جست‌وجوی استاد و پژوهشگر

• Isotope Geochemistry
• Climate Science
• Greenland Ice Sheet Studies
• +۴ مورد دیگر

Getachew Agmuas Adnew is a Postdoctoral Researcher in Forest and Landscape Ecology at the Department of Geosciences and Natural Resource Management, Faculty of Science, University of Copenhagen. His research focuses on isotope geochemistry applications to understand climate-relevant processes in extreme environments. Dr. Adnew's research interests center on isotope geochemistry , particularly clumped isotope measurements to investigate methane dynamics beneath the Greenland ice sheet and atmospheric CO 2 composition. His work bridges glaciology, atmospheric science, and climate change research, with significant contributions to understanding subglacial biogeochemical processes. He also participates in interdisciplinary projects like CloudRoots-Amazon22 that examine land-atmosphere interactions across multiple scales. Analysis of his 18 research outputs (15 journal articles and 3 conference abstracts from 2023-2025) reveals a strong thematic focus on methane emissions from subglacial environments and atmospheric isotope signatures . His work frequently employs advanced isotopic techniques to trace biogeochemical processes relevant to climate change. The research demonstrates increasing collaboration across international boundaries, particularly with European and South American institutions. Dr. Adnew actively collaborates with major climate research groups, including those led by T. Röckmann, T. Blunier, and C.J. Jørgensen. His work appears in high-impact journals such as Geochimica et Cosmochimica Acta, Atmospheric Measurement Techniques, and Bulletin of the American Meteorological Society. His research has garnered attention across academic platforms with multiple citations and mentions in scientific networks. His current research involves field work at the Greenland ice sheet margin and analysis of atmospheric samples from various global locations. The ongoing projects suggest continued focus on understanding the connections between subglacial processes and global climate systems through innovative isotopic approaches.

• Machine Learning
• Visual Computing
• Image Analysis
• +۶ مورد دیگر

Soumya Dutta is an Assistant Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Kanpur (IITK), where he leads the INSIGHT: Intelligent Scientific and Visual Computing of Big Data Research Group. He joined IIT Kanpur in October 2022 after working as a Scientist II at Los Alamos National Laboratory (LANL) from July 2019 to August 2022, and previously as a Postdoctoral Research Associate at LANL from June 2018 to July 2019. His educational background includes a Ph.D. and M.S. in Computer Science and Engineering from The Ohio State University (2011-2018), where he was part of the GRAVITY research group, and a B.Tech. in Electronics and Communication Engineering from West Bengal University of Technology, India (2005-2009). Research Interests: Dr. Dutta's research focuses on the intersection of machine learning, visual computing, big data, and high-performance computing. His primary research areas include Machine Learning for Visual Computing and Image Analysis, Big Data Visualization and Analytics, Data Science and HPC, Machine Learning for Scientific Computing, and Explainability and Interpretability of AI Models. His work addresses various big data characteristics including the 5 Vs: Volume, Velocity, Variety, Veracity, and Value. He develops techniques that make complex machine learning models more interpretable and explainable, enabling their effective adoption in real-life applications across scientific domains, social media, IoT, healthcare, and industry applications. Dr. Dutta's research group has secured multiple funded projects including: DAVi: An Intelligent Data Analytics and Visualization Framework (funded by ISRO), Intelligent Visual Computing of Extreme-scale Data for Accelerating Scientific Discovery (IIT Kanpur Initiation Grant), Enabling Interactive Big Data Analytics and Visualization at Exascale (SERB), Development of AI-Enabled National Portal for Efficient Search of Missing People (C3iHub), and Proactive and Generalized Deepfake Defense Mechanisms (C3iHub). Best Reviewer, Honorary Mention Award for IEEE Transactions on Visualization & Computer Graphics (TVCG), 2021 Best Paper Award at ISAV 2021, co-located with Supercomputing (SC) LAAP Award at Los Alamos National Laboratory, 2021 Best Paper Award at TopoInVis 2019 Best Paper Award at ISAV 2018, co-located with Supercomputing (SC) Best Poster Award in 12th Annual CSE Student Poster Exhibition, The Ohio State University, 2018 Best Poster Award in 11th Annual CSE Student Poster Exhibition, The Ohio State University, 2017 Best Paper Honorable Mention Award at IEEE Visualization Conference (IEEE VIS) 2016 Dr. Dutta actively mentors a large group of students including Ph.D., M.Tech., and B.Tech. students. His current Ph.D. students include Shanu Saklani, Sankhadeep Bhowmick, Ananya Chaturvedi, Arpita Santra, Anubhav Dixit (co-supervised), and Robin Shah. He has supervised numerous M.Tech. students with thesis topics ranging from uncertainty-aware neural networks to deepfake detection. Dr. Dutta currently teaches courses including CS360 - Introduction to Computer Graphics and CS661 - Big Data Visual Analytics. The INSIGHT research group collaborates internationally with researchers from Meta, Oak Ridge National Laboratory, and National Taiwan Normal University. The group's work focuses on building machine learning and data science-based solutions to analyze large-scale multifaceted data in a scalable way, enabling interactive and interpretable analytics of complex data from scientific simulations, social media, IoT, healthcare, and other application domains.

Lorenzo M. Polvaniمشاهده پروفایل

استاد

• Atmospheric Science
• Climate Modeling
• Arctic Studies
• +۴ مورد دیگر

Lorenzo M. Polvani is the Maurice Ewing and J. Lamar Worzel Professor of Geophysics at Columbia University, with dual appointments in the Department of Applied Physics and Applied Mathematics and the Department of Earth and Environmental Sciences. He has taught at Columbia for over 30 years and received multiple teaching awards. PhD in Physical Oceanography, MIT/Woods Hole Joint Program (1988) MSc and BSc in Physics, McGill University His research spans Atmospheric Science , Climate Modeling , and Arctic Studies , focusing on geophysical fluid dynamics, radiative forcing, and climate sensitivity. Recent work examines nonlinear climate responses to CO2 variations, Arctic amplification mechanisms, and volcanic aerosol impacts. Scientific publications reveal trends in radiative forcing , Arctic sea ice dynamics , stratospheric ozone effects , and climate feedback interactions . Key tools include the ClimKern Python package for radiative feedback analysis. Notable research includes: Nonlinear precipitation responses to volcanic eruptions High CO2 forcing effects on North Atlantic Oscillation Cloud feedbacks reducing hydrological sensitivity Arctic amplification through radiative-advective equilibrium Stratospheric ozone impacts on tropical climate patterns

Cathryn Mitchellمشاهده پروفایل

استاد

• Radio Science
• Space Weather
• Position, Navigation and Timing (PNT)
• +۴ مورد دیگر

Cathryn Mitchell is a Professor of Radio Science and Royal Society Industry Fellow at the University of Bath, specializing in ionospheric physics, position, navigation, and timing (PNT). She leads research in the Space & Telecoms Research Group (STAR), focusing on radio propagation, data assimilation, and space weather impacts on communication systems. Her work bridges theoretical, computational, and experimental approaches, with applications in satellite navigation, climate monitoring, and defense sectors. Her research interests include ionospheric tomography, HF communications, and the development of robust PNT systems. Mitchell collaborates extensively with industry partners like Spirent Communications on future navigation technologies and space weather resilience. She has held roles such as Academic Director of the Doctoral College and contributes to interdisciplinary projects like the DRIIVE initiative exploring ionospheric variability with EISCAT-3D radar. Recent work emphasizes ionospheric effects during geomagnetic storms (e.g., the 2024 Gannon Storm) and cooperative autonomous systems under communication constraints. Her projects are funded by the Royal Society, Natural Environment Research Council (NERC), and ESA, addressing challenges in space weather forecasting and PNT system reliability. Awards: Royal Society Industry Fellow (2022–present) Key Projects: Royal Society Industry Fellowship on Future PNT Technologies DRIVERS (DRIIVE): Ionospheric Variability Studies EISCAT-3D FINESSE: Ionospheric Structuring Analysis Mitchell’s lab, STAR, integrates academic and industrial partnerships to advance space weather applications and sustainable navigation systems, contributing to UN Sustainable Development Goals related to climate action and innovation.

Dominik Büelerمشاهده پروفایل

پژوهشگر

• Subseasonal-to-Seasonal Prediction
• Weather Regimes
• Extratropical Cyclones
• +۴ مورد دیگر

Dr. Dominik Büeler is a Researcher at ETH Zurich's Institute for Atmospheric and Climate Science and staff member of the Center for Climate Systems Modeling (C2SM). His work bridges atmospheric dynamics with practical climate services, focusing on subseasonal prediction systems and their societal applications in Europe. Research Focus: Büeler's work centers on subseasonal-to-seasonal prediction, with emphasis on weather regime dynamics, extratropical cyclone behavior, and stratosphere-troposphere interactions. His research integrates large ensemble modeling, forecast verification, and climate impact assessment, particularly for European weather extremes. Recent projects examine heatwave mortality prediction, energy meteorology applications, and the role of moist processes in atmospheric blocking. Analysis of his publication record since 2021 reveals consistent advancement in subseasonal forecasting methodology, with growing emphasis on societal applications including public health (heat-related mortality) and energy sectors. His work increasingly connects fundamental atmospheric processes with operational forecasting systems, leveraging collaborations through the Subseasonal-to-Seasonal Prediction Project. Affiliations: Center for Climate Systems Modeling (C2SM) - Core Research Staff ETH Zurich Institute for Atmospheric and Climate Science MeteoSwiss Collaborator (Energy Meteorology) Büeler contributes to multidisciplinary teams developing climate services, with recent work supporting Swiss operational forecasting systems. His research group within C2SM focuses on improving subseasonal predictability through advanced diagnostics of model biases and atmospheric processes.

Simon Carnمشاهده پروفایل

استاد

• Volcanology
• Remote Sensing
• Atmospheric Chemistry
• +۵ مورد دیگر

Simon Carn is a Professor in the Department of Geological and Mining Engineering and Sciences at Michigan Technological University, specializing in satellite-based monitoring of volcanic degassing and atmospheric pollution. His work leverages NASA satellite constellations to quantify sulfur dioxide emissions and their climate impacts. Education: PhD in Volcanology from Cambridge University MS in Volcanology and Magmatic Processes from Université Blaise Pascal BA in Earth Sciences from Oxford University Research Focus: Carn pioneers the use of space-borne sensors like OMI and TEMPO to measure volcanic SO 2 , ozone, and other trace gases. His research bridges satellite observations with climate modeling to understand sulfate aerosol formation, volcanic cloud transport, and anthropogenic pollution sources. Key methodologies include DOAS/FTIR remote sensing, satellite-ground data validation, and aviation hazard mitigation systems. Publication Trends: Recent work (2023-2025) centers on high-cadence monitoring via geostationary satellites (TEMPO, DSCOVR/EPIC), analysis of major eruptions (Hunga Tonga, Raikoke), and extending 20+ years of global SO 2 records. Research emphasizes volcanic-climate interactions, eruption response protocols, and quantifying underreported passive degassing that affects climate models.

Andrew Gettelmanمشاهده پروفایل

پژوهشگر

• Atmospheric sciences
• Climatology
• Climate modeling
• +۶ مورد دیگر

Andrew Gettelman is a distinguished climate scientist at Pacific Northwest National Laboratory whose research spans atmospheric sciences, climatology, and climate modeling. With a D-index of 91 and over 32,652 citations across 343 publications, he ranks 422nd globally and 194th nationally in Environmental Sciences. His research interests focus on fundamental climate processes including cloud microphysics, aerosol-cloud interactions, stratospheric dynamics, and climate model development. Gettelman has made significant contributions to understanding Arctic climate feedbacks, particularly how clouds respond to sea ice loss, and has advanced the representation of aerosols in climate models through his work on the Community Atmosphere Model (CAM). Analysis of his publication trends reveals a consistent focus on improving climate model representations of atmospheric processes, with recent work emphasizing climate sensitivity in the Community Earth System Model (CESM2) and bounding global aerosol radiative forcing. His research bridges fundamental atmospheric science with practical applications for understanding climate change. Among his recognitions, Gettelman has been named to the World's Best Scientists 2025 list. His highly cited works include foundational papers on cloud microphysics schemes and aerosol representation in climate models. Gettelman maintains extensive collaborative networks, frequently working with researchers from the National Center for Atmospheric Research, University of Colorado Boulder, and other leading climate institutions. His research has been instrumental in advancing climate modeling capabilities used in major international climate assessments.

• Solar variability
• Stratosphere-Troposphere coupling
• Ocean-Atmosphere coupling
• +۱۶ مورد دیگر

Dr. Indrani Roy is an Honorary Associate Professor in the Department of Earth Sciences at University College London (UCL). She holds a PhD from Imperial College London and has extensive research experience at institutions including Imperial College and the University of Exeter. Previously, she served as a permanent employee at the India Meteorological Department (Government of India). She is a Fellow of the Royal Meteorological Society (FRMetS) and serves as its Trustee. Dr. Roy contributes to international scientific governance as a panel member for the UK's Natural Environmental Research Council (NERC) and the Romanian National Research Council. Her multidisciplinary research spans: Solar-atmosphere-ocean coupling mechanisms Monsoon dynamics and teleconnection patterns Climate change processes and extreme events Stratosphere-troposphere interactions Climate variability across decadal scales She actively investigates how solar cycles influence regional climates and extreme weather phenomena. Dr. Roy's publications demonstrate consistent focus on climate dynamics with recent emphasis on African and Asian monsoon systems, COVID-19 climate interactions, and improving predictive capabilities for extreme rainfall events. Her work increasingly integrates public health perspectives with climate science. Scientific Recognition: Fellow of the Royal Meteorological Society (FRMetS) Teaching & Advising: As an Associate Fellow of the Higher Education Academy (HEA), she currently teaches the Literature Project module (NSCI0004) for Natural Sciences at UCL. Her past teaching includes: Undergraduate research supervision (University of Exeter) Masters project supervision and guest lecturing (UCL) Instruction of Masters/PhD candidates (University of Oulu, Finland) Professional Engagement: Dr. Roy serves as reviewer for over 40 international journals (including Nature Geoscience and Science Reports) and grant agencies such as NSF, Royal Society, and French National Research Agency. She co-convenes sessions at major conferences (AOGS) and previously held editorial roles at Frontiers journals.

Jonathan Weareمشاهده پروفایل

استاد

• Monte Carlo sampling
• Multiscale analysis
• Randomized numerical linear algebra
• +۲ مورد دیگر

Jonathan Weare is a Professor of Mathematics at the Courant Institute of Mathematical Sciences, New York University. He holds affiliations with the Faculty of Arts and Science and the Graduate School of Arts and Science. His academic journey includes roles as an Associate Professor at the University of Chicago (2014–2019) and Assistant Professor (2011–2014), following postdoctoral work as a Courant Instructor at NYU. He earned his Ph.D. in Mathematics from UC Berkeley in 2007. His research focuses on stochastic algorithms and models, with applications in astrophysics, biophysics, computational chemistry, and climate science. Key areas include Monte Carlo methods, rare event simulation, and machine learning-driven scientific analysis. Collaborations with domain experts ensure his work addresses real-world challenges in diverse fields. Recent publications emphasize advancements in trajectory stratification, rare event prediction using machine learning, and efficient algorithms for high-dimensional problems. Notable contributions include the BAD-NEUS framework and AI-based solar system instability predictions. His group’s interdisciplinary approach bridges computational methods with scientific inquiry. Weare has advised numerous students and mentored postdocs, fostering talent in applied mathematics and computational science. His work on Mercury’s orbital dynamics and extreme weather prediction showcases the societal impact of his research. Current projects explore AI applications in weather modeling and rare event analysis, leveraging cutting-edge machine learning techniques. Labs/Teams: His research group at Courant develops stochastic algorithms and collaborates with interdisciplinary teams in computational chemistry, climate science, and astrophysics. Key collaborations include the University of Chicago and Columbia University.

Michael P. Byrneمشاهده پروفایل

دانشیار

• Climate Dynamics
• Atmospheric Science
• Monsoons
• +۳ مورد دیگر

Dr. Michael P. Byrne is an Associate Professor at the School of Earth and Environmental Sciences , University of St Andrews, and a Marie Skłodowska-Curie Research Fellow at the Atmospheric, Oceanic and Planetary Physics Group , University of Oxford. His research focuses on climate dynamics, monsoons, land-climate interactions, and the water cycle. He leads the Climate Dynamics Lab at St Andrews, exploring topics like cloud feedbacks, tropical climate change, and continental-ocean temperature contrasts. He completed his PhD at MIT under Paul O’Gorman. His work bridges theory, models, and observations to address fundamental climate questions, including monsoon dynamics, intertropical convergence zone behavior, and extreme temperature amplification over tropical land. Key contributions include studies on ITCZ width impacts, elevation-dependent warming, and biases in precipitation projections. Education: PhD from Massachusetts Institute of Technology (advisor: Paul O’Gorman) Research Highlights: Cloud feedback mechanisms in tropical climates Land-ocean warming contrasts and their societal impacts ITCZ dynamics and global climate modeling Awards: Marie Skłodowska-Curie Fellowship (Oxford) Labs/Teams: Climate Dynamics Lab (St Andrews), ITCZ-MIP collaboration

• Computer Vision
• Human Pose Estimation
• Gesture Recognition
• +۴ مورد دیگر

Stephanie Käs is a Researcher at RWTH Aachen University specializing in Human Pose Estimation (HPE) and gesture recognition using CNN-based methods and Video Language Models applied to fisheye imagery. Her interdisciplinary background spans particle physics and railway engineering data science projects, with strong emphasis on science communication and agile project management. Her research focuses on overcoming challenges in 3D human pose estimation from distorted fisheye images, temporal consistency in motion recognition, and gesture-based human-robot interaction. She actively develops novel approaches for monocular 3D pose estimation and foundation model applications in robotics, with contributions to datasets like FISHnCHIPS for fisheye image analysis. Stephanie supervises multiple ongoing theses including motion recognition, visual anonymization, and anatomical realism evaluation in AI-generated imagery. She leads the Stratospheric Balloon Research Project (StratoGI) at JLU Gießen and has extensive teaching experience in machine learning, computer vision, and statistics at RWTH Aachen and JLU Gießen.

Valentin P. Dymnikovمشاهده پروفایل

استاد

• Numerical models of short-range weather prediction
• Theory of baroclinic instability in moist atmosphere
• Transport and transformations of humidity fields in atmosphere
• +۸ مورد دیگر

Valentin P. Dymnikov is a Professor and Director of the Institute of Numerical Mathematics at the Russian Academy of Sciences. His career spans decades of leadership in geophysics and atmospheric modeling, with significant contributions to climate science and meteorology. Academic Positions: Director of Institute of Numerical Mathematics (2000–present); Head of Department of General Circulation Atmosphere Modelling (1980–2000); Head of Department of Numerical Weather Prediction (1971–1974). Education: Doctor of Sciences in Geophysics (1981) and Candidate of Science in Geophysics (1970), both from the Main Geophysical Observatory in St. Petersburg. Research Interests: Valentin's work focuses on numerical weather prediction, climate modeling, atmospheric dynamics, and mathematical methods in meteorology. Key areas include baroclinic instability, humidity transport, attractors in atmospheric models, and atmosphere-ocean interactions. Scientific Awards: 1990: Member-correspondent of USSR Academy of Sciences 1993: A. Friedman Award for dynamical meteorology 1997: Full member of Russian Academy of Sciences 2000: State Prize for models/methods in atmosphere-ocean problems

Waël Jaafarمشاهده پروفایل

استاد

• Wireless Communications
• 5G/6G Networks
• Space Telecommunications
• +۷ مورد دیگر

Waël Jaafar is a Professor in the Department of Software Engineering and IT at École de technologie supérieure (ETS), a constituent school of the Université du Québec system in Montreal, Canada. His research spans multiple critical domains in modern communications and computing infrastructure, with a particular focus on next-generation wireless networks and intelligent systems. Dr. Jaafar holds a B.Eng. from Sup'Com Tunisie, and both M.Sc.A. and Ph.D. degrees from Polytechnique Montréal. His academic background provides a strong foundation for his interdisciplinary research that bridges theoretical concepts with practical engineering solutions. His research interests center around wireless communications systems, with particular emphasis on 5G/6G networks, UAV communications, space telecommunications, and machine learning applications for networking. He has developed significant expertise in federated learning techniques for distributed networks, cybersecurity applications for next-generation mobile systems, and edge computing architectures. His work frequently explores the intersection of communication theory, artificial intelligence, and network security, with applications ranging from industrial IoT to public safety communications. Analysis of his recent publications reveals a strong trend toward integrating artificial intelligence with wireless networking infrastructure, particularly focusing on UAV-assisted communications, federated learning approaches for distributed networks, and security enhancements for 5G/6G systems. His research demonstrates increasing emphasis on practical implementation challenges including energy efficiency, communication overhead reduction, and reliability in non-ideal network conditions. As an academic supervisor, Dr. Jaafar actively mentors numerous graduate students across various projects. He currently supervises doctoral candidates working on blockchain-enhanced security for 5G networks, green network slice orchestration, and federated learning approaches for Open RAN architecture. His master's students are engaged in diverse topics including LiDAR-based power line monitoring, multimodal behavioral authentication, and 5G/6G security using AI techniques. Dr. Jaafar is affiliated with two prominent research laboratories at ETS: LASI (Computer System Architecture Research Laboratory) and LACIME (Communications and Microelectronic Integration Laboratory). At LASI, he contributes to research in AI-based systems engineering, resource orchestration in edge/cloud environments, and intelligent network design. Through LACIME, he engages with broader communications research spanning from microelectronic components to complex communication systems, with particular focus on wireless networks and signal processing applications.

• Climate
• Climate change
• Climate dynamics
• +۹ مورد دیگر

Jost-Diedrich Graf Von Hardenberg is a Full Professor in the Department of Environmental, Land and Infrastructure Engineering (DIATI) at the Polytechnic University of Turin. He serves as the Energy and Climate Change Area Coordinator and is a Scientific Advisor of the HPC-AI Advisory Council. His research focuses on climate science and geophysical fluid dynamics, with significant contributions to understanding climate change impacts and Earth system modeling. Professor Von Hardenberg's research interests span multiple areas of climate science, including climate dynamics, geophysical fluid mechanics, hydrological cycle analysis, numerical climate modeling, and precipitation downscaling. His work particularly emphasizes climate tipping points and extremes, Rayleigh-Bénard convection in geophysical contexts, high-resolution Earth-system climate modeling, and stochastic approaches to precipitation downscaling. His research integrates theoretical, computational, and observational approaches to address fundamental questions about climate system behavior and change. His recent publications demonstrate a strong focus on Atlantic Meridional Overturning Circulation (AMOC) dynamics, climate extremes in Alpine regions, urban climate effects, and interdisciplinary applications of climate science to ecological and conservation challenges. His work bridges fundamental climate dynamics with practical applications for climate adaptation and environmental management. Among his notable recognitions are the Research in Paris award from the Maire de Paris (2009) and Fellowships at the London School of Economics and Political Science (2001-2002, 2004-2006). He has participated in numerous research networks including the European Geosciences Union section 'Nonlinear Processes in Geophysics' (2004-2012), the EC-Earth Consortium (2012-present), and COST Action ES0805 TERRABITES 'The terrestrial biosphere in the earth system' (2010-2014). Professor Von Hardenberg actively supervises PhD students including Marianna Albanese, Maria Clara Corda, Sara Filippini, and Jacopo Grassi, among others. He leads multiple significant research projects such as ROTurb (Resolving Ocean Macroscale Turbulence), LocClima (Impact of LOCal conditions on Italian microCLIMAtes), CRAWL (Carbon Release in A Warming cLimate), and CliMOC (Climate Impacts of the Atlantic Meridional Overturning Circulation), with funding from EU, national programs, and commercial contracts. He is a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory, where he contributes expertise in climate data analysis and modeling. His collaborative work extends to multiple institutions through non-commercial agreements with the National Research Council and various international research consortia focused on climate system understanding.

Jacqueline McClearyمشاهده پروفایل

استادیار

• Astrophysics
• Cosmology
• Weak Gravitational Lensing
• +۴ مورد دیگر

Dr. Jacqueline McCleary is an Assistant Professor of Physics at Northeastern University's College of Science, specializing in observational cosmology with a focus on galaxy clusters and dark matter. She leads research using weak gravitational lensing to study cosmic structures, collaborating on projects like the COSMOS-Web (JWST), SuperBIT (balloon telescope), and LoVoCCS surveys. Her work leverages multi-wavelength data from space, stratospheric, and ground-based observatories. Education: M.S. in Astronomy (New Mexico State University), M.S. and Ph.D. in Physics (Brown University), Postdoctoral Fellow at NASA's Jet Propulsion Laboratory. She transitioned to Northeastern as an ADVANCE Future Faculty Fellow before becoming a tenure-track faculty member in 2022. Research Interests: Dark matter interactions, galaxy cluster dynamics, gravitational lensing techniques, and next-generation observational platforms. Her team develops advanced algorithms and instrumentation for high-resolution imaging. Recent Contributions: COSMOS-Web has enabled unprecedented observations of distant galaxies using JWST, while SuperBIT's stratospheric flights provide diffraction-limited data. Key publications focus on lensing surveys, data reduction techniques, and dark matter-halo relationships. Awards: Recognized as a Northeastern ADVANCE Future Faculty Fellow. Media Engagement: Regularly comments on space exploration, asteroid risks, and cosmic phenomena for public outlets.