جست‌وجوی استاد و پژوهشگر

Lakshmi N Sankarمشاهده پروفایل

استاد

• Aerodynamics
• Fluid Mechanics
• Computational Fluid Dynamics
• +۵ مورد دیگر

Lakshmi N Sankar serves as Regents Professor and Sikorsky Professor in the Guggenheim School of Aerospace Engineering at Georgia Institute of Technology, where he directs the Computational Fluid Dynamics Laboratory and teaches aerodynamics, helicopter theory, and wind energy courses. His research program spans unsteady viscous flow modeling for aircraft, helicopters, and wind turbines since joining the faculty in 1982 after industry experience at Lockheed Martin. Education: Ph.D., Aerospace Engineering, Georgia Institute of Technology, 1977 MSAE, Aerospace Engineering, Georgia Institute of Technology, 1975 B. Tech., Aeronautical Engineering, Indian Institute of Technology, Madras, India, 1973 Research Focus: Professor Sankar's work centers on Computational Fluid Dynamics for rotorcraft aerodynamics and wind energy systems , with significant contributions to icing phenomena and unsteady flow modeling . His recent publications reveal intensifying focus on adverse weather effects (rain/icing), eVTOL conversion challenges, and high-fidelity hybrid modeling techniques for rotorcraft performance prediction. Publication Trends: Analysis of his 2022-2025 publications shows dominant themes in rotorcraft icing (35%), weather impact studies (25%), and advanced CFD methodologies (20%), with growing interest in drone applications and mathematical aspects of fluid dynamics. His work consistently bridges theoretical mathematics with practical aerospace engineering challenges. Scientific Recognition: AIAA Fellow and AHS Technical Fellow NASA Group Achievement Award (2007) and Space Act Software Release Award (2003) Multiple Sigma Gamma Tau Teaching Awards (2005-2015) Dean George C. Griffin Faculty of the Year (2014-2015) Sikorsky Professorship (2018-Present) Mentorship and Collaboration: As recipient of Georgia Tech's Graduate Research Assistant Development Award, he has cultivated extensive student mentorship. His research integrates with the Vertical Lift Research Center of Excellence and Center for 21st Century Universities, securing major industry and NASA funding for rotorcraft innovation. Current projects include physics-based modeling of ice accretion and eVTOL retrofit feasibility studies. Research Infrastructure: The Computational Fluid Dynamics Laboratory serves as his primary research hub, complemented by collaborations through the Vertical Lift Research Center of Excellence where his team develops next-generation modeling tools for military and civilian rotorcraft applications under federal funding programs.

Hyuck Jin Parkمشاهده پروفایل

استاد

• Landslide Hazard Assessment
• Geotechnical Engineering
• Machine Learning Applications
• +۵ مورد دیگر

Hyuck Jin Park is a Full Professor in the Department of Energy Resources and Geosystems Engineering at Sejong University, South Korea, where he has been teaching and conducting research since 2003. With a Ph.D. in Engineering Geology from Purdue University, his expertise spans geotechnical engineering, landslide analysis, and geospatial technologies. Professor Park has built a distinguished career in landslide hazard assessment, combining traditional geotechnical approaches with modern machine learning techniques to improve prediction accuracy and risk management. His educational background includes: B.S. in Geology from Yonsei University (1990) M.S. in Geophysics from Yonsei University (1993) Ph.D. in Engineering Geology from Purdue University (2011) Professor Park's research focuses on the spatial and temporal probability of landslide occurrence, utilizing fuzzy logic, probabilistic analysis, GIS, Monte Carlo simulation, and machine learning for landslide hazard assessment. His work integrates physically based models with statistical approaches to better understand landslide mechanisms and improve prediction capabilities. He has made significant contributions to the development of methodologies that account for geological uncertainties in hazard assessment, with applications ranging from rock slope stability to rainfall-induced shallow landslides. His recent publications demonstrate a clear trend toward integrating explainable artificial intelligence with traditional geotechnical approaches for natural hazard assessment. Professor Park's work increasingly focuses on making machine learning models transparent and interpretable while maintaining high predictive accuracy. The research spans multiple hazard types including landslides, earthquakes, and floods, with a growing emphasis on climate change impacts and data-scarce environments. With an h-index of 28 and over 3,421 citations, Professor Park has established himself as a leading researcher in his field. His work has been published in high-impact journals including Engineering Geology, Landslides, and Catena, reflecting the significance and quality of his contributions to geotechnical engineering and natural hazard assessment. Professor Park has mentored numerous researchers through collaborative projects and has secured funding for his innovative work in landslide prediction and hazard assessment. His research has involved significant international collaboration, particularly with researchers from Malaysia, Australia, and Yemen, addressing landslide and flood risks in diverse geographical contexts. He leads research activities within the Department of Geoinformation Engineering at Sejong University and has contributed to the development of specialized tools like DEWS (Distance, Elevation, Watershed, and Slope unit) for landslide early warning systems.

Paul Withersمشاهده پروفایل

استاد

• Martian upper atmosphere
• Martian ionosphere
• Venus ionosphere
• +۵ مورد دیگر

Paul Withers is a Professor and Chair of the Department of Astronomy at Boston University. He leads research on planetary atmospheres and ionospheres, with a focus on Mars and Venus, and serves as Principal Investigator on multiple NASA-funded research projects. Education: B.A. in Physics, 1998, Queens' College, Cambridge University M.S. in Physics, 1998, Queens' College, Cambridge University M.A., 2001, Queens' College, Cambridge University Ph.D. in Planetary Science, 2003, University of Arizona Professor Withers' research focuses on the upper atmospheres and ionospheres of terrestrial planets, particularly Mars and Venus. His work involves analyzing spacecraft data and developing theoretical models to understand how solar flux, neutral atmospheres, magnetic fields, and ionospheres interact under unique planetary conditions. He has made significant contributions to understanding the response of the Martian ionosphere to solar flares, the structure of the Venus ionosphere, and meteoric plasma layers in planetary ionospheres. His research often involves multi-instrument campaigns and coordinated observations across different spacecraft missions including Mars Express, MAVEN, and Venus Express. Analysis of Professor Withers' recent publications reveals a strong emphasis on Martian ionospheric dynamics, particularly its response to solar activity and its variability under different conditions. His work frequently combines data from multiple missions to create comprehensive models of planetary upper atmospheres. He has developed important methods for analyzing radio occultation data and reconstructing atmospheric properties from entry, descent, and landing measurements. Major Funded Projects: "Characterizing the topside bulge in the ionosphere of Mars" (NASA Mars Data Analysis Program, 2014, $144K) "Integration of MAVEN neutral and plasma observations" (NASA MAVEN Participating Scientist Program, 2013, $284K) "Radio occultation studies at Mars" (NASA Early Career Fellowship Program, 2013, $99K) "EDL reconstruction for MSL" (NASA, JPL contract, 2012, $199K) "Meteoric plasma layers on Venus and Mars" (NASA Planetary Atmospheres Program, 2012, $232K) Professor Withers has been actively involved in mentoring students and collaborating with international researchers. He serves as a key member of the Mars Upper Atmosphere Network (MUAN) and has contributed to community white papers for planetary science decadal surveys. His work supports future Mars landers through atmospheric modeling and surface pressure prediction, with direct applications to mission planning and execution. He has presented his research at numerous international conferences including the American Geophysical Union meetings, Division for Planetary Sciences meetings, and European Planetary Science Congress. His work has important implications for understanding planetary climate evolution, space weather effects on technological systems, and the search for habitable environments beyond Earth.

Jaime Peraireمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Finite Element Methods
• Aerodynamics
• +۷ مورد دیگر

Jaime Peraire is the H.N. Slater Professor of Aeronautics and Astronautics at MIT, affiliated with the School of Engineering. He leads research in computational mechanics, aerodynamics, and numerical methods for partial differential equations, with key roles as former Department Head (2011-2018) and Director of the Aerospace Computational Design Lab (1993-2011). His expertise spans finite element methods, shock capturing algorithms, and high-order numerical techniques applied to hypersonic flows, space weather, and metamaterials. Education includes a Ph.D. from the University of Wales (1986) and engineering degrees from the University of Barcelona (1983, 1987). He holds prestigious awards like the T.J. Hughes Medal (2015) and the Ildefons Cerdá Medal (2015). His work bridges computational science and engineering, with contributions to discontinuous Galerkin methods, mesh adaptivity, and GPU-accelerated simulations. Research interests emphasize high-fidelity modeling of compressible flows, plasma dynamics, and terahertz spectroscopy. Notable projects include MIT’s space weather modeling initiative and metamaterial fabrication using atomic layer lithography. His labs collaborate across MIT’s Schwarzman College of Computing, IDSS, and CCSE to advance computational tools for aerospace and environmental systems. Awards: Over 10 major prizes, including NASA Exceptional Achievement (1997) and IACM Young Researchers Award (1998). Grants/Advising: Led NSF-funded space weather projects and advised numerous PhD students in computational engineering. Labs: Aerospace Computational Design Lab, MIT Schwarzman College of Computing collaborations.

Scott Englandمشاهده پروفایل

استاد

• Planetary Atmospheres
• Space Environment
• Atmospheric Tides
• +۳ مورد دیگر

Scott England is a Professor in the Department of Aerospace and Ocean Engineering at the College of Engineering, Virginia Polytechnic Institute and State University. He serves as the Project Scientist for NASA’s Ionospheric Connection Explorer (ICON), Co-Investigator for Global-scale Observations of the Limb and Disk (GOLD), and Participating Scientist for Mars Atmosphere and Volatile Evolution (MAVEN). Education PhD, University of Leicester (UK), 2005 MPhys First Class Honors, University of Leicester (UK), 2001 England’s research focuses on planetary atmosphere-space environment interactions, particularly gravity waves, atmospheric tides, and ionosphere-thermosphere coupling on Earth and Mars. His work integrates NASA mission data (ICON, GOLD, MAVEN) with numerical modeling to study thermal dynamics, wind systems, and solar flare impacts. Recent publications highlight his expertise in thermospheric gravity wave science, planetary wave-induced ionospheric variability, and Mars atmosphere studies using EMUS and IUVS instruments. Articles span topics like Seasonal variability of DE3/DE2 tides , Transient Martian hot oxygen corona , and Shock-induced plasma dynamics . Scientific Honors 2020 Dean's Award for Teaching Excellence 2016 RHG Exceptional Achievement for Mars Science As a professional leader, England served as Thermospheric Lead for the 2019 Planetary Mission Concept Studies Program and on the National Academy of Sciences Decadal Survey panel. He manages Virginia Tech’s participation in the Virginia Space Grant Consortium and has contributed to high-performance computing committees.

Rajesh Karkiمشاهده پروفایل

استاد

• Power Systems
• Renewable Energy Integration
• Grid Reliability
• +۳ مورد دیگر

Rajesh Karki is a Professor in the Department of Electrical and Computer Engineering at the University of Saskatchewan’s College of Engineering. He holds a B.E., M.Sc., and Ph.D. in related fields. His research focuses on power system reliability, renewable energy integration, and microgrid resilience, with particular emphasis on addressing challenges posed by extreme weather, cyber threats, and decarbonization targets. Dr. Karki’s work spans theoretical modeling, probabilistic analysis, and practical implementation strategies for smart grids, energy storage systems, and distributed generation. His educational background includes advanced degrees in electrical engineering, complemented by professional engineering licensure (P.Eng.). His research has explored diverse topics such as wind energy curtailment mitigation, energy storage optimization, and demand response mechanisms in developing economies like Nepal. He has authored numerous peer-reviewed publications on grid resilience, reliability economics, and cyber-physical system security. Key themes in his work include: (1) quantifying the reliability value of energy storage in active distribution systems, (2) modeling cyber-physical threats to microgrids, and (3) developing frameworks for extreme weather-resilient infrastructure. Despite the volume of his publications (over 50 articles), no specific awards or grants are explicitly listed in the provided materials. His research often intersects technical, economic, and policy dimensions of sustainable energy systems.

Che-Wei Changمشاهده پروفایل

استادیار

• Coastal Engineering
• Coastal Resilience
• Nature-based Solutions
• +۶ مورد دیگر

Che-Wei Chang is an Assistant Professor in the Department of Ocean Engineering at the University of Rhode Island (URI) , where he joined in August 2023. Prior to URI, he was an Assistant Professor at the Disaster Prevention Research Institute of Kyoto University in Japan. He earned his Ph.D. in Civil and Environmental Engineering from Cornell University in 2017, along with an M.S. in Civil Engineering from National Taiwan University (2008) and a B.S. in Soil and Water Conservation from National Chung Hsing University (2006). Ph.D., Civil and Environmental Engineering, Cornell University, 2017 M.S., Civil Engineering, National Taiwan University, 2008 B.S., Soil and Water Conservation, National Chung Hsing University, 2006 Dr. Chang specializes in coastal engineering , coastal resilience , and nature-based solutions for mitigating coastal hazards. His research focuses on water waves and nearshore hydrodynamics , particularly how mangroves and other natural features reduce wave impacts from tsunamis, storm surges, and rising sea levels. He integrates numerical modeling , laboratory flume experiments , and field observations to advance understanding of coastal morphodynamics under climate change. His recent work, including 2025 publications on SPH simulations and field studies , emphasizes mangrove resilience against breaking wave forces and critical wave conditions leading to mangrove failure. Earlier studies (2015–2022) explore Boussinesq modeling , wave-vegetation interactions , and coastal forest functional evaluation . These articles highlight his commitment to sustainable shoreline management and science-based coastal design. Dr. Chang received the Coastal Engineering Journal (CEJ) Citation Award 2024 for his impactful review paper and was appointed a Senior Fellow of the Coastal Institute (URI) in 2025 . He actively mentors graduate students like Felipe Espinoza and Ramin Safari , who investigate wave-mangrove dynamics and vegetation impacts on coastal systems . His lab at URI, the Chang Coastal Lab , collaborates on conferences (e.g., ICCE 2024) and NSF-funded projects like NHERI RAPID Facility workshops.

• Machine Learning
• Graph Neural Networks
• Time Series Analysis
• +۷ مورد دیگر

Filippo Maria Bianchi is an Associate Professor in the Department of Mathematics and Statistics at UiT The Arctic University of Norway, where he conducts research at the intersection of machine learning, dynamical systems, and complex networks. He is also a Senior Researcher at NORCE Norwegian Research Centre and actively contributes to the IEEE Task Force on Learning for Structured Data and the ELLIS Society. Department: Department of Mathematics and Statistics School: Faculty of Science and Technology University: UiT The Arctic University of Norway Adjunct Position: Senior Researcher, NORCE Education: Bachelor’s in Computer Engineering, Sapienza University of Rome Master’s in Artificial Intelligence & Robotics, Sapienza University of Rome (cum laude, 2012) PhD in Machine Learning, Sapienza University of Rome His research focuses on graph machine learning, time series analysis, reservoir computing, and probabilistic forecasting , with applications in energy analytics and remote sensing. He has led and contributed to numerous projects involving Arctic power grids, satellite-based environmental monitoring, and deep learning for sustainability. The recent publications reflect a strong trend in graph neural networks —particularly pooling mechanisms, spatiotemporal modeling, and explainability—alongside applications in energy forecasting, avalanche detection, and remote sensing . His work combines theoretical innovation with real-world impact, especially in Arctic and remote environments. Scientific Affiliations and Leadership: Vice-Chair, IEEE Task Force on Learning for Structured Data Member, ELLIS Society Co-founder, Northernmost Graph Machine Learning group Member, IEEE Task Force on Reservoir Computing Visiting Professor, Politecnico di Milano (2024–2025) He actively mentors students and collaborates on interdisciplinary research. He has led projects in power grid reliability, solar fault detection, and unsupervised change detection in satellite imagery . His work is supported by open-source implementations and reproducible research practices. Laboratories and Research Groups: Northernmost Graph Machine Learning group (co-founder) ARC Research Group, UiT Graph Machine Learning Group, Lugano

• Cloud Physics
• Ice Nucleation
• Aerosol-Cloud Interactions
• +۳ مورد دیگر

Paul Connolly is a Professor of Atmospheric Physics and Reader in the School of Earth and Environmental Sciences at The University of Manchester. He serves as the Department's Senior Academic Advisor since 2018. His roles include academic leadership, research, and teaching in atmospheric sciences. Connolly holds a BSc (Hons) in Pure and Applied Physics from UMIST (2001) and a PhD in Atmospheric Science from Manchester (2006). His research focuses on cloud physics, ice nucleation, and numerical modeling, including developing the University’s large cloud chamber facility in the Latham Laboratories. Research Interests: Ice nucleation mechanisms and secondary ice production Cloud-aerosol interactions and numerical modeling Unsupervised deep-learning applications in image classification Key Projects: Climate and Weather Impacts on Society (2022–present) RAI Centre for Robotics and Artificial Intelligence (co-investigator) Teaching: Courses include Environmental Modelling (EART22001) and Measuring and Predicting-2 (EART60071). He has over a decade of experience teaching mathematics, statistics, and atmospheric physics to undergraduate and postgraduate students. Impacts: His work contributed to UK responses during the 2010 volcanic ash crisis. Research collaborations span cloud dynamics, microphysics, and fieldwork in Australia, Switzerland, Germany, and New Mexico.

• Efficiency Analysis
• Productivity Measurement
• Agricultural Economics
• +۵ مورد دیگر

Christopher John O'Donnell is a distinguished Professor at the School of Economics, University of Queensland, Australia, where he holds a dual affiliation (50% each) with both the main School of Economics and the Centre for Efficiency and Productivity Analysis (CEPA). His research primarily focuses on efficiency and productivity analysis across various sectors including agriculture, fisheries, public services, and healthcare. As a leading scholar in his field, he has published extensively in top-tier economics and operations research journals and is recognized as being among the top 5% of authors globally according to multiple citation metrics. O'Donnell's research interests span several interconnected domains: efficiency analysis, productivity measurement, agricultural economics, econometrics, state-contingent production frontiers, and metafrontier analysis. His work often bridges theoretical methodology with practical applications, particularly in estimating efficiency and productivity changes under various constraints and uncertainties. He has developed innovative approaches for measuring productivity in public service providers, agricultural sectors, and healthcare institutions, with particular attention to how weather, climate change, and demand uncertainty affect performance metrics. His research output demonstrates consistent productivity, with publications spanning from the 1990s to the present, including significant contributions in the last five years. O'Donnell frequently collaborates with researchers internationally, particularly with scholars from Australia, Europe, and Asia, reflecting the global relevance of his work. His publications appear in leading journals such as the American Journal of Agricultural Economics, Journal of Productivity Analysis, European Journal of Operational Research, and Agricultural and Applied Economics journals. Ranked among top 5% authors by citation metrics (Number of Citations) Ranked among top 5% authors by citation metrics (Number of Citations, Discounted by Citation Age) Ranked among top 5% authors by citation metrics (Number of Citations, Weighted by Number of Authors) Ranked among top 5% authors by citation metrics (Number of Citations, Weighted by Number of Authors, Discounted by Citation Age) Ranked among top 5% authors by citation metrics (Euclidian citation score) O'Donnell has supervised numerous graduate students, as evidenced by his 'Record of graduates' noted in his RePEc profile. His research has been supported by various institutions, particularly focusing on agricultural productivity, public sector efficiency, and resource economics. He has contributed significantly to methodological developments in productivity measurement, including nonparametric approaches and metafrontier frameworks that allow for cross-technology comparisons. As a core member of the Centre for Efficiency and Productivity Analysis (CEPA) at the University of Queensland, O'Donnell contributes to one of the world's leading research centers in efficiency and productivity analysis. His work has practical applications for policymakers in agriculture, fisheries management, healthcare, and public service delivery, helping organizations measure and improve their performance in increasingly complex economic environments.

Daniel E. Hortonمشاهده پروفایل

دانشیار

• Climate Change
• Atmospheric Science
• Environmental Science
• +۶ مورد دیگر

Daniel E. Horton is an Associate Professor in the Department of Earth, Environmental & Planetary Sciences at Northwestern University's Weinberg College of Arts and Sciences, where he leads the Climate Change Research Group (CCRG). His interdisciplinary work bridges atmospheric science, environmental health, and geoscience through advanced modeling techniques. Education: Ph.D. in Geological Sciences from University of Michigan B.S. in Atmospheric Science from Texas A&M University B.S. in Physics from Tulane University Horton's research spans extreme weather events, near-term societal impacts of climate change, geologic climate evolution, and exoplanet habitability. His group integrates atmospheric, biospheric, cryospheric, hydrospheric, and lithospheric processes using numerical models, environmental observations, and machine learning. Recent work emphasizes environmental justice through neighborhood-scale air quality analysis and transportation electrification impacts. Analysis of his 10 most recent publications (2022-2023) reveals three dominant research thrusts: (1) urban air quality modeling with WRF-CMAQ systems focusing on racial disparities in pollution exposure, (2) transportation electrification impacts on public health and equity, particularly for heavy-duty vehicles, and (3) hydrological extremes including precipitation variability and post-wildfire debris flows. Machine learning applications are increasingly prominent across all research areas. Scientific Awards: NSF CAREER Award (2023) for research on air quality, public health, and equity implications of transportation electrification Horton secured a $600,000 NSF grant supporting both research and educational initiatives, including after-school sustainability programming for Chicago middle schools. His Climate Change Research Group actively recruits graduate students for projects at the intersection of climate science and societal impacts, with strong collaborations across environmental health, urban planning, and engineering disciplines. Current work emphasizes equity-centered climate solutions through fine-scale spatial analysis of pollution and health outcomes.

Johannes Dahlمشاهده پروفایل

دانشیار

• Atmospheric Science
• Meteorology
• Convective Storm Dynamics
• +۳ مورد دیگر

Dr. Johannes Dahl is an Associate Professor in the Department of Geosciences at Texas Tech University. His research focuses on the dynamics of convective storms, particularly supercells and tornado formation. He leads a research group using numerical simulations and mobile observational platforms like TTU Ka-band radars to study tornado vorticity origins and storm-environment interactions. Education: M.Sc. Atmospheric Science (Free University of Berlin, 2007); Ph.D. Atmospheric Science (Ludwig Maximilian University, Munich, 2010). Research Interests: Tornadogenesis mechanisms, storm-scale vorticity dynamics, and cloud-scale numerical modeling. His work addresses critical questions such as whether tornado rotation is generated internally or imported from the environment. The group employs idealized simulations, theoretical frameworks, and field observations to advance understanding of severe weather processes. Recent publications emphasize vortex dynamics, numerical model validation, and environmental influences on tornado formation. He teaches courses in atmospheric science fundamentals, synoptic/mesoscale dynamics, and geophysical fluid dynamics. Labs/Teams: Active participant in VORTEX-SE field campaigns and collaborates with Texas Tech’s radar teams. His group integrates observational data with high-resolution simulations to improve storm prediction models.

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

Univ.-Prof. Aiko Voigt is a Professor and Head of the Department of Meteorology and Geophysics at the University of Vienna. Her research focuses on climate dynamics, cloud physics, and atmospheric processes. She leads the Environment and Climate Research Hub and teaches advanced courses like 'Climate Modelling Lab' and 'Cloud Physics.' Her work explores cloud-radiative interactions, climate change impacts, and extreme weather dynamics. Recent studies analyze energy imbalances, high-cloud feedbacks, and tropical precipitation patterns. Voigt's contributions bridge climate modeling with observational data, emphasizing high-resolution simulations and interdisciplinary approaches. Teaching includes courses such as 'Climate System of the Earth,' 'Scientific Communication,' and 'Introduction to Computational Meteorology.' Her research spans from present-day climate to Snowball Earth scenarios, addressing both modern and paleoclimatic challenges. Publications highlight advancements in radiative transfer algorithms, cyclone dynamics under warming, and uncertainties in climate model predictions. Her work underscores the critical role of clouds in amplifying climate sensitivity and reshaping atmospheric circulation patterns.

Arthur Bousquetمشاهده پروفایل

دانشیار

• Applied Mathematics
• Numerical Analysis
• Computational Fluid Dynamics
• +۳ مورد دیگر

Arthur Bousquet is an Associate Professor of Mathematics at Lake Forest College, affiliated with the Math and Computer Science department. He holds a PhD in Applied Mathematics from Indiana University (Bloomington, IN) and a MS in Engineering in applied mathematics and scientific computing from SuP Galilee Engineering School (Paris, France). His research focuses on numerical methods for partial differential equations, including finite volume and finite element techniques, with applications to geophysical fluid dynamics, climate modeling, and biomedical problems like viral shell mechanics. Notable areas include shallow water equations, phase field modeling, and computational methods for atmospheric dynamics. Bousquet has published extensively on topics such as numerical weather prediction, electrokinetic equations, and virus nanoindentation modeling. His work often combines theoretical analysis with computational simulations to address complex systems in fluid dynamics and materials science. He has received the Rothrock Award for teaching excellence (2014) and held research fellowships including an NSF Graduate Fellowship (2009-2013). His teaching includes courses like Computational Mathematics, Multivariable Calculus, and Real Analysis.

• Climate Change Modelling
• Resilient Infrastructure
• Environmental Sustainability
• +۳ مورد دیگر

Mohd Ahmad Syed is a Senior Lecturer in Geotechnical Engineering at the University of Manchester's Department of Civil Engineering and Management. His research focuses on climate change impacts on geotechnical infrastructure, resilient and sustainable infrastructure design, and earthquake engineering. He holds a PhD from the Indian Institute of Technology Bombay and has industry experience with firms like Consulting Engineering Services (I) Pvt. Ltd and Dar Al-Handasah Consultants. Education: BTech (Hons) in Civil Engineering, Indian Institute of Technology Kanpur (2001) MTech in Geotechnical Engineering, Indian Institute of Technology Kanpur (2003) PhD in Seismic Analyses of Waterfront Structures, Indian Institute of Technology Bombay (2009) Research Interests: Climate change modelling for geotechnical infrastructure resilience Development of sustainable construction materials (e.g., bagasse ash) Seismic risk analysis for dams and tunnels in West Africa Artificial soil weathering techniques for laboratory testing Coupled numerical methods for embankment stability under climate scenarios Editorial Activities: Assistant Editor, International Journal of Geomechanics (ASCE) Assistant Editor, Indian Geotechnical Journal (Springer) Key Achievements: Developed first-of-its-kind displacement-based S-curve for seismic earth pressure analysis Co-developed methodologies for post-liquefaction pile behavior and blast-loaded tunnels Guided 10 PhD/MSc students in geotechnical resilience and sustainability topics