جستجوی استاد راهنمای دانشگاهی

Sai Ravelaمشاهده پروفایل

پژوهشگر

• Nonlinear Stochastic Dynamics
• Coherent Fluids
• Uncertainty Quantification
• +۶ مورد دیگر

Sai Ravela is a Principal Research Scientist in the Department of Earth, Atmospheric and Planetary Sciences (EAPS) at the Massachusetts Institute of Technology (MIT). His research focuses on nonlinear stochastic dynamics, coherent fluid systems, uncertainty quantification, and autonomous observing technologies. He specializes in developing data-driven methodologies for natural hazard detection, climate change impacts, and environmental risk assessment. Ravela’s work integrates computational science with geophysical applications, including storm surge modeling, extreme rainfall analysis, and geothermal exploration. He pioneers techniques like neural dynamical systems and adversarial learning to improve predictive accuracy in nonstationary climate regimes. His contributions span environmental monitoring systems, autonomous aircraft resilience frameworks, and policy-informed climate vulnerability assessments. Key research areas include: Coastal flood risk in Bangladesh and Vietnam Dynamic data-driven applications systems (DDDAS) Machine learning for geosciences and environmental systems Uncertainty quantification in complex fluid dynamics He leads interdisciplinary projects at MIT’s Computational Science and Engineering (CSE) program, advancing methods for data assimilation, surrogate modeling, and real-time environmental observatories. His innovations bridge theoretical frameworks with practical solutions for climate adaptation and disaster resilience.

Kumar Varoon Agrawalمشاهده پروفایل

دانشیار

• Materials Science
• Chemical Engineering
• Membrane Technology
• +۴ مورد دیگر

Kumar Varoon Agrawal is an Associate Professor at École Polytechnique Fédérale de Lausanne (EPFL), holding the Gaznat Chair for Advanced Separations. He is affiliated with the School of Basic Sciences (SB), the Institute of Chemical Sciences and Engineering (ISIC), and the Laboratory of Advanced Separations (LAS) in Sion, Switzerland. Additionally, he contributes to the Swiss Doctoral School in Chemical and Bioengineering (SCGC) and serves as Vice President of the Confédération des Chimistes et des Génie Chimique (CCE). Research Focus: Material Chemistry & Engineering at the Ångström scale for high-performance inorganic and hybrid membranes, emphasizing energy-efficient molecular separations. Teaching: Courses include Fundamentals of separation processes , Diffusion and mass transfer , and Chemical engineering product design . Scientific Contributions: His 15 most recent publications (2025-2020) span topics like graphene pore engineering , 2D material synthesis , carbon capture , and gas separation membranes , with keywords such as Nanotechnology , Materials Science , and Molecular Transport . Subfields include Atomic-Scale Pores , Membrane Stability , and Industrial Scalability . Students and Collaborations: He advises 10 current PhD students and has mentored 9 past PhD candidates in areas like graphene membranes , ion separation , and MOF films . He is an Academic Referent for the EPFL Carbon Team and a committee member for the EDCH Doctoral Program in Chemistry and Chemical Engineering.

Leonardo Chamorroمشاهده پروفایل

استاد

• Aero/Hydrodynamics
• Wind and Hydrokinetic Energy
• Advanced Flow Diagnostics
• +۵ مورد دیگر

Leonardo Chamorro is a Professor in the Department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign (UIUC), with affiliations in Earth Science and Environmental Change, Aerospace Engineering, and Civil and Environmental Engineering. His research focuses on fluid dynamics, renewable energy systems, and turbulence modeling. He holds a Ph.D. in Civil Engineering from the University of Minnesota (2010) and has held academic positions at UIUC since 2013, advancing to Full Professor in 2024. Chamorro's work spans experimental and theoretical investigations of wind and hydrokinetic energy, geophysical flows, and particle dynamics. His research group, the Renewable Energy & Turbulent Environment Group (RE-TE-G), explores topics like tidal flow multifractality, vortex dynamics, and bio-inspired robotics. Key achievements include Nature and Lab on a Chip cover articles, and contributions to turbulence modeling for tidal energy systems. He has received awards such as the Best Paper Award in Energies (2018) and recognition for pandemic-related research (2021). His editorial roles include associate editorships at journals like Journal of Renewable and Sustainable Energy and Frontiers in Energy Research . Chamorro has supervised numerous graduate students and postdocs, contributing to over 150 peer-reviewed publications since 2009.

Esteban G. Tabakمشاهده پروفایل

استاد

• Fluid Dynamics
• Data Science
• Optimal Transport
• +۴ مورد دیگر

Esteban G. Tabak is a Professor of Mathematics at the Courant Institute of Mathematical Sciences, New York University. He holds a Ph.D. in Mathematics from MIT (1992) and a Hydraulic Engineer degree from the University of Buenos Aires (1988). His research spans fluid dynamics, data science, and optimization, with notable contributions to optimal transport theory, atmospheric and ocean modeling, and machine learning methodologies. He leads the Research and Training Group in Mathematical Modeling and Simulation at NYU. Research Interests include Data Analysis, Optimal Transport, Applied Mathematics, and Physics, particularly in fluid dynamics and geophysical flows. His work bridges theoretical advancements with practical applications, such as sea ice dynamics, internal waves, and turbulence modeling. Publications highlight innovations in density estimation, constrained optimization, and energy spectrum analysis of oceanic internal waves. Collaborations span disciplines, including biomedical applications (e.g., heart transplant diagnostics) and climate science. His methodologies, such as dual ascent algorithms and prototypal analysis, emphasize data-driven solutions to complex systems. Teaching includes courses on partial differential equations, fluid dynamics, and mathematical modeling. His work has been supported by grants addressing stratified flows, internal wave energy spectra, and turbulent mixing.

Sujan Palمشاهده پروفایل

پژوهشگر

• Hydrometeorology
• Hydroclimatology
• Land-Atmosphere Interactions
• +۴ مورد دیگر

Sujan Pal is a Hydroclimate Scientist at Argonne National Laboratory , focusing on hydrometeorology, hydroclimatology, and land-atmosphere interactions through numerical modeling and field experiments. He serves as an associate mentor for multiple observational systems in the Atmospheric Radiation Measurement (ARM) user facility and monitors environmental data at Argonne Testbed for Multiscale Observational Science (ATMOS). Ph.D., University of Illinois at Urbana-Champaign (2017-2021) M.S., The University of Arizona (2015-2017) B.E., Jadavpur University (2010-2014) His research spans hydrometeorological modeling, urban climate impacts, and machine learning applications in environmental science. He leads high-resolution flood simulations and contributes to the DOE-funded CROCUS project studying urban climate change in Chicago. Recent publications highlight his work on convection-permitting climate modeling, extreme rainfall dynamics, and flood risk assessment across South America, the U.S. Northeast, and Argentina. His methodologies integrate field data with advanced computational tools. ARM Service Award 2025 Argonne Commercialization Excellence Award 2024 Argonne IMPACT Awards (2024, 2023, 2022) He actively collaborates with national user facilities and contributes to spatiotemporal modeling of water-related hazards as an Associate Editor for Frontiers in Water .

Yiguang Juمشاهده پروفایل

استاد

• Energy Engineering
• Environmental Engineering
• Combustion Science
• +۴ مورد دیگر

Yiguang Ju is the Robert Porter Patterson Professor of Mechanical and Aerospace Engineering at Princeton University, affiliated with the HMEI Grand Challenges Program. His research focuses on plasma-assisted combustion, alternative fuels, and nano-material synthesis via flame processes. He investigates energy-efficient systems for microscale energy conversion, catalytic reactions, and low-temperature plasma chemistry. Research interests include non-equilibrium plasma dynamics, ammonia synthesis, and high-pressure oxidation kinetics. He develops advanced diagnostics like hybrid laser spectroscopy and machine learning models to study reaction mechanisms. Recent work explores plasma-enhanced combustion for hydrogen and alternative fuels, with applications in energy storage and emission reduction. His studies address challenges in plasma-chemistry interactions, material synthesis, and high-pressure combustion systems. His articles highlight innovations in plasma catalysis, combustion kinetics, and atmospheric chemistry. Collaborative projects include plasma-based material recycling and supercritical-pressure reactor analysis. He leads initiatives in clean energy technologies and sustainable chemical processes.

Matt Pritchardمشاهده پروفایل

استاد

• Volcanology
• Geodesy
• Remote Sensing
• +۴ مورد دیگر

Prof. Matt Pritchard is a Professor in Earth & Atmospheric Sciences at Cornell University, based at Snee Hall. His research focuses on volcanology, geodesy, and remote sensing, with a particular emphasis on using satellite data to monitor volcanic activity, deformation, and glacial interactions. He leads studies on global volcanic systems, including Indonesia's Semeru and Raung volcanoes, Chile's Cordón Caulle, and Bolivia's Uturuncu, applying techniques like InSAR, SAR, and thermal imaging. Key research interests include volcanic eruption dynamics, magma-hydrothermal systems, and the integration of multi-sensor datasets. He has contributed to developing tools like Hotspotter for automated volcanic thermal feature detection and has explored planetary volcanism (e.g., Venus). His work bridges geophysics, glaciology, and computational methods, addressing both Earth and extraterrestrial systems. Prof. Pritchard has received recognition such as the William Bowie Lecture (2022, 2023). His projects often involve international collaborations, including the CEOS Volcano Demonstrator initiative and the EarthDEM/ArcitcDEM projects. He also engages in geothermal energy research and seismic monitoring in Ithaca, NY.

Aurora Maccaroneمشاهده پروفایل

پژوهشگر ارشد

• Single-Photon Imaging
• Underwater LiDAR
• Quantum Sensing
• +۴ مورد دیگر

Aurora Maccarone serves as an RAEng Research Fellow within the Institute of Photonics and Quantum Sciences at Heriot-Watt University's School of Engineering & Physical Sciences. Her work focuses on advanced photonics applications for challenging environments, particularly underwater and obscured conditions. Her research expertise spans: Single-photon LiDAR systems for underwater 3D imaging Photon-counting detector arrays for depth profiling Real-time reconstruction algorithms for obscurant-penetrating imaging Quantum sensing applications in marine environments Recent publications demonstrate consistent innovation in single-photon imaging techniques, with emphasis on underwater applications (2023-2024) and obscurant penetration (2022). Her work shows strong interdisciplinary connections between optical engineering, computational imaging, and environmental sensing. Key publications reveal growing impact in underwater LiDAR technology, with multiple high-citation papers on photon-efficient imaging systems. Dr. Maccarone actively supervises PhD students and has created significant research datasets. Her collaborations span international institutions, with notable contributions to sensor hardware development and computational imaging algorithms. Recent work shows increasing integration of machine learning techniques with traditional photon-counting approaches.

Chenming Zhangمشاهده پروفایل

پژوهشگر ارشد

• Hydrology
• Groundwater hydrology
• Environmental Sciences
• +۷ مورد دیگر

Dr. Chenming Zhang is an Advanced Queensland Industry Research Fellow at the School of Civil Engineering, The University of Queensland. His research focuses on hydrological processes in coastal and terrestrial groundwater systems, with particular emphasis on evaporation-driven mass and heat transport in soils and tailings, and hydrogeochemical dynamics in aquifers and mine waste systems. Specializes in IoT-based environmental monitoring Develops numerical models for coastal aquifer dynamics Conducts field and laboratory experiments on tailings behavior Research interests span coastal hydrology, groundwater modeling, mine waste management, and environmental monitoring. He works on contamination transport, aquifer protection, and climate impacts on water systems. Recent publications analyze: Iron curtain formation in subterranean estuaries Sea water intrusion mechanisms Salinity dynamics in tidal wetlands Smart sewer monitoring systems Scientific awards include the prestigious Advanced Queensland Industry Research Fellowship. He supervises multiple PhD projects on mine waste hydrology and coastal aquifer management, with notable collaboration on: Evolution Mining's gold tailings projects ARC Discovery Projects on coastal processes Grange Resources' PAF cell instrumentation His work combines field measurements, laboratory testing, and computational modeling to address critical environmental challenges in mining and coastal zones.

Peter Huybersمشاهده پروفایل

استاد

• Climate change
• Paleoclimatology
• Environmental science
• +۸ مورد دیگر

Peter Huybers is a Professor of Earth and Planetary Sciences and Environmental Science and Engineering at Harvard University , where he investigates the climate system and its societal implications, including interactions between volcanism and glaciation , extreme temperature predictability , and climate change impacts on food production . Research interests span climate change attribution , paleoclimate reconstruction , drought dynamics , crop yield modeling , and earth system feedbacks . His work often integrates art-historical analysis with climate science, as seen in studies of 19th-century air pollution through Turner and Monet paintings . Scientific awards include funding from Harvard Data Science Initiative (2023) for projects on climate change and food supply volatility Amazon Web Services (2023) grant His 20+ peer-reviewed articles since 2020 focus on climate proxies , hydrological modeling , solar forcing , and agricultural-climate interactions , with recent work in Nature , PNAS , and Science Advances . Advising : Mentored 10+ PhD students including Parker Liautaud , Duo Chan , and Marena Lin , while leading research teams with current members like Greta Berendes and Caro Park . Former staff include Jon Proctor and Lucas Vargas Zeppetello , the latter now at UC Berkeley (2024).

• Geohazards
• Landslides
• Debris flows
• +۵ مورد دیگر

Scott McDougall is an Associate Professor in the Department of Earth, Ocean & Atmospheric Sciences at the University of British Columbia (UBC). He specializes in geohazards, particularly landslides and related risks, with a focus on improving risk assessment and mitigation strategies. His work integrates field data, statistical analysis, numerical modeling, and laboratory experiments to understand landslide dynamics. Education: PhD in Geological Engineering, UBC (2006) BASc in Civil Engineering, University of Toronto (1998) Research Interests: Landslide mobility and runout modeling Tailings dam breaches and their impacts Risk evaluation frameworks for geohazards Shoreline erosion and landslide-generated waves Applications of machine learning in hazard prediction Key Contributions: Development of the UBC Geohazards Research Team to advance landslide risk reduction Leadership in the CanBreach project to improve tailings dam breach analysis Pioneering probabilistic runout prediction models for rock avalanches and debris flows Awards: Engineering Geology Best Paper Award 2024 CDA Published Paper Award Advising & Grants: Supervised over 15 graduate students and postdoctoral fellows Active industry collaborations with mining and engineering firms Funded by NSERC, Mitacs, and industry partnerships Labs & Teams: UBC Geohazards Research Team CanBreach Collaborative Research and Development Project

James R. Fienupمشاهده پروفایل

استاد

• Imaging Science
• Phase Retrieval
• Unconventional Imaging
• +۸ مورد دیگر

James R. Fienup is the Robert E. Hopkins Professor of Optics at the University of Rochester's Institute of Optics, with additional appointments as Distinguished Scientist at the Laboratory for Laser Energetics, Professor at the Center for Visual Science, Professor of Electrical and Computer Engineering, and Affiliated Faculty at the Goergen Institute for Data Science and Artificial Intelligence. His office is located at Wilmot 410, 275 Hutchison Rd., Rochester, NY. Education PhD in Applied Physics from Stanford University (1975) MS in Applied Physics from Stanford University (1972) BA in Physics & Mathematics (magna cum laude) from Holy Cross College (1970) Research Focus Professor Fienup's research specializes in imaging science , with emphasis on phase retrieval algorithms, unconventional imaging techniques, and wavefront sensing. His work spans computational methods for image reconstruction, sparse-aperture systems, and synthetic-aperture imaging. Recent innovations include applying machine learning to wavefront control and developing advanced digital holography techniques for 3D imaging through atmospheric turbulence. Publication Trends His recent articles (2018-2024) demonstrate a strong focus on computational imaging techniques, particularly phase retrieval algorithms applied to optical metrology and wavefront correction. Key themes include multi-plane digital holography, coronagraphic wavefront control for astronomical applications, machine learning-enhanced sensing, and novel approaches for segmented-aperture systems. His work consistently bridges theoretical optics with practical instrumentation challenges. Awards and Honors Lifetime Achievement Award, Hajim School of Engineering (2019) Emmett N. Leith Medal, Optical Society of America (2013) National Academy of Engineering Member (2012) Distinguished Visiting Scientist, JPL (2009) Fellow of OSA and SPIE International Prize in Optics (1983) Rudolf Kingslake Medal (1979) NSF Graduate Fellow (1970-1972) Professional Activities Professor Fienup has served as Editor-in-Chief of the Journal of the Optical Society of America A (1998-2003) and held editorial roles at Applied Optics and Optics Letters . He consults for NASA (James Webb Space Telescope, Hubble), national laboratories, and aerospace companies, and holds five patents in optical systems design.

Svetlana Stanišićمشاهده پروفایل

دانشیار

• Environmental Science
• Air Pollution Modeling
• Artificial Intelligence Applications
• +۷ مورد دیگر

Svetlana Stanišić is an Associate Professor at Singidunum University's Faculty of Informatics and Computer Science, Department of Applied Artificial Intelligence. She holds a dental degree from the University of Belgrade's Dental Faculty (1998-2004) and a PhD in Physical Chemistry from the University of Belgrade's Faculty of Physical Chemistry (2007-2011). Her interdisciplinary research bridges environmental science, artificial intelligence, and public health. Her research interests focus on environmental science, air pollution modeling, and artificial intelligence applications . She investigates the atmospheric fate of pollutants using advanced machine learning techniques, with particular emphasis on polycyclic aromatic hydrocarbons (PAHs), volatile organic compounds (VOCs), and particulate matter. Her work combines environmental chemistry, computational modeling, and public health impact assessment to address urban air quality challenges. Analysis of her recent publications reveals a clear trend toward explainable AI applications in environmental science . She has pioneered the use of SHAP (SHapley Additive exPlanations), XGBoost, and metaheuristic optimization for pollutant fate prediction and source apportionment. Her research spans indoor and outdoor environments, with particular attention to health implications of air pollution exposure in urban settings like Belgrade. Dr. Stanišić leads significant research projects including "crAIRsis" (2024-2026) , which characterizes crisis-caused air pollution alternations using AI frameworks, and "ATLAS" , focusing on artificial intelligence theoretical foundations for spatio-temporal modeling. She has also authored influential books including "Ako je hrana Vaš porok" (2024) and "Ishrana i zdravlje" (2018). Her research group focuses on environmental informatics , developing computational tools to understand pollutant behavior in complex urban environments. The team combines atmospheric chemistry measurements with advanced machine learning techniques to create predictive models with practical applications for urban air quality management and public health protection.

Markus Reichsteinمشاهده پروفایل

استاد

• Biogeochemistry
• Climate Science
• Ecosystem Ecology
• +۴ مورد دیگر

Markus Reichstein is a Professor for Global Geoecology at Friedrich Schiller University (FSU) Jena and Director of the Biogeochemical Integration Department at the Max Planck Institute for Biogeochemistry. His research focuses on ecosystem responses to climate variability, climate extremes, and the application of AI in Earth system science. He holds a PhD in Plant Ecology from the University of Bayreuth and has pioneered interdisciplinary approaches combining machine learning with environmental modeling. Key roles include leadership in the Michael-Stifel-Center Jena for Data-driven and Simulation Science and founding director of the ELLIS Unit Jena. He contributed to the IPCC Special Report on Climate Extremes and has received prestigious awards such as the Leibniz Prize. His work bridges ecology, hydrology, and atmospheric science, addressing critical global challenges like carbon cycle feedbacks and ecosystem resilience. Recent research emphasizes AI-driven early warning systems for climate risks, integrating observational data with mechanistic models. His team explores land-atmosphere interactions, soil-vegetation dynamics, and the impacts of climate extremes on societal systems. Notable projects include GartenDiv, a citizen science initiative for garden biodiversity, and advancements in global water cycle modeling using hybrid AI-physics frameworks. Awards include the Piers J. Sellers Award (2018), ERC Synergy Grant (2019), and Leibniz Prize (2020). He collaborates with international networks like ELLIS and Future Earth, advancing data-driven solutions for sustainability science.

Daniel Varonمشاهده پروفایل

استادیار

• Atmospheric Science
• Environmental Science
• Satellite Remote Sensing
• +۳ مورد دیگر

Daniel Varon is the Boeing Assistant Professor in Aeronautics and Astronautics at MIT, joining in July 2025. He is also affiliated with the MIT Institute for Data, Systems, and Society (IDSS). His research focuses on atmospheric composition, satellite remote sensing of greenhouse gases, and air pollution. Varon holds a PhD in Atmospheric Chemistry from Harvard University (2020), an MSc in Applied Mathematics, and dual undergraduate degrees in English Literature and Physics from McGill University. He has held postdoctoral roles at Harvard and Princeton University. His work uses satellite data to quantify methane and nitrogen oxide emissions, with applications in climate policy and environmental monitoring. Notable contributions include developing methods for detecting methane super-emitters via hyperspectral satellites and quantifying emissions from oil/gas fields. Varon has received over 3,000 citations and an h-index of 24 as of 2025, with extensive media coverage for his Nord Stream pipeline leak analysis. Varon has secured grants totaling $785K, including NOAA funding for geostationary satellite methane monitoring. He mentors postdocs and graduate students in satellite data analysis and machine learning applications. His teaching includes Harvard’s Atmospheric Chemistry course, where he received the Harvard Certificate of Distinction in Teaching. Varon serves as an Associate Editor for Atmospheric Measurement Techniques and contributes to initiatives like the Methane Emissions Detection Using Satellites Assessment (MEDUSA) Advisory Board. His lab focuses on integrating machine learning with satellite data to advance climate science.