intersection of robotics, artificial intelligence, and multi-agent systems, with applications spanning autonomous navigation, critical infrastructure resilience, and intelligent transportation. Dr. Tran earned his Ph.D. in Aerospace Engineering from Georgia Institute of Technology in 2015, following advanced degrees from Georgia Tech and University of Wisconsin-Madison. His academic journey includes research assistant professor positions before achieving his current assistant professor role in 2021. He previously worked as a Senior Multi-Disciplinary Systems Engineer at The MITRE Corporation and served as a Visiting Scholar at the Air Force Institute of Technology. His research interests encompass Autonomy, Reinforcement Learning, Artificial Intelligence, Machine Learning, Robotics, Multiagent Systems, Intelligent Transportation Systems, and Critical Infrastructure Resilience. As director of the Lab for Intelligent Robots and Agents (LIRA), he leads cutting-edge research in autonomous systems that interact with humans and other robots. His work has evolved from foundational resilience modeling in aerospace systems toward increasingly sophisticated AI applications in multi-robot coordination and explainable decision-making. Dr. Tran's publication record demonstrates a clear trajectory toward explainable AI and human-AI collaboration, with recent work focusing on generating explanations for reinforcement learning policies, coordination in ad hoc teams, and neuro-symbolic approaches to robot policy interpretation. His research bridges theoretical advances with practical applications in air traffic control, field robotics, and critical infrastructure management. Best Paper Award: Theoretical (2016 Complex Adaptive Systems Conference) Selected for oral presentation at IROS 2023 Workshop 27% full paper acceptance rate at AAMAS 2022 44% acceptance rate at ICRA 2020 As an educator, Dr. Tran teaches core aerospace courses including Computational Systems Engineering, Aerospace Numerical Methods, and Reinforcement Learning. He has secured significant research funding from NASA's Transformational Tools and Technologies program, ARL A2I2 program, ONR Science of AI program, and DARPA. His current projects span ad hoc teaming in multi-robot systems, collective autonomous air mobility, hierarchical reinforcement learning, and interpretable AI agents.
Dr. Horia Hangan is a Professor of Mechanical Engineering and Canada Research Chair in Adaptive Aerodynamics at Ontario Tech University's Faculty of Engineering and Applied Science. He holds an adjunct professorship at Western University. His research focuses on Experimental Fluid Mechanics, particularly bluff body aerodynamics, turbulent coherent structures, and aerodynamic control, with applications to buildings, vehicles, and aerostructures. He pioneered the WindEEE Dome, a unique facility simulating complex 3D wind flows, enabling studies of tornado-like vortices and non-Gaussian wind phenomena. Education: PhD in Wind Engineering from Western University (1996), Diplomat Engineering Degree in Aeronautics from the Polytechnic University of Bucharest (1985). Research interests include downburst dynamics, wind–structure interaction, and renewable energy. Over 150 publications span experimental and numerical studies of tornado-like vortices, downburst flows, and wind turbine performance. Notable awards include the CSME Fellowship (2016), ENR News Maker of the Year (2015), and the ASME Lewis F. Moody Award (2010). His work bridges fundamental aerodynamics with practical engineering solutions for wind-related challenges.
Dr. Nikolina Ban is an Assistant Professor at the Department of Atmospheric and Cryospheric Sciences (ACINN) at the University of Innsbruck, Austria. Her research focuses on high-resolution climate modeling, convection-permitting models, and mountain climate dynamics. She leads projects such as 'Mountain Climate at the Kilometre-Scale Resolution' and collaborates with international teams like TEAMx-UIBK and the CORDEX-FPSCONV-Team. Key areas include extreme rainfall projections, hail/lightning diagnostics, and the impact of climate change on Alpine regions. Expertise: Regional climate modeling, convection-permitting approaches, mountain climate variability. Key Projects: Third Pole climate simulations, Alpine hydrological studies, and national climate scenario development in Austria. Her work addresses challenges in resolving fine-scale climate processes over complex terrains. Recent studies emphasize improving projections of precipitation extremes and understanding model uncertainties. Collaborations span institutions globally, including the Swiss Federal Institute of Technology (ETH Zurich) and the University of California, Los Angeles (UCLA). Publications highlight advancements in ensemble-based climate simulations and the added value of kilometer-scale models for capturing temperature and wind patterns in alpine regions. Ongoing research includes evaluating dynamical downscaling techniques for reliable regional climate change assessments.
Summer Rupper is a Professor at the School of Environment, Society & Sustainability at the University of Utah, where she has held her position since July 2019. Her research focuses on understanding the interactions between climate, glaciers, and water resources, with particular emphasis on high mountain regions including High Mountain Asia, the Himalayas, and polar regions. She leads multiple research projects examining glacier dynamics, hydrological processes, and climate change impacts on water security for downstream populations. BS in Geology from Brigham Young University (2001) MS in Geology from University of Washington (2004) PhD in Earth and Space Sciences from University of Washington (2007) Professor Rupper's research spans physical geography, environmental geoscience, and climate change science, with specific expertise in glaciology, hydrology, and atmospheric sciences. Her work integrates field measurements, remote sensing, and numerical modeling to understand glacier dynamics, snow processes, and water resource availability in mountainous regions. She has particular expertise in High Mountain Asia, where glaciers provide critical water resources for over a billion people. Her research addresses fundamental questions about glacier response to climate change, hydrological partitioning, and the implications for water security in vulnerable regions. Her recent publications demonstrate a consistent focus on understanding glacier dynamics, hydrological processes, and climate interactions in mountainous regions. The work spans multiple methodologies including remote sensing analysis, numerical modeling, statistical approaches, and field-based measurements. Key themes include glacier melt contributions to river systems, precipitation patterns in complex terrain, snow density modeling, and the impacts of climate change on water resources in High Mountain Asia and polar regions. Her research often integrates multiple data sources and approaches to address complex questions about cryospheric processes and their societal implications. Superior Research Award (2024, CSBS, University of Utah) G.K. Gilbert Award for Excellence in Geomorphic Research (2022) Outstanding Utah Higher Education Science Teacher (2021) Top Researcher Award, Celebrate U showcase (2017) Antarctic Service Medal (2010, USAF) Professor Rupper actively mentors graduate students through thesis research courses at both the PhD and Master's levels, as well as individual projects. She has secured significant research funding from multiple federal agencies including NSF, NASA, and USAID, with current projects examining climatic controls on Antarctic ice sheets, glacier dynamics in High Mountain Asia, and historical glacier changes. Her collaborative work extends across international boundaries, working with scientists in Pakistan, Bhutan, and other regions to address shared water security challenges. She also engages in community outreach through workshops with school districts and science teacher associations to communicate climate science to broader audiences. Professor Rupper participates in multiple collaborative research teams including the NASA High Mountain Asia Team (HiMAT), where she contributes expertise in glacier dynamics and hydrology. She serves on several scientific committees including the NSF Ice Core Facility Sample Allocation Committee and the American Geophysical Union Cryosphere Section Fellows Committee. Her research often involves interdisciplinary teams combining expertise in glaciology, hydrology, remote sensing, and climate modeling to address complex questions about mountain water systems under changing climate conditions.
Dale Lawrence is a Professor in the Department of Aerospace Engineering Sciences at the University of Colorado Boulder, where he has served continuously since 1991. He directs research at the Research and Engineering Center for Unmanned Vehicles (RECUV), focusing on astrodynamics, satellite navigation systems, and autonomous aerial platforms for atmospheric science. His academic credentials include: PhD in Electrical Engineering from Cornell University (1985) MS in Electrical Engineering from Cornell University (1982) BS in Electrical Engineering from Colorado State University (1980) Professor Lawrence's research spans spacecraft attitude control , vibration isolation , and adaptive control systems , with pioneering work in haptic interfaces for scientific visualization and teleoperation. His recent work emphasizes unmanned aerial systems for Arctic atmospheric research, particularly turbulence measurement and boundary layer studies using custom UAV platforms like DataHawk. This work bridges aerospace engineering with climate science through field campaigns such as MOSAiC and LAPSE-RATE. His publication record reveals a clear trajectory toward Arctic atmospheric science and UAV-based sensing , with increasing focus on turbulence dynamics, sea-ice interactions, and autonomous system validation. The work consistently integrates hardware development (sensors, UAVs) with field deployment in extreme environments. Selected honors include: Best Commercial Potential Award at IEEE Symposium on Haptic Interfaces (2004) Best Paper Presentation at American Control Conference (1994) Teaching Excellence Awards from University of Cincinnati (1990, 1991) Distinguished Publication Award from Martin Marietta Astronautics (1988) Professor Lawrence has led major field campaigns including MOSAiC and LAPSE-RATE, securing funding from NSF and DOE for projects like ERASMUS and ShUREX. His RECUV team develops specialized UAV platforms (DataHawk, HELiX) for atmospheric research, with recent work focusing on machine self-confidence for autonomous decision-making in complex environments. While student advising details aren't specified, his projects involve extensive student participation in hardware development and field operations. He maintains active leadership in Arctic atmospheric research through the DataHawk UAV program and HELiX multispectral systems, with ongoing work on gossamer propeller technology for high-altitude applications and machine self-confidence frameworks for autonomous systems.
Kristen L. Rasmussen is an Associate Professor in the Department of Atmospheric Science at Colorado State University (CSU), affiliated with the Walter Scott, Jr. College of Engineering. She holds a Ph.D. (2014) and M.S. (2011) in Atmospheric Sciences from the University of Washington, and dual B.S. (Meteorology and Mathematics) and B.A. (Music) from the University of Miami (2007). Before joining CSU in 2016, she was an Advanced Study Program Postdoctoral Fellow at NCAR (2015–2016). Her research focuses on convective storms, cloud-climate interactions, mesoscale meteorology, and hydrometeorology. Key interests include analyzing extreme rainfall, tropical convective systems, and the impacts of climate change on storm dynamics. She leads the Rasmussen Group, which investigates topics like the NASA INCUS satellite mission, subtropical storms in South America, and climate modeling. Received awards such as the 2015 AMS Mesoscale Processes Conference Very Early Career Award and the 2011 NASA Earth System Science Graduate Fellowship. Active in field campaigns like RELAMPAGO in Argentina and PRECIP in Taiwan/Japan. Teaches courses on synoptic and mesoscale meteorology, hydrometeorology, and mountain meteorology. Her group includes researchers and students studying topics ranging from convective storm environments to stratospheric aerosol injection impacts. Ongoing projects include the INCUS mission and climate projections for extreme precipitation in the U.S. Midwest.
Raul Wood is a Research Fellow at the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), specifically within the Institute for Snow and Avalanche Research (SLF) in Davos. He operates in the Snow and Atmosphere Unit under the Hydrology & Climate Impacts in Mountain Regions Group, focusing on climate-hydrology interactions in alpine environments. His research centers on extreme hydroclimatic events, with emphasis on precipitation extremes, flood/drought dynamics, and climate change impacts in mountainous regions. Wood employs global climate model ensembles and hydrological modeling to dissect internal variability versus forced responses, particularly across European and Alpine domains. His work bridges theoretical climate science with practical water resource management challenges. Analysis of Wood's publication record reveals consistent focus on multi-scale extreme event analysis, compound hazards, and ensemble-based uncertainty quantification. His recent work increasingly addresses societal impacts through urban flood resilience and population exposure metrics, while maintaining technical rigor in statistical downscaling and hydrological modeling. Wood actively contributes to three major research initiatives: SynFire (synchronous forest fires in Europe), Hydro-SMILE (hydrological ensemble for Swiss droughts/floods), and upXdown (upstream-downstream drought cascades in the Alps). These projects demonstrate his commitment to solving complex climate-water challenges through collaborative, interdisciplinary approaches with European partners.
Dr. Zhaoxia Pu is a Professor in the Department of Atmospheric Sciences at the University of Utah and an Adjunct Professor at the School of Computing . Recognized as a Fellow of both the American Meteorological Society and the Royal Meteorological Society, she serves on the NOAA Science Advisory Board and has led 38 federally funded projects from agencies including NOAA, NASA, NSF, DOE, and ONR. Specializes in numerical weather prediction , data assimilation , and AI/machine learning for high-impact weather systems Developed advanced methods integrating satellite/radar data (GOES-R, CYGNSS, TROPICS) with Earth system models (UFS, E3SM, WRF) Recipient of the 2024 Excellence in Research Award and 2023 Provost's Banner Project recognition Research Trends : Her recent publications focus on: Machine learning approaches for precipitation retrieval using GOES-R data Cold fog microphysics and visibility parameterization in complex terrain Tropical cyclone dynamics through radar and lidar data assimilation Boundary layer turbulence in landfalling storms Drought mechanisms linked to synoptic-scale circulation New particle formation in mountainous regions Scientific Leadership : Lead scientist for CFACT NSF field campaign (2021–2025) Editorial board member of leading journals Active reviewer for NSF, DOE, NOAA, and NASA Teaching & Mentorship : Teaches Numerical Weather Prediction , Atmospheric Dynamics , and Introduction to Atmospheric Sciences courses. Has supervised 28 graduate students to completion.
Thomas Albright is an Associate Professor and Deputy Nevada State Climatologist at the University of Nevada, Reno (UNR), affiliated with the Department of Geography and the Ecology, Evolution & Conservation Biology Graduate Program. His work integrates landscape ecology, biogeography, and remote sensing to address environmental challenges at global and local scales. He has conducted international research across 15 countries, emphasizing conservation, climate impacts, and sustainability. Educated at the University of Wisconsin-Madison (Ph.D. in Zoology, 2007) and the University of California, Santa Barbara (M.A. in Geography), he has held roles including Postdoctoral Associate at UW-Madison and Senior Scientist at the USGS EROS Center. His teaching focuses on physical geography, remote sensing applications, and climate solutions, emphasizing active learning and mentorship. Research interests include conservation biogeography, ecoclimatology, and urban heat dynamics. Notable projects include studying invasive species in China and the US, avian responses to extreme weather, and Las Vegas urban heat hazards. He collaborates globally, including with Nicaraguan institutions and NASA initiatives. His lab, the Laboratory for Conservation Biogeography, emphasizes environmental justice, community engagement, and policy-relevant science. Key collaborators include USGS, NASA, and international universities. Advised students include D Mutiibwa, G Sadoti, Nicole Shaw, and Lauren Phillips.
Mario Harper is an Assistant Professor in the Department of Computer Science at Utah State University. His research emphasizes Machine Learning, Data Science, Robotics, and their intersections with Finance and Artificial Intelligence. He specializes in autonomous systems, energy-efficient robotics, and AI-driven solutions for transportation and urban sustainability. His work includes developing tools like simulators for electric vehicle systems and stealth-centric navigation algorithms inspired by biological systems. Key research areas include multi-robot coordination, reinforcement learning applications in robotics, and algorithmic approaches to environmental and economic challenges. He has contributed to projects like POSEIDON-SAT for satellite-based fishing vessel detection and electrified transportation equity analysis in urban settings. His publications span topics from trajectory planning in legged robots to AI modeling for economic systems. Beyond research, he designs interactive visualization tools to support policy decisions on sustainable transportation infrastructure. No scientific awards are explicitly listed in the provided information. Mario Harper’s advising and grants focus on robotics, energy systems, and AI applications, though specific student advisees or grant details are not detailed here. He collaborates on projects involving lab tools such as the Unknown Building Exploration Simulator (UBES) and Stealth Centric Autonomous Robot Simulator (SCARS), advancing robotic autonomy in unstructured environments.
Feng Chen is a Clinical Associate Professor at the Marshall School of Business, University of Southern California, affiliated with the Department of Data Sciences and Operations. She teaches courses in operations management and data analytics for decision-making, with a Ph.D. in Business Administration from USC. Education: Ph.D. in Business Administration from University of Southern California Her research focuses on process analysis , supply chain analytics , and behavioral operations decision-making . She has designed and instructed advanced courses on business analytics, statistics, and operations optimization. Recent publications demonstrate expertise in atmospheric data assimilation , satellite meteorology , and weather system modeling . Key methodologies include multi-sensor integration, cloud-dependent observation-error modeling, and numerical prediction systems for tropical weather phenomena. Contact: fchen@marshall.usc.edu | Phone: 213-740-6319
Jose Ignacio Rojas Gregorio is an Associate Professor at the Department of Physics, School of Telecommunications and Aerospace Engineering (EETAC) at the Polytechnic University of Catalonia (UPC). With over 160 documented research activities, he specializes in mechanical properties, viscoelasticity, wind energy systems, and computational fluid dynamics. His work bridges fundamental materials science with practical applications in renewable energy, particularly wind power optimization and thermally-driven wind phenomena. His research interests span mechanical properties and viscoelastic behavior of materials, wind energy systems, computational fluid dynamics for wind resource assessment, non-destructive testing methods, and earthquake precursors. Dr. Rojas Gregorio's work has significant practical applications in renewable energy, particularly in optimizing wind turbine performance through advanced flow control techniques and understanding sea-breeze phenomena for energy generation. His research demonstrates a strong interdisciplinary approach connecting materials science with renewable energy engineering. His recent publications show a concentrated focus on wind energy optimization, particularly through advanced flow control techniques for wind turbines. He has been actively researching sea-breeze phenomena and their potential for wind energy generation in the Llobregat river delta region of Spain, as well as the mechanical properties of advanced materials including glasses and composites for aerospace applications. His work combines experimental, numerical, and analytical approaches to address complex engineering challenges. 4th MedGU Annual Meeting-Best Paper Award - Track 1. Atmospheric Sciences, Meteorology, Climatology, Oceanography (2024) Dr. Rojas Gregorio has advised doctoral students including Athota, Rathan on "Numerical Analysis of Thermally-Driven Winds in Mountain-Valley Regions." His research is supported by multiple competitive R&D projects including WOW-CONTROL and Optimum Active Flow Control implementation in large-scale wind turbines. He collaborates extensively with researchers across multiple institutions on projects related to wind energy, materials science, and computational modeling. He is affiliated with several research groups at UPC including GCM (Materials Characterization Group), CTE-CRAE (Space Science and Technology Research Group), and PTP-GlaDyM (Phase transitions, polymorphism, glasses and dynamics of the metastability). These groups provide collaborative environments for interdisciplinary research spanning materials science, aerospace engineering, and renewable energy technologies.
Jim Steenburgh is a Professor of Atmospheric Sciences at the University of Utah specializing in mountain weather and climate, orographic and lake-effect precipitation, weather analysis and forecasting, and numerical weather prediction. He joined the University of Utah faculty in 1995 and served as Department Chair from 2005-2011. An avid skier, he shares his expertise through his popular blog Wasatch Weather Weenies and his book Secrets of the Greatest Snow on Earth . B.S. in Meteorology from The Pennsylvania State University (1989) Ph.D. in Atmospheric Sciences from the University of Washington (1995) Dr. Steenburgh's research focuses on winter storms in complex terrain, particularly in mountainous regions. His work spans mountain meteorology, lake-effect and sea-effect snow systems, and the interaction between weather systems and topography. He has conducted significant research on the Wasatch Mountains, Great Salt Lake region, Japan Sea, and other mountainous areas worldwide. His expertise in winter weather forecasting has practical applications for avalanche safety, ski industry forecasting, and understanding climate change impacts on mountain snowpack. Analysis of Steenburgh's recent publications reveals a strong emphasis on lake-effect and sea-effect precipitation systems, particularly their interaction with terrain. His research combines observational studies with numerical modeling approaches to understand mesoscale weather phenomena. A significant portion of his work focuses on the Wasatch Mountains and Great Salt Lake region, while also expanding to international locations including Japan and the European Alps. His publications demonstrate an evolving research trajectory incorporating climate change impacts on mountain snow systems. Fellow, American Meteorological Society (2021) Fulbright Scholar, University of Innsbruck (2019) Distinguished Teaching Award, University of Utah (2024) Russel L. DeSouza Award, NSF Unidata Program (2024) Named Session Award, AMS Mountain Meteorology Committee (2018) Hosler Alumni Scholar Medal, Penn State University (2017) Outstanding Service Award, National Weather Service Western Region (2002) Outstanding Teaching Award, University of Utah (2001) Steenburgh has secured substantial research funding from NSF, NASA, and other agencies, with current projects extending through 2025. His grants focus on mountain meteorology, lake-effect snow prediction, and improving winter weather forecasting in complex terrain. He has mentored numerous graduate students through projects like the Storm Peak Laboratory graduate education program and has been involved in several major field campaigns including the Ontario Winter Lake-effect Systems (OWLeS) and the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) program. Dr. Steenburgh leads the Wasatch Weather Weenies blog, a collaborative effort with other meteorologists that provides real-time weather analysis and commentary, particularly focused on Utah's mountain weather. He has been instrumental in connecting academic research with practical weather forecasting applications, working closely with the National Weather Service and avalanche centers. His research group frequently collaborates with international partners, particularly in Japan where sea-effect snow systems share similarities with Utah's lake-effect snow events.
Prof. Dr. Renato Pajarola is the Head of the Visualization and MultiMedia Lab at the Department of Informatics, University of Zurich. His research focuses on computer graphics, scientific visualization, and geometric processing, with applications in 3D scanning, point cloud analysis, and real-time rendering. He leads a team developing advanced visualization techniques for high-dimensional data, parallel rendering frameworks, and interactive systems for complex datasets. Key research areas include: 3D reconstruction of indoor environments Tensor approximation for volume visualization Interactive ray tracing and point cloud processing Parallel rendering frameworks (e.g., Equalizer) Scientific computing and sensitivity analysis His recent publications emphasize: High-dimensional data exploration using tensor methods Efficient rendering techniques for large-scale point clouds Integration of citizen-reported weather data for environmental analysis Prof. Pajarola’s lab collaborates on projects like VIAN (visual annotation tool for film analysis) and Terrender (web-based terrain visualization). His Erdős number is 3, reflecting interdisciplinary research connections in mathematics and computer science.
