Monique Pfaltz is a Professor at Mid Sweden University's Department of Psychology and Social Work (PSO). Her research focuses on trauma psychology, childhood maltreatment, and mental health interventions, with emphasis on social functioning, emotional regulation, and clinical outcomes. She leads projects like the Child Trauma Network and studies body-oriented treatments for trauma-related symptoms. Her work explores how adverse childhood experiences impact interpersonal relationships, facial expression recognition, and physiological responses. Key themes include cross-cultural analyses of maltreatment effects, resilience mechanisms, and validated psychological scales (e.g., Emotion Reactivity Scale, Intimacy Scale). Publications highlight trauma's influence on social distance preferences, depression, and PTSD symptom severity. She collaborates globally, addressing refugee mental health and scalable interventions like Problem Management Plus (PM+). Grants and projects emphasize preventive strategies for allostatic load, cultural variability in trauma responses, and psychosocial support systems. Her research bridges clinical practice and theoretical models in trauma psychology.
Christoph Beier is a Professor of geochemistry at the University of Helsinki, Faculty of Science, Department of Geosciences and Geography. He serves as Head of Helsinki mineralogical and environmental laboratories (HelLabs), Head of laser ablation ICP-MS laboratory, and Director of the research programme in geology and geophysics. His primary research focuses on: Igneous trace element and isotope geochemistry and petrology Geochemistry of the short-lived U-series decay chains Spatial and temporal evolution of magmatic systems Geology and Petrology of marine igneous systems Professor Beier teaches Elemental geochemistry (BSc), isotope geochemistry (MSc) and microanalytical methods (MSc). His extensive publication record demonstrates expertise across multiple subfields of geochemistry and petrology, with particular emphasis on magmatic processes, volcanic systems, and mineral exploration. His work spans diverse geographical locations including Iceland, the Azores, the Pacific-Antarctic Ridge, Greece, China, and Finland. He currently leads several major international research projects: FluxBEATS MSCA DN (2024-2028): Fluxes at divergent plate Boundary Environments Analyzed in Time and Space Machine learning approaches for IOCG (2023-2026) SA FIRI Finnish Thermal Ionisation (2023-2025) Fingerprinting the origin and ascent of magmas through the crust in rift zones (2021-2025) Professor Beier actively supervises numerous doctoral students across various research topics including the metasomatic evolution of the Suomenniemi complex, machine learning approaches for IOCG-style Fe-Cu-Au deposits, and the geochemical and petrological variability of the Fjallgarðar volcanic ridge. He serves on the IODP Scientific Evaluation Panel and is a member of the ESSAC committee. He directs the Helsinki Geoscience Laboratories (Hellabs) and manages the Geofluids Laboratory and Laser ablation ICP-MS laboratory, providing critical research infrastructure for geochemical analysis.
Dr Dawn Wimpory is a Lecturer / Practitioner in Clinical Psychology at Bangor University and a Consultant Clinical Psychologist (Lead for ASD) at Betsi Cadwaladr University Health Board (BCUHB). Her work integrates clinical practice and research, focusing on Autism Spectrum Disorder (ASD) through the lens of social timing and its genetic underpinnings. Education: PhD (2017) in Social Engagement in Preschool Autism from Bangor University; MSc (1988) in Clinical Psychology from University of Exeter; MA (1985) in Child Clinical Psychology from University of Nottingham; BEd (1984) in Psychology and Education from University of Wales, Cardiff. Her research explores the Social Timing Hypothesis (Wimpory et al., 2002), which posits that temporal synchronization in interactions is critical for social engagement in ASD. Key contributions include the development of the Detection of Autism by Infant Sociability Interview (DAISI) and Musical Interaction Therapy (MIT), a parent-mediated intervention for severely affected ASD children. Recent publications (2023-2000) span topics such as interoceptive awareness, gait analysis as a diagnostic tool, and MIT's clinical efficacy. She has secured over £884,764 in grants, including KESS Scholarships and Baily Thomas funding, and serves as a reviewer for journals like Molecular Psychiatry and Journal of Autism and Developmental Disorders . Scientific Awards: NISCHR Clinical Research Fellowship (2011-2014) Knowledge Economy Skills Scholarship (KESS) Baily Thomas Charitable Fund Grant Dr Wimpory supervises PhD and postgraduate students, including Judit Elias-Masiques (2020-2023) and Kitty Forster (2013). Her teaching at Bangor University covers Intellectual and Developmental Disabilities, Applied Behaviour Analysis, and Theoretical Models in Clinical Psychology.
Professor Ian Holman is a leading academic at Cranfield University, where he holds the position of Professor of Integrated Land and Water Management and leads the Centre for Water, Environment and Development within the Cranfield Water Science Institute. His expertise spans integrated land and water systems, natural capital, sustainable land systems, and water science and engineering, with a strong focus on climate change adaptation and policy. His research is centered on three main pillars: (1) integrated modeling of land and water systems under changing climate and socio-economic conditions, (2) innovative agricultural water management to enhance water security and drought resilience, and (3) understanding lowland peat management to reduce greenhouse gas emissions. He employs interdisciplinary methods combining hydrogeology, spatial pedology, and agricultural science to address complex environmental challenges at catchment to continental scales. His recent publications (2023–2025) reflect a strong trend in drought resilience, particularly in Thailand and the UK, with increasing focus on socio-hydrological systems, institutional adaptation, and decision support tools. Key subfields include drought forecasting using climate teleconnections (e.g., NAO), sediment and nutrient transport in rivers, rainwater harvesting, and peatland carbon management. His work bridges science and policy, with clients including Defra, Environment Agency, NERC, and the European Commission. Professor Holman has supervised numerous students and collaborators, many of whom appear as co-authors on his publications. He has led major research projects funded by UK government departments, research councils, and international agencies. His work supports climate adaptation policy and water security in both temperate and tropical regions. He is actively involved in developing decision support tools such as the D-Risk webtool for drought risk management and has contributed to lowland peat re-wetting assessments for greenhouse gas reduction. His leadership in integrated modeling platforms supports evolving environmental and agricultural policies. He has also co-authored several books on climate change, vulnerability assessment, and socio-economic pathways.
John Isaac Murray is a Professor of Genetics at the Perelman School of Medicine, University of Pennsylvania. His laboratory focuses on understanding how genomes orchestrate animal development at single cell resolution using the nematode worm Caenorhabditis elegans as a model organism. Dr. Murray's research integrates powerful imaging-based experiments with genomics and computational tools to determine gene expression patterns across entire embryos at single cell resolution. Dr. Murray received his B.S. in Civil Engineering with a minor in Biology from Carnegie Mellon University in 1999, followed by a Ph.D. in Genetics from Stanford University in 2004. He completed his post-graduate training as a Senior Fellow in Genome Sciences at the University of Washington from 2003 to 2009, working in the laboratory of Robert Waterston. Dr. Murray's research interests span developmental biology, genomics, and gene regulation. His laboratory has developed innovative lineage tracing methods that allow quantitative determination of gene expression at single cell and approximately 1-minute temporal resolution for essentially all embryonic cells. Current research focuses on three main areas: (1) improved technology for lineage tracing and expression mapping in developing embryos, (2) mechanisms ensuring robust development across environmental conditions, and (3) defining mechanisms of context specificity in developmental gene regulation. His work has revealed how transcription factors and signaling pathways regulate developmental gene expression, with implications for understanding cancer and other human diseases. Dr. Murray's laboratory has produced significant publications in high-impact journals including Science, Genome Research, and Genetics. His recent work has focused on single-cell resolution analysis of embryonic gene expression evolution, mRNA decay dynamics in developing embryos, and comprehensive mechanisms of lineage specification in C. elegans . His research employs cutting-edge techniques including live-cell imaging, single-cell RNA sequencing, and computational analysis to build comprehensive molecular atlases of embryonic development across multiple species. Large CRL, et al. (2025). Lineage-resolved analysis of embryonic gene expression evolution in C. elegans and C. briggsae. Science. Peng F & Murray JI (2024). A spatiotemporally resolved atlas of mRNA decay in the C. elegans embryo. Genome Research. Liu J & Murray JI (2023). Mechanisms of lineage specification in Caenorhabditis elegans. Genetics. Dr. Murray has mentored numerous students and postdoctoral fellows who have gone on to successful careers, including Dr. Felicia Peng who recently completed her PhD in his laboratory, Dr. Priya Sivaramakrishnan who now leads her own laboratory at the Children's Hospital of Philadelphia, and Dr. Amanda Zacharias who is an Assistant Professor at Cincinnati Children's Hospital Medical Center. His laboratory is affiliated with several graduate programs at Penn including Biomedical Graduate Studies, Cell and Molecular Biology, Genomics and Computational Biology, Biochemistry and Molecular Biophysics, and Bioengineering. The Murray laboratory maintains active collaborations with other research groups and has contributed to studies on chromatin regulation, neuronal development, and cuticle formation in C. elegans . Dr. Murray's work continues to advance our understanding of how genomes control the complex process of animal development at unprecedented resolution.
Lisa Gustavsson is an Associate Professor in the Department of Linguistics at Stockholm University, where she conducts cutting-edge research on early language acquisition and forensic phonetics. She is affiliated with the Stockholm Babylab, a research group dedicated to studying infant language development through multiple parallel projects and international collaborations. Her research interests focus on early language acquisition, specifically examining speech processing, speech production, and communicative interaction in infants, with particular attention to the acoustic characteristics of speech signals. She also investigates forensic phonetics, exploring speaker identification and profiling techniques for forensic investigations, and how speaker recognition relates to fundamental phonetic processes. Her work bridges theoretical linguistics with practical applications in understanding how infants acquire language. Analyzing her recent publications reveals consistent themes in infant language development research. Her work demonstrates a strong focus on how hyperarticulation in child-directed speech affects language learning, the development of tone perception across different language environments, and the role of social and emotional factors in language acquisition. Her research spans multiple methodologies including behavioral experiments, cross-linguistic comparisons, and neuroscientific approaches to understanding speech processing. Gustavsson leads several significant research projects including Learning First Words (L3WO), which investigates hyperarticulation's effect on infant word recognition; The Effect of Hyperarticulation on Early Language Development (HELD); Distributional Learning: Domain-specificity and the impact of social cues (DIDI); Learning Tones: The influence of pitch accent language experience on lexical tone perception (LETO); Parent Affect in Language Learning (PALL); SoundStart; and the CAPSL-project on statistical learning and auditory predictability. As part of the Stockholm Babylab, Gustavsson works within a collaborative research environment that employs multimodal approaches to study language acquisition longitudinally through parent-child interactions. Her work contributes significantly to our understanding of the complex processes involved in how infants learn language, with implications for both theoretical linguistics and practical applications in speech therapy and language education.
David M. Blei is the William B. Ransford Professor of Statistics and Computer Science at Columbia University. He is a leading researcher in machine learning, with a focus on probabilistic modeling and Bayesian statistics. His work bridges theoretical foundations with practical applications across various domains. Professor Blei's research spans several key areas in modern machine learning: Development and analysis of probabilistic models for complex data Bayesian inference methods, particularly variational inference Topic modeling and mixed-membership models Causal inference and model criticism Deep generative models and representation learning Applications in natural language processing and recommendation systems His recent publications demonstrate continued advancement in variational inference theory while exploring applications in deep learning and causality. Blei's work on posterior collapse in variational autoencoders, black box variational inference, and scalable recommendation systems has been particularly influential in the machine learning community. Professor Blei mentors PhD students and postdoctoral researchers, fostering the next generation of machine learning researchers. He actively teaches graduate courses on probabilistic models, machine learning, and causal inference at Columbia University, including STCS 6701: Probabilistic Models and Machine Learning (scheduled for Fall 2025). He leads a research group focused on probabilistic modeling, contributing significantly to both theoretical advancements and practical applications of statistical methods in artificial intelligence. The group is part of Columbia's thriving machine learning community, which spans multiple departments and research centers.
Rainer Prinz is a Senior Scientist at the Department of Atmospheric and Cryospheric Sciences (ACINN) at the University of Innsbruck, Austria. His research focuses on glaciology and climatology in high mountain regions, with particular expertise in mass and energy balance of glaciers, micro-meteorology, and geophysical methods. As Station Manager of Hintereisferner for the INTERACT project, he oversees one of Europe's longest continuously monitored glaciers, which serves as an open-air laboratory for climate-glacier interactions. Dr. Prinz's research spans several key areas including tropical glacier monitoring in East Africa (Kilimanjaro, Mount Kenya, Rwenzori Range), Alpine glacier dynamics, snow physics, and climate change impacts on mountain environments. His work integrates field measurements, remote sensing data, and numerical modeling approaches to understand complex glacier-atmosphere interactions. He has made significant contributions to understanding wind-driven snow redistribution, glacier mass balance, and the application of novel sensor technologies for continuous environmental monitoring. His publication record includes highly cited works such as 'Historically unprecedented global glacier decline in the early 21st century' with over 500 citations. Dr. Prinz leads or contributes to multiple international research projects including the World Glacier Monitoring Service (as National Correspondent for Kenya, Tanzania, and Uganda), the LATICE project studying land-terminating ice cliffs in North Greenland, and the INTERACT network for Arctic research. His work on Hintereisferner glacier serves as a model for long-term glacier monitoring, providing critical data on climate change impacts in the European Alps. At the University of Innsbruck, Dr. Prinz is actively involved in research infrastructure development, particularly through the Hintereisferner station which functions as an open-air laboratory. His work connects with broader networks including the World Glacier Monitoring Service and international collaborations focused on high mountain regions worldwide, from the Alps to East Africa and Greenland.
Dr. Michael Rzanny is a Scientist at the Max Planck Institute for Biogeochemistry in Jena, Germany, working within the Department of Biogeochemical Integration and the Biod.AI.versity Observation & Integration research group. His work focuses on leveraging technology and citizen science to advance ecological research. Email: mrzanny@... Location: Hans-Knöll-Str. 10, 07745 Jena, Germany Dr. Rzanny's research spans several critical areas in ecology and biodiversity science. He specializes in plant phenology , using citizen science data and machine learning to monitor and predict plant life cycle events across Central European forests and grasslands. His work also explores multitrophic interactions , examining how plant diversity affects predator and herbivore specialization in complex ecosystems. Additionally, he contributes to digital taxonomy through mobile apps like Flora Incognita and Flora Capture, which enable automated plant species identification using smartphone technology. His research extends to functional diversity in grassland ecosystems, analyzing how species richness impacts ecological multifunctionality and food web stability. Dr. Rzanny's publications demonstrate a strong trend toward integrating automated image analysis with ecological monitoring . His work on phenological dynamics combines observational networks, citizen science databases, and land surface models to understand climate change impacts on plant communities. He has developed methodologies for leaf shape analysis using deep learning, validated through geometric morphometrics. His projects like Flora Incognita and Flora Capture emphasize the potential of mobile applications in transforming biodiversity research and public engagement with natural environments.
David Kepplinger is an Assistant Professor in the Department of Statistics at George Mason University's School of Computing. His academic expertise spans robust statistical methods for high-dimensional data, computational statistics, and applications in biomedical sciences and environmental modeling. Education: PhD in Statistics, University of British Columbia, 2020 Master of Science in Statistics, Vienna University of Technology (Austria) Dr. Kepplinger's research primarily focuses on robust estimation in high-dimensional settings, with particular interest in the robustness of feature selection in the presence of arbitrary contamination and countering the effects of contamination on predictive models. His work addresses critical challenges in statistical analysis where outliers and unusual values can severely impact results, especially in settings with many variables. He develops methods that maintain reliable performance even when data contains contamination in both response variables and explanatory features. His recent publications demonstrate a strong interdisciplinary approach, spanning computational statistics, biomedical applications, environmental modeling, and clinical research. The research shows a consistent theme of developing robust statistical methodologies applicable to complex real-world problems across multiple domains, from protein biomarker identification to phenological modeling of cherry blossom predictions. His work frequently involves developing computational algorithms that can handle non-convex optimization problems common in robust statistics. Dr. Kepplinger serves as a co-organizer for the statistics seminar series and is the PR & communications contact for the Department of Statistics at George Mason University. He mentors PhD students Yang Long and Siqi Wei, who focus on improving computational methods for robust regularized regression estimators. He teaches several courses including STAT 665 (Categorical Data Analysis) and STAT 778 (Statistical Computing). He leads several notable projects including the First International Cherry Blossom Prediction Competition, which has been featured in prominent media outlets like The Weather Network, CBC Radio, and Public Radio's The World. This citizen science initiative aims to improve phenological modeling through crowd-sourced predictions of cherry blossom peak bloom dates in Washington, D.C., Vancouver, Kyoto, and Liestal-Weideli, Switzerland. He also develops multiple R packages available on CRAN and Bioconductor, including pense for robust regression estimation and examinr for creating online exams from R markdown documents.
Bo P Wang is a Professor in the Mechanical and Aerospace Engineering Department at The University of Texas at Arlington's College of Engineering. With a distinguished career spanning several decades, he has established himself as an expert in computational mechanics and structural dynamics with significant contributions to design optimization, vibration analysis, and finite element methods. Dr. Wang received his PhD in Aerospace Engineering from the University of Virginia in 1974, following an MS in Mechanical Engineering from the University of Missouri Columbia (1970) and a BS in Mechanical Engineering from National Taiwan University (1967). His educational background provided the foundation for his extensive research in structural mechanics and computational methods. His research interests focus on design optimization, finite element methods, computational mechanics, vibration, structural dynamics, and image reconstruction for NIR measurements. His work bridges theoretical developments with practical engineering applications, particularly in structural optimization and vibration control. Dr. Wang has developed innovative methods including the semi-analytic complex variable method for sensitivity analysis, which has significantly advanced computational approaches in structural dynamics. His publication record demonstrates consistent contributions to structural dynamics and optimization, with recent work focusing on vibration analysis of complex structures, optimization of damping systems, and mid-frequency structural-acoustic problems. His research shows a clear trajectory from fundamental structural mechanics to sophisticated computational approaches for complex engineering problems. Dr. Wang has received notable recognition including The Halliburton Award for Outstanding Research from UTA's College of Engineering and a Certificate of Recognition from NASA. These awards highlight the significance and impact of his research contributions to the field. As an educator and mentor, Dr. Wang has advised numerous PhD and Master's students, serving as Dissertation Committee Chair for many students including Bret Hauser, Rick Scott, and Mike Henson. His teaching portfolio includes advanced courses in structural dynamics, finite element methods, and design optimization, reflecting his expertise across these core mechanical engineering disciplines. He has also contributed to the academic community through extensive service as a reviewer for major journals including Journal of Sound and Vibration, AIAA Journal, and Structural and Multidisciplinary Optimization.
Per Åhag is an Associate Professor at the Department of Mathematics and Mathematical Statistics, Umeå University. His research spans several complex variables, pluripotential theory, and differential geometry, with applications in Kähler geometry, polyfold theory, and mathematical education. Current research projects include 'Mathematical Modeling for Sustainable Development and Societal Change' (2024-2029) and 'Tensors and Geometric Metrics on Manifold-like Polyfolds' (2022-2026). He explores mathematical education through studies like 'Students' Perspectives on Artificial Intelligence' (2022-2024) and 'Formative Assessment and Personalized Learning' (2022-2024). Recent publications address complex Hessian equations, geodesics in m-subharmonic functions, and educational strategies. His work intersects pure mathematics and applied educational psychology, demonstrating a commitment to both theoretical and pedagogical advancements.
Dr Evina Katsou is a Visiting Professor in the Department of Mechanical and Aerospace Engineering within the College of Engineering, Design and Physical Sciences at Brunel University London. She serves as Course Director for the Water Engineering MSc program and leads the Water & Environmental Engineering research group with 20 researchers. Dr Katsou's educational background includes a PhD in 'Wastewater Treatment with the Use of Membranes' (2008-2011), an MSc in Water Resources Science & Technology (2006-2008), and an MEng in Chemical Engineering (2000-2005), all from the National Technical University of Athens (NTUA), Greece. Her research program focuses on three interconnected areas: (1) Sustainable resource recovery from wastewater and safe reuse; (2) Data analytics, knowledge discovery and process modelling; and (3) Circularity & sustainability measurement and assessment. Dr Katsou has developed innovative approaches for biological nutrient removal from wastewater, including partial nitrification/denitrification and complete autotrophic nitrogen removal processes. Her work integrates advanced data analytics methods such as multivariate statistics, clustering techniques, machine learning algorithms, and artificial neural networks to identify complex relationships between process variables, particularly for measuring GHG emissions in water treatment systems. Dr Katsou has authored 98 journal publications (h-index: 27) and 12 book chapters with over 100 presentations, and holds a patent on biopolymers recovery. Her recent publications demonstrate a strong focus on circular economy applications in water systems, nature-based solutions for urban environments, and resource recovery technologies. The research trends show increasing integration of data-driven decision support systems with environmental sustainability metrics, particularly in the water-energy-food nexus domain. Chartered Chemical Engineer (Greece) HEA Fellow (FHEA) of the Higher Education Academy Mentor in the APEX (Academic Practice & Professional Excellence Framework) scheme Member of management group of the Royal Academy of Engineering (RAE) Visiting Professors Scheme Co-leader of Circular Economy VLT in Water Europe Leader of SMART WATER Working Group in ICT4Water Cluster-EC Member of ISO standards drafting team on Circular Economy Dr Katsou has successfully supervised 16 PhD students to completion and currently supervises several ongoing doctoral projects. She has secured substantial research funding as Principal Investigator on 11 national and international projects including RESILEX Horizon Europe, SYMBIOREM Horizon Europe, BORECER Horizon Europe, HYDROUSA H2020, and WATER-MINING H2020. Her industrial consulting portfolio includes significant contracts with leading UK water industry partners such as Affinity Water, Arup, Severn Trent, and Anglian Water, with projects ranging from carbon footprint assessment to corrosion mitigation and process optimization. She leads the Transformation Tools group of the Cost Action on Circular Cities, co-leads the Circular Water VLT of Water Europe, and co-leads the SMART-WATER group of the ICT4Water Cluster-EC. Dr Katsou is also a member of the drafting team for new ISO standards on Circular Economy (Measuring and Assessing Circularity - ISO5902).
Dr. Stavros Sakellariou serves as a Research Fellow (Marie Curie) in Civil and Environmental Engineering at Brunel University London's College of Engineering, Design and Physical Sciences. His expertise centers on geospatial analysis of natural disasters, particularly wildfires and droughts, leveraging remote sensing and AI for risk management. His educational background includes: PhD in Environmental Hazards Management and Spatial Planning, University of Thessaly (2016) MSc in Geospatial Technologies (Erasmus Mundus Joint Degree), 2016 MSc in Spatial Planning & Development, University of Thessaly (2010) MEng in Spatial Planning and Regional Development, University of Thessaly (2008) Dr. Sakellariou's research integrates geographic information systems , remote sensing , and artificial intelligence to address wildfire dynamics, drought/flood modeling, and climate change impacts. His work emphasizes spatial decision support systems for disaster prevention and resilience engineering in Mediterranean ecosystems, with significant contributions to early warning frameworks and urban-wildland interface safety. Recent publications reveal a concentrated focus on wildfire risk assessment (40% of works), drought monitoring (30%), and climate adaptation modeling (20%), predominantly utilizing satellite data fusion and spatiotemporal analytics. Key innovations include optimization methods for firefighting resource deployment and vulnerability assessments of agroecosystems. His accolades include: Marie Skłodowska-Curie Postdoctoral Fellowship (FIREWISE project, 2024) 7 national/international scholarships and awards With 11.5 years of teaching experience across undergraduate and master's programs at Greek universities, he has contributed to 8 multi-partner research projects on disaster management. His service includes reviewing for 25+ journals and guest-editing special issues on natural hazards. Current work centers on the FIREWISE project's integrated framework for proactive wildfire resilience.
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.
