جستجوی استاد راهنمای دانشگاهی

Jay Famigliettiمشاهده پروفایل

استاد

• Hydrology
• Climate Change
• Remote Sensing
• +۳ مورد دیگر

Jay Famiglietti is a Global Futures Professor at Arizona State University’s School of Sustainability, serving as Director of Science for the Arizona Water Innovation Initiative. He holds affiliated roles in the School of Sustainable Engineering and the Built Environment and the Swette Center for Sustainable Food Systems. Previously, he was a Professor Emeritus and Executive Director of the Global Institute for Water Security at the University of Saskatchewan, where he held the Canada 150 Research Chair in Hydrology and Remote Sensing. His career includes leadership roles at NASA’s Jet Propulsion Laboratory and founding Waterplan, a water tech startup. Education: B.S. in Geology (Tufts University); M.S. in Hydrology (University of Arizona); M.A./Ph.D. in Civil Engineering (Princeton University); Postdoctoral research at Princeton and the National Center for Atmospheric Research. Research focuses on satellite-based tracking of global water availability, groundwater depletion via GRACE mission data, and integrating hydrology with climate models. Key interests include groundwater sustainability, the food-water nexus, corporate water stewardship, and water diplomacy. He has pioneered methods for detecting groundwater changes from space and improving hydrological predictions in IPCC models. Publications highlight advancements in GRACE applications, groundwater sustainability, and climate-water interactions. His work has been featured in major media outlets like 60 Minutes and Nature . Awards include the AGU’s Peter S. Eagleson Hydrologic Sciences Award and Fellowships from AGU and the Geological Society of America. He advises governments and global leaders on water policy, hosts the podcast What About Water? , and collaborates internationally through roles like Chair of the Bolin Centre’s External Science Advisory Group. His research group includes postdocs, PhD candidates, and scientists addressing water security challenges globally.

Laura Balzanoمشاهده پروفایل

دانشیار

• Machine Learning
• Optimization
• Signal Processing
• +۷ مورد دیگر

Laura Balzano is an Associate Professor of Electrical Engineering and Computer Science at the University of Michigan, with a courtesy appointment in the Department of Statistics within the College of Literature, Science, and the Arts. Her research focuses on optimization, machine learning, and signal processing, particularly in high-dimensional data analysis, subspace learning, and low-rank structures. She holds affiliations with the Department of Statistics and is located at 323 West Hall, Ann Arbor, MI. Contact information includes girasole@umich.edu . Her work bridges theoretical foundations and practical applications, addressing challenges in heterogeneous data, online learning, and robust algorithms. Key research areas include subspace clustering, tensor decomposition, and model compression for deep learning systems. Recent contributions explore dynamic networks, control theory integration, and energy-efficient algorithms for large-scale models. Laura Balzano's publications span topics like PCA variants for noisy data, optimization on Riemannian manifolds, and neural collapse analysis. Her methods emphasize scalable solutions for real-time applications, such as energy disaggregation and medical imaging. While no explicit awards are listed, her extensive publication record reflects recognition in her field. Advising and grant details are not provided in the available text.

Yang Chenمشاهده پروفایل

استادیار

• Statistical Methodology
• Computational Algorithms
• Bayesian Modeling
• +۷ مورد دیگر

Yang Chen is an Assistant Professor of Statistics and Research Assistant Professor at the Michigan Institute for Data Science (MIDAS), University of Michigan. Her research focuses on statistical methodology and computational algorithms for scientific applications, including Bayesian modeling, hidden Markov models, and applications in astronomy, space science, and epidemiology. She holds a Ph.D. in Statistics from Harvard University and a B.Sc. in Mathematics from the University of Science and Technology of China. Education: Ph.D. in Statistics, Harvard University, 2017 B.Sc. in Mathematics, University of Science and Technology of China, 2011 Research Interests: Her work emphasizes computational algorithms for statistical inference, with applications in astronomy (e.g., solar flare prediction, instrument calibration) and epidemiology. Key areas include spatial-temporal data analysis, uncertainty quantification, and machine learning for large-scale imaging data. Grants & Funding: Principal Investigator/Co-Investigator on multiple NSF, NASA, and industry grants totaling over $13M, including space weather modeling, solar physics, and data science initiatives. Teaching: Teaches advanced courses in Bayesian data analysis, statistical modeling, and computational methods at the University of Michigan. Professional Activities: Associate Editor for The American Statistician , Statistical Science , and Journal of the American Statistical Association . Active in organizing conferences and seminars on astrostatistics, machine learning, and space weather.

Gongjun Xuمشاهده پروفایل

دانشیار

• Latent Variable Models
• Psychometrics
• Statistical Learning
• +۶ مورد دیگر

Gongjun Xu is an Associate Professor of Statistics and courtesy Associate Professor of Psychology at the University of Michigan. He leads the Master's Program in Applied Statistics and holds positions in the Department of Statistics within the College of Literature, Science, and the Arts (LSA). His research focuses on latent variable models, psychometrics, statistical learning, and high-dimensional statistics. Xu completed his Ph.D. in Statistics at Columbia University and B.S. at the University of Science and Technology of China (USTC). His research interests include advanced statistical methodologies for educational and psychological measurement, such as cognitive diagnosis models, item response theory, and network data analysis. He has contributed to high-dimensional inference, survival analysis, and machine learning applications in healthcare. Xu serves as Co-Editor-in-Chief of the Journal of Educational and Behavioral Statistics and holds editorial roles in multiple top-tier journals. Xu has been recognized with prestigious awards including the AERA Research Methodology Award (2025), ICSA President’s Citation (2024), and COPSS Emerging Leader Award (2023). His team advises numerous graduate and undergraduate students, many of whom pursue academic and industry roles in statistics, data science, and education. Key collaborations include work on educational testing, health analytics, and AI-driven scientific methods via the Schmidt AI in Science Fellowship. He oversees a vibrant research group with active projects in latent variable modeling, differential item functioning detection, and scalable Bayesian methods for large-scale assessments. His lab emphasizes interdisciplinary applications spanning education, healthcare, and social sciences.

Jim Daiمشاهده پروفایل

استاد

• Applied Probability
• Operations Research
• Health Systems
• +۳ مورد دیگر

Jim Dai is the Leon C. Welch Professor of Engineering at Cornell University's School of Operations Research and Information Engineering (ORIE). He previously held the Chandler Family Chair at Georgia Institute of Technology (1990–2012) and serves as a Special Term Professor at Tsinghua University and a Visiting Professor at National University of Singapore. His research focuses on applied probability models for service systems, healthcare operations, and transportation networks. He holds a B.S. and M.S. from Nanjing University and a Ph.D. in Mathematics from Stanford University. Research interests include stochastic models for resource allocation in processing networks, healthcare systems, and ridesharing networks. His work emphasizes fluid and diffusion models, Stein’s method, and reinforcement learning. Awards include the Erlang Prize (1998), ACM SIGMETRICS Achievement Award (2018), and the John von Neumann Theory Prize (2024). He is Editor-in-Chief of Mathematics of Operations Research and a Fellow of INFORMS and the Institute of Mathematical Statistics. Teaching spans Markov chains, stochastic processes (both undergraduate and graduate levels), and optimization. Service roles include editorial positions at journals like Stochastic Systems and advisory roles at Singapore University of Technology and Design.

Tigran Ayrapetyanمشاهده پروفایل

دانشیار مدعو

• Structural Engineering
• Earthquake Engineering
• Architectural Design
• +۷ مورد دیگر

Tigran Ayrapetyan is an Adjunct Associate Professor at the USC School of Architecture since 2006, where he teaches undergraduate and graduate courses in Building Science and advanced structural systems. He holds an M.S. and B.S. in Civil/Structural Engineering from UCLA. With over three decades of experience, he specializes in structural engineering, earthquake engineering, and architectural design of complex structures, including long-span aluminum geodesic domes, space frames, and seismic-resistant designs. His work spans national and international projects in commercial, industrial, and residential sectors. He previously served as a Structural Consultant and Project Manager at Temcor (1994–1998), addressing structural design and installation of large-scale projects like water reservoirs and petroleum tanks. At EQE International (1994), he studied seismic performance of steel structures post the Northridge Earthquake, contributing to repair methodologies for failed moment connections. Earlier roles include co-ownership of A & A Design (1991–1993) and consulting for Prof. Goetz Schierle on an NSF-funded grant for lateral design graphs. Education: M.S., Civil / Structural / Earthquake Engineering, UCLA B.S., Civil / Structural Engineering, UCLA His research interests focus on innovative structural materials (e.g., aluminum), computational methods in finite element analysis, and integrating building systems for sustainable and efficient designs. Notable projects include the Sands Expo & Convention Center in Las Vegas, Shanghai International Gymnastics Center, and geodesic domes up to 415 ft in diameter. He has also provided expert seminars on seismic design and long-span structures since 1994. Awards: 2012: Certificate of Recognition from California State Assembly for community and educational service 2012: Recognition Plaque from The Knights of Vartan for educational leadership In advising and grants, he collaborated on an NSF-funded research project (LDG: Lateral Design Graphs) with Prof. Schierle (1990–1991). His consultancy firm, Tigran Ayrapetyan, M.S., P.E., Structural Consulting (since 1998), has worked with high-profile clients like Children’s Hospital LA, McCarran International Airport, and JPL. He also contributed to post-earthquake assessments and repairs, notably at the Borax facility in Valencia, CA. Though not explicitly mentioned, his professional affiliations and teaching roles suggest involvement in academic teams focused on building science and structural innovation. His career bridges academic instruction and practical engineering, emphasizing real-world applications of advanced structural concepts.

Oleksiy Klymenkoمشاهده پروفایل

مدرس ارشد

• Model-Based Process Design
• Mathematical Modelling in Natural Sciences
• Uncertainty Quantification
• +۳ مورد دیگر

Dr. Oleksiy Klymenko is a Senior Lecturer in Chemical Process Engineering at the University of Surrey, affiliated with the School of Chemistry and Chemical Engineering and the Institute for Sustainability. He holds a DPhil and specializes in model-based process design, mathematical modeling, and uncertainty quantification. Research Interests: Model-based design and optimization of process systems Mathematical modeling in natural and life sciences Uncertainty quantification, particularly global sensitivity analysis Teaching: Module leader for three M-level modules: ENGM071 Process and Energy Integration (MSc) ENGM214 Process Modelling and Simulation (MSc/Year 4 MEng) ENGM256 Technology, Business and Research Seminars (MSc/Year 4 MEng) Contributes to a Year 2 BEng/MEng module. Research Trends: Publications focus on antimicrobial technologies, energy systems optimization, and electrochemical simulations. Recent work includes 3D modeling of microbial dynamics, sustainable energy design, and the development of tools like KISSA software for electrochemical analysis. Advising & Grants: No explicit student advisees or grant details provided in texts. Research collaborations likely underpin his work in interdisciplinary areas like food safety and energy systems. Labs/Teams: Part of the Institute for Sustainability at Surrey, collaborating on projects aligning with sustainable development goals, particularly in energy and food systems.

Lynn Meskellمشاهده پروفایل

استاد

• Archaeological Theory
• UNESCO World Heritage
• Global Heritage Preservation
• +۷ مورد دیگر

Lynn Meskell is the PIK Professor of Anthropology at the University of Pennsylvania's School of Arts and Sciences, with cross-appointments as Professor in the Weitzman School of Design's Historic Preservation Department and Middle East and Asia Sections Curator at the Penn Museum. She also serves as A.D. White Professor-at-Large at Cornell University (2019–2025). Her academic career includes roles at Stanford University and honors from institutions worldwide, including honorary doctorates from Sapienza University of Rome and the University of Bergen. Education: Ph.D. in Archaeology (University of Cambridge, 1997), B.A. with First Class Honours and University Medal (University of Sydney, 1994). Meskell's research focuses on UNESCO World Heritage governance, postcolonial archaeology, and heritage ethics. Her work critiques international heritage frameworks through case studies in conflict zones (Syria/Iraq), India, South Africa, and Egypt. She examines how heritage policies intersect with sovereignty, diplomacy, and geopolitics, particularly in post-conflict reconstruction. Her articles analyze global heritage dynamics, including public opinion on reconstruction, Cold War cultural diplomacy, and UNESCO's role in mediating conflicts. Key themes include heritage as a site of political contestation, the ethics of international intervention, and the interplay between cultural preservation and economic development. Recipient of grants from the Mellon Foundation, NSF, and Australian Research Council Editor of the Journal of Social Archaeology Leader of large-scale surveys on heritage perception in Iraq/Syria and India Meskell's work bridges archaeology, anthropology, and policy, emphasizing participatory heritage practices and the decolonization of global cultural frameworks.

William Hornsbyمشاهده پروفایل

پژوهشگر ارشد

• Plasma Transport Theory
• Plasma Turbulence Theory
• Kinetic Simulations
• +۵ مورد دیگر

William Hornsby is a Postdoctoral Research Fellow at the University of Warwick , affiliated with the Centre for Fusion, Space & Astrophysics and the Department of Physics . His research focuses on plasma transport and turbulence theory, kinetic simulations, and numerical methods for plasma physics problems. Education: PhD in Plasma Physics, Imperial College London Research Highlights: He develops the Gyro-Kinetic code GKW to simulate plasma turbulence and fusion stability, leveraging supercomputing resources. His work includes refining numerical methods for differential equations and studying magnetic island effects on plasma behavior. He also contributed to a Vlasov-Fokker-Planck code analyzing cross-field plasma transport. Collaborations & Tools: Uses the Francesca supercomputer and collaborates on visualizing 3D plasma data. Masters students under his guidance created video tools for GKW data visualization. Labs/Teams: Part of the GKW subgroup, focused on advancing gyrokinetic simulations and plasma stability research.

Martijn Smitمشاهده پروفایل

استادیار

• Human Geography
• Labor Market
• Economic Development
• +۹ مورد دیگر

Dr. Martijn Smit is an Assistant Professor in the Department of Economic Geography at Utrecht University, within the Faculty of Geosciences. His research focuses on teleworking, regional development, labor markets, agglomeration economies, innovation diffusion, peripheral regions, and EU regional policy. He also explores urban development, big data, and railway infrastructure, alongside historical interests in classical music globalization and Roman studies. Education: M.Sc. in Human Geography (cum laude) and M.A. in Classics from the University of Groningen, with additional training at the Dutch Institute in Rome and Università degli Studi di Verona. Professional Experience: Since 2013, he has held an 80% position at Utrecht University. Prior roles include postdoc research at Vrije Universiteit Amsterdam (2010–2016) and freelance database design for the North Sea Interreg Program (2005–2012). Teaching: Teaches courses on philosophy of science, regional policy, and spatial econometrics, coordinating master's theses and internships in economic geography. His research interests emphasize the geography of remote work, agglomeration benefits, and EU policy impacts. Key areas include coworking spaces, eco-innovation in fashion, and the dynamics of urban-rural divides. He has contributed to high-profile projects like the EU's SPARD and IC-EU initiatives, analyzing transport infrastructure and agricultural subsidies. Awards: Won first prize in the Regional Studies Association Poster Competition (2013). His work has been featured in media outlets like De Stentor and Reporter Radio , discussing topics like post-pandemic office trends and Dutch regional policy. Service: Serves as book review editor for Papers in Regional Science , editorial board member of Tijdschrift voor Economische en Sociale Geografie , and treasurer of the Regional Science Association Nederland.

• Smart Cities
• Urban Planning
• Feminist Geography
• +۴ مورد دیگر

Dr. Krisztina Varró is an Assistant Professor in Spatial Planning at Utrecht University’s Faculty of Geosciences. She holds an MSc from the University of Pécs (Hungary), a postgraduate degree in urban planning from the University of Tours, and a PhD (cum laude) from Radboud University Nijmegen. Her research focuses on critical urban political economy, smart city governance, feminist geography, and gender-sensitive urban planning. She has published widely on urban development policies in Europe, particularly in post-socialist contexts like Hungary, and recently shifted toward feminist spatial analysis. Her current project, 'Her City, Her Story,' examines Dutch feminist geography’s historical contributions to urban planning and education. She teaches courses such as Introduction to Human Geography and Planning for Open Cities . Her work addresses smart city discourses, data-driven urban practices, and inclusive urban space design. She is involved in interdisciplinary research groups like Governing the Digital Society and Open Cities at Utrecht University. Varró’s research bridges theory and practice, critiquing authoritarian urban policies and advocating gender-inclusive planning. Her recent articles include analyses of Hungary’s smart city articulations, feminist pedagogy in geography curricula, and multiscalar smart village perspectives. She has collaborated on projects funded by Utrecht University, exploring topics like transnational cross-border governance and relational sense of place through participatory methods.

Sheng Daiمشاهده پروفایل

استاد مدعو

• Geomechanics
• Gas Hydrate Systems
• Granular Materials Engineering
• +۳ مورد دیگر

Dr. Sheng Dai holds a courtesy appointment as an Adjunct Professor in the School of Earth & Atmospheric Sciences at Georgia Institute of Technology, part of the College of Sciences. His research focuses on geomechanics, gas hydrate systems, and bio-inspired engineering solutions. He collaborates across disciplines to address challenges in environmental fluid mechanics, granular materials, and energy systems. His work integrates computational modeling, experimental analysis, and machine learning. Key research areas include the mechanical and hydraulic properties of hydrate-bearing sediments, granular flow dynamics of biomass and municipal waste, and the application of bacterial proteins to stabilize clathrate structures. He has contributed to advanced modeling frameworks for subsurface energy systems and bio-inspired solutions for rock drilling. Dr. Dai's recent studies analyze the influence of particle size distribution, temperature effects on shale properties, and pore-scale observations of sediment behavior. His work frequently intersects with engineering applications such as hopper design optimization, energy screw piles, and geothermal energy recovery systems. He has co-authored over 50 peer-reviewed articles, with notable contributions in Geomechanics for Energy and the Environment and Environmental Science & Technology . His research has been supported by international collaborations and industry partnerships.

• Probability Theory
• Stochastic Analysis
• Machine Learning
• +۵ مورد دیگر

Xiong Wang is a J.J. Sylvester Assistant Professor in the Department of Mathematics at Johns Hopkins University (non-tenure track). His research focuses on probability theory, stochastic analysis, and their applications to machine learning and complex systems. He holds a Ph.D. from the University of Alberta (2022), where he received the Faculty of Science Dissertation Award. Education: Ph.D. in Mathematics, University of Alberta (2022) Advisor: Professor Yaozhong Hu Research Interests: Probability Theory & Stochastic Processes Machine Learning Algorithms Partial Differential Equations (PDEs) Interacting Particle Systems Inverse Problems in Stochastic Dynamics Mathematical Foundations of Data Science Teaching: Instructor for advanced courses at Johns Hopkins, including Stochastic Differential Equations, Partial Differential Equations, and Real Analysis Prior teaching roles at University of Alberta (Calculus, Linear Algebra) Recent Activities: Speaker at over 30 international conferences/seminars since 2021 Active in SIAM, CMS, and ICERM events Collaborations with institutions globally (e.g., Peking University, Brown University)

Santiago Badiaمشاهده پروفایل

استاد

• Computational Science and Engineering
• Numerical Analysis
• Numerical Linear Algebra
• +۸ مورد دیگر

Santiago Badia is a Professor of Computational Mathematics at Monash University's School of Mathematics since 2019. Previously, he held roles at UPC (Universitat Politècnica de Catalunya) as Professor of Computational Science and Engineering (2009–2019) and was an adjunct researcher at CIMNE (Barcelona), leading the Large Scale Scientific Computing Department. He earned his PhD in 2006 from UPC, with prior work at Politecnico di Milano (2006) and Sandia National Labs (2007–2008). His research focuses on numerical approximation of PDEs using finite element methods, with applications in fluid/solid mechanics, electromagnetics, and multiphysics problems. He leads high-performance computing projects like FEMPAR (scalable PDE solvers) and Gridap (Julia-based PDE framework). His work includes perfect weak scalability on supercomputers and solving PDEs with up to 60 billion unknowns. Research interests span computational science, numerical analysis, parallel computing, and numerical linear algebra. Projects address challenges in fusion energy, additive manufacturing, and nuclear waste repositories. He actively supervises PhD students through funded projects, emphasizing computational modeling and simulation. Collaborations include international teams in geophysical fluid dynamics and stochastic inverse problems. His software frameworks (FEMPAR, Gridap) are widely used for industrial and academic research, emphasizing scalability and usability.

Gregory Markowskyمشاهده پروفایل

مدرس ارشد

• Stochastic processes
• Complex analysis
• Graph theory

Gregory Markowsky serves as a Senior Lecturer in the School of Mathematics at Monash University, maintaining an active research profile with continuous publication output through 2025. His academic appointment shows no indication of part-time status, emeritus designation, or former staff classification. His research centers on three interconnected domains: Stochastic processes, particularly planar Brownian motion and random walk theory Complex analysis with applications to probabilistic models Graph theory focusing on algebraic and combinatorial structures These areas converge in his investigation of probabilistic phenomena with geometric interpretations. Recent publication trends reveal sustained productivity with 61 research outputs cataloged, including 4 articles in 2025 alone. His work demonstrates consistent methodological focus on stochastic analysis and combinatorial structures, with increasing cross-disciplinary applications in forensic science and econometrics as evidenced by 2024-2025 publications. Markowsky has secured three significant research projects funded by the Australian Research Council, including: "Planar Brownian motion and complex analysis" (2014-2017) as Primary Chief Investigator "Finite Markov chains in statistical mechanics and combinatorics" (2014-2017) "AMSI Industry Internship: Melbourne Storm" (2013) His ORCID profile (0000-0003-1656-337X) documents extensive scholarly activity with international collaborations. Professional engagement includes contributions toward UN Sustainable Development Goals through mathematical applications, though specific goal alignments aren't detailed in available materials. His email contact Greg.Markowsky@monash.edu remains active with current research dissemination.