جستجوی استاد راهنمای دانشگاهی

Margaret P. Chapmanمشاهده پروفایل

استادیار

• Risk-Averse Control Theory
• Stochastic Control Theory
• Safety Analysis for Dynamical Systems
• +۴ مورد دیگر

Margaret P. Chapman is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Toronto's Faculty of Applied Science and Engineering. She leads the DATA Lab (Decision Analysis for Trustworthy Autonomy), focusing on risk-averse and stochastic control theory with applications to environmental and human health. Education: B.S. and M.S. in Mechanical Engineering from Stanford University (2012, 2014), Ph.D. in Electrical Engineering and Computer Sciences from UC Berkeley (2020, advised by Claire Tomlin) Her research bridges robust and stochastic optimal control via risk measure theory, emphasizing safety-critical applications in healthcare and sustainable cities. Key challenges include scalable risk-sensitive control methods, integrating physics-based and data-driven models for safety analysis, and promoting technologies that enhance planetary and human well-being. Recent publications focus on risk-averse autonomous systems, CVaR-based safety analysis, and multi-time-scale modeling for cancer treatment. She has advised students in both graduate and undergraduate research roles, including NSERC awardees and thesis participants. Awards: US National Science Foundation Graduate Research Fellowship, Berkeley Fellowship, Terman Engineering Scholastic Award, Leon O. Chua Award She teaches courses like ECE 557 (Linear Control Theory) and ECE 1643 (Risk-Averse Control with Learning). Her invited talks span institutions such as MIT, Princeton, and Georgia Tech, highlighting risk-sensitive analysis and control for trustworthy autonomy.

Olivier David Zerbibمشاهده پروفایل

استادیار

• Sustainable Finance
• Environmental Finance
• Asset Pricing
• +۲ مورد دیگر

Olivier David Zerbib is an Assistant Professor of Sustainable Finance at CREST, ENSAE, Institut Polytechnique de Paris, and serves as an Associate Editor for the Review of Finance. His research bridges financial theory with environmental sustainability, focusing on market mechanisms for ecological challenges. His primary research areas include sustainable finance, environmental finance, and asset pricing, with specific expertise in green bonds, biodiversity valuation, and climate impact investing. He investigates how pro-environmental preferences influence pricing mechanisms, develops sustainable asset pricing models, and examines shareholder engagement strategies to curb greenwashing through quantitative methodologies. Analysis of his publications reveals a cohesive trajectory toward integrating environmental metrics into core financial frameworks, with significant contributions spanning green bond markets, sustainable CAPM development, and biodiversity economics. His work demonstrates methodological rigor through score-driven conditional betas and empirical validation across global markets. Dr. Zerbib's scientific recognition includes: #1 most cited article in the Journal of Banking and Finance over 3 and 5 years (2019) SUERF/UniCredit Research Prize (2018) Multiple Best Paper Awards at international finance conferences (2017-2020) European Investment Forum Research Prize Finalist (2021) He co-organizes the CMAP-CREST Quantitative Sustainable Economics and Finance seminar series with Patricia Crifo, Emmanuel Gobet, Peter Tankov, and Gauthier Vermandel, fostering collaboration between Ecole Polytechnique and ENSAE on quantitative approaches to sustainability challenges. His presentation record spans elite institutions including LSE, Yale, and the European Commission Joint Research Center.

Nicole M. Gaspariniمشاهده پروفایل

دانشیار

• Fluvial Geomorphology
• Tectonic Geomorphology
• Landscape Evolution
• +۲ مورد دیگر

Nicole M. Gasparini is an Associate Professor in Tulane University's Department of Earth and Environmental Sciences, School of Science & Engineering. She holds a Ph.D. from MIT (2003) and researches fluvial/tectonic geomorphology, landscape evolution modeling, and climate-erosion interactions using tools like Landlab. Her work investigates sediment transport, river network evolution, and human impacts on landscapes. Research integrates field data with numerical models to quantify erosion processes across diverse environments. Publications demonstrate expertise in geomorphic model development, particularly through contributions to the Landlab toolkit. Recent articles focus on climatic controls on erosion, fault geomorphology, and uncertainty quantification in earth-surface models. Awards: Marguerite T. Williams Award for contributions to geosciences and advocacy against harassment in STEM Leads collaborative projects on landscape response to climate change and mentors students/postdocs in geomorphology and computational modeling.

Huiyan Sangمشاهده پروفایل

استاد

• Spatial Statistics
• Bayesian Nonparametrics
• Machine Learning
• +۹ مورد دیگر

Huiyan Sang is a Professor and Director of the Undergraduate Program in the Department of Statistics at Texas A&M University (College of Arts & Sciences). She earned her Ph.D. in Statistics from Duke University and a B.Sc. in Mathematics and Applied Mathematics from Peking University. Her research focuses on spatial statistics, Bayesian nonparametric methods, machine learning, computational statistics, and applications in environmental sciences, geosciences, urban planning, and biomedical research. Her interdisciplinary work integrates statistical methodologies with real-world challenges, such as analyzing extreme environmental events, optimizing urban infrastructure, and modeling complex systems like human mobility during pandemics. She has contributed to advancing spatio-temporal modeling, Gaussian processes, and Bayesian hierarchical frameworks for large datasets. Recent publications highlight innovations in nonparametric regression, spatial functional data analysis, and stochastic frontier analysis, often leveraging computational efficiency and scalability. Her work addresses critical societal issues, including the impact of community design on public health and environmental monitoring through remote-sensing data. No scientific awards are explicitly listed in the provided texts. She advises no students or grants in the current dataset but collaborates widely on interdisciplinary projects. Her research lab focuses on developing cutting-edge statistical tools with applications in engineering, public health, and environmental science.

Gary Froylandمشاهده پروفایل

استاد

• Dynamical Systems
• Machine Learning
• Optimisation
• +۱۲ مورد دیگر

Scientia Professor Gary Froyland is a Professor at the University of New South Wales (UNSW), affiliated with the School of Mathematics & Statistics. He leads the ARC Laureate Centre for Dynamical Systems and Data and holds an Einstein Visiting Fellowship from the Einstein Foundation Berlin. His academic credentials include a BSc (Hons 1, Medal) in Pure and Applied Mathematics from the University of Queensland and a PhD in Mathematics from the University of Western Australia. Professor Froyland's research spans two primary domains: dynamical systems and optimization. In dynamical systems, he investigates the interplay of probability and geometry in nonlinear and chaotic systems, employing tools from ergodic theory, functional analysis, and differential geometry. His work extends to applications in oceanography, atmospheric science, and granular flows. In optimization, he focuses on decision-making in complex systems with uncertain information, developing novel approaches in mathematical programming that have been applied to mining, logistics, and medical treatment planning. His recent publications demonstrate a strong focus on coherent structures in dynamical systems, linear response theory, and applications to geophysical phenomena. The research shows increasing interdisciplinary collaboration, particularly with climate scientists and data analysts, reflecting a trend toward applying advanced mathematical techniques to real-world problems in environmental science and engineering. J.D. Crawford Prize (2025) Elected Member of the Academy of Europe / Academia Europaea (2024) ARC Laureate Fellow (2024-2029) Fellow of the Society for Industrial and Applied Mathematics (SIAM) (2021) Fellow of the Australian Academy of Science (2020) Vice-Chancellor's Award for Teaching Excellence - Postgraduate Research Supervision (2015) Professor Froyland actively supervises PhD and honors students, with current advisees including Kevin Felipe Kühl Oliveira, Nicholas Peters, and Kathrin Völkner. His research is supported by multiple grants, including an ARC Laureate Fellowship (2024-2029) for "Breakthrough mathematics for dynamical systems and data," an Einstein Visiting Fellowship (2022-2026), and several ARC Discovery Projects. His work has practical applications in climate science, mining optimization, and medical treatment planning, particularly in radiotherapy. He leads the ARC Laureate Centre for Dynamical Systems and Data, which brings together researchers to develop new mathematical approaches for analyzing complex dynamical systems. The center focuses on creating methods to identify coherent structures in spatiotemporal data, with applications spanning environmental science, social science, health science, and engineering.

Ruchi Choudharyمشاهده پروفایل

استاد

• Urban Energy Systems
• Building Energy Modeling
• Sustainable Cities
• +۷ مورد دیگر

Professor Ruchi Choudhary is a Professor in Architectural Engineering at the University of Cambridge, Department of Engineering, within the School of Technology. She leads the Energy Efficient Cities initiative (EECi), a cross-disciplinary research project focused on strengthening the UK's capacity to address energy demand reduction and environmental impact in cities through research in building and transport technologies, district power systems, and urban planning. Her research interests span urban energy systems, building energy modeling, sustainable cities, geothermal energy systems, and data-driven energy modeling . She has pioneered work in digital twins for energy systems, urban subsurface thermal modeling, and building-integrated agriculture. Her research group develops numerical tools to improve energy efficiency of cities, with particular focus on modeling energy consumption of large building sets at multiple time and spatial resolutions. Analysis of her recent publications reveals a strong trend toward integrating machine learning with physics-based modeling for energy systems, with increasing emphasis on uncertainty quantification, digital twins, and value of information analysis for decision-making. Her work bridges the gap between theoretical modeling and practical urban implementation, with significant focus on city-scale geothermal potential, underground climate change impacts, and energy equity considerations. Professor Choudhary has supervised numerous PhD students who have gone on to prominent positions at institutions including UCL, University of Cambridge, BEIS, Arup, and various international universities. Her research group includes faculty members, research associates, graduate students, and international collaborators from institutions worldwide. Her current research focuses on two parallel investigations: one on using multi-scale multidisciplinary models to address energy use questions in the built environment, and second, on quantifying uncertainties in model outcomes. Current projects include integration of food production in urban environments, analysis of underground transport systems as energy sources, large-scale integration of ground source heat pumps, and distributed energy networks.

• Computational Imaging
• Artificial Intelligence
• Inverse Problems
• +۷ مورد دیگر

Aviad Levis is an Assistant Professor at the University of Toronto's Department of Computer Science, starting July 2024. He is affiliated with the Dunlap Astronomical Data Science and Technology Group (DADDAA) and collaborates with the Toronto Computational Imaging Group alongside Kyros Kutulakos and David Lindell. Previously, he was a postdoctoral researcher at Caltech's Computing + Mathematical Sciences department under Katherine Bouman, working with the Event Horizon Telescope (EHT) collaboration. PhD in Electrical Engineering from the Technion (supervised by Yoav Schechner) Research focuses on computational imaging tools at the intersection of AI and physics Develops algorithms for 3D tomography in both cloud physics and black hole imaging Recipient of ERC Synergy grant for CloudCT space mission His research spans two major domains: Computational Climate Imaging through cloud tomography to improve climate models, and Black Hole Imaging with the EHT collaboration. He pioneered methodologies for 3D cloud structure recovery using scattered sunlight and contributes to dynamic 3D reconstructions of black hole environments. Current interests include non-linear inverse problems, equation discovery from data, and ML-accelerated scientific simulations. Recent publications highlight advancements in atmospheric tomography and black hole emission modeling. His work on CloudCT involves coordinated nano-satellites for 3D cloud imaging, while EHT contributions include first images of Sagittarius A* (2022) and ongoing development of algorithms for 3D structure recovery. The ERC Synergy grant underscores his impact on climate imaging technology. Personal Website Work Email

Ronnie Sircarمشاهده پروفایل

استاد

• Financial mathematics
• Stochastic models
• Market volatility
• +۵ مورد دیگر

Ronnie Sircar is the Eugene Higgins Professor of Operations Research and Financial Engineering at Princeton University , where he contributes to the Department of Operations Research and Financial Engineering (ORFE). His work spans financial mathematics, stochastic modeling, and applied probability, with a focus on market volatility, optimal investment strategies, and dynamic game theory. Email: sircar@princeton.edu Office: Sherrerd Hall, Room 208, Princeton, NJ 08544 His research interests include: Stochastic Volatility: Asymptotic analysis, calibration, and impact on option pricing and portfolio optimization. Mean Field Games: Applications to cryptocurrency mining, energy markets, and interbank network formation. Portfolio Theory: Forward performance processes, drawdown constraints, and risk-averse strategies. Credit Risk: Multi-name credit derivatives, CDO valuation, and risk measures. Energy Systems: Renewable reliability, unit commitment, and electricity market design. Recent publications emphasize mean field games in energy and blockchain, stochastic volatility in portfolio optimization, and machine learning applications for financial engineering. He has advised graduate students such as Giulia Crippa, Nicolas Garcia, and Burak Aydin, often collaborating with researchers including M. Soner, P. Chan, and A.M. Reppen.

• Civil Engineering
• Physical Geography and Environmental Geoscience
• Environmental Engineering
• +۳ مورد دیگر

Dr. Christian Onof is an Associate Professor (Reader) in Stochastic Environmental Systems at Imperial College London's Department of Civil and Environmental Engineering (Faculty of Engineering). He holds affiliations with the Centre for Systems Engineering and Innovation, Environmental and Water Resource Engineering group, and the Grantham Institute. After completing undergraduate studies in Mathematics and Engineering in Paris and Hanover, he earned his PhD at Imperial College and began his academic career as a lecturer in 1994. Education: BSc in Mathematics/Engineering (Paris/Hanover), PhD in Environmental Systems (Imperial College London) His research focuses on stochastic rainfall modeling for hydrological simulations and flood design, particularly at fine time-scales, with emphasis on climate change impact assessment and development of downscaling tools. Recent work explores statistical/machine learning approaches for convective rainfall forecasting. Teaching responsibilities include pioneering courses in Statistics (MEng Year II), Operational Research (MEng Year IV), and Stochastic Hydrology (MSc). He has taught over a dozen undergraduate modules and contributed to international collaborations, including a course at École des Ponts ParisTech via the European Athens Network. As former Course Director of the MSc in Systems Engineering and Innovation, he has actively promoted student exchange programs, establishing partnerships with universities in Melbourne, Hong Kong PolyU, Barcelona, Queensland, and California. No scientific awards or specific grants are explicitly listed, though his research contributions are notable in environmental systems engineering.

Valerie Thomasمشاهده پروفایل

استاد

• Sustainability
• Energy Systems
• Industrial Ecology
• +۵ مورد دیگر

Valerie Thomas is the Anderson Interface Chair of Natural Systems at Georgia Tech, holding joint appointments in the H. Milton Stewart School of Industrial and Systems Engineering and the School of Public Policy. Her research focuses on energy systems, sustainability, industrial ecology, and science and technology policy. She earned a B.A. in Physics from Swarthmore College and a Ph.D. in Theoretical Physics from Cornell University, followed by postdoctoral research at Carnegie Mellon and Princeton Universities. Her work addresses low-carbon transportation, environmental impacts of food systems, and energy development in Africa. Key research areas include life cycle assessment, climate policy, and technology assessment. Thomas has contributed to over 80 technical publications and serves on advisory boards for the U.S. EPA and USDA/DOE. Education: Ph.D. in Physics, Cornell University; B.A. in Physics, Swarthmore College Awards: AAAS and APS Fellowships, Georgia Tech’s 1934 Outstanding Interdisciplinary Award Her teaching spans energy policy, lifecycle analysis, and engineering economics. She leads interdisciplinary teams at the Climate and Energy Policy Laboratory and the Technology Policy and Assessment Center, advancing sustainable systems engineering and policy solutions.

Lasantha Meegahapolaمشاهده پروفایل

دانشیار

• Power System Stability
• Renewable Energy Integration
• Microgrid Modelling and Control
• +۴ مورد دیگر

Associate Professor Lasantha Meegahapola is a Deputy Head of Department (Teaching & Learning) at RMIT University's School of Engineering in Melbourne, Australia. He holds an IEEE Senior Membership and serves as an Associate Editor for several prestigious journals, including IEEE Transactions on Power Systems and IET Renewable Power Generation. His research focuses on Power System Stability with Renewable Integration, Microgrid Control, and Smart Grid Technologies, addressing challenges like voltage stability, inverter-based grid dynamics, and renewable energy penetration. He has supervised 16 PhD students to completion and published over 200 articles. Key contributions include identifying stability issues in microgrids and advancing grid-forming inverter control strategies. His work aligns with UN Sustainable Development Goals 7 (Clean Energy), 9 (Infrastructure), and 13 (Climate Action). He is actively involved in IEEE committees, including the PSDP Task Force on Microgrid Stability. Teaching roles include Programme Manager for the Bachelor of Electrical Engineering (HK) and Subject Coordinator for Power System Analysis and Control courses. Collaborations span industry and international research institutions, emphasizing real-world applications of his research in power systems and renewable energy integration.

• Behavioral Ecology
• Evolutionary Biology
• Population Ecology
• +۱۱ مورد دیگر

Prof. Dr. Oliver Krüger is a behavioral ecologist and evolutionary biologist at Bielefeld University 's Faculty of Biology , where he leads the Department of Animal Behaviour since 2013. His research spans avian and marine mammal systems, focusing on life history strategies, parasite-host interactions, and environmental adaptation. Education: Biology studies at Bielefeld University (1994-1996) MSc in Oxford (1996-1997) PhD at Bielefeld University with Fritz Trillmich and Jan Lindström (1998-2000) Research Themes: Behavioral ecology, evolutionary biology, and population dynamics across tropical and temperate ecosystems. Key projects include NC³ (Niche Choice/Construction) and studies on Galápagos sea lions, common buzzards, and pinniped species. Scientific Leadership: Spokesperson, SFB TRR 212 "NC³" (2018-2025) Advisory Board member: German Ornithologists Union, IUCN SSC pinniped group, German Primate Centre Peer review roles: Humboldt Foundation, DFG, HFSP, NSF Awards: Leopoldina Prize (2001) Niko Tinbergen Award (2008) DFG Heisenberg Professorship (2010-2015)

Thomas S. Lontzekمشاهده پروفایل

استاد

• Economic Growth
• Quantitative Macroeconomics
• Resource and Energy Economics
• +۳ مورد دیگر

Thomas S. Lontzek is Professor of Economics at RWTH Aachen University, holding the Chair of Computational Economics within the School of Business and Economics since October 2016. His research develops numerical methods for economic decision-making with focus on climate change and environmental risks. His educational background includes economics studies at Maastricht University and UC San Diego (1999-2003), followed by PhD from University of Kiel (2009). Prior positions include Assistant/Senior Assistant at University of Zurich (2010-2016) and visiting scholar at Stanford's Hoover Institution (2012). Lontzek's research spans Economic Growth, Quantitative Macroeconomics, Resource and Energy Economics, Computational Economics, Climate Risk Management, and Decision Making under Uncertainty. His work emphasizes unconventional methods for analyzing economic processes through multidimensional, nonlinear stochastic optimization while incorporating ethical principles into economic analysis for sustainability challenges. His publication record reveals a consistent focus on climate economics, particularly the social cost of carbon, climate tipping points, and integrated assessment modeling. These works demonstrate how accounting for economic and climate risks, especially potential tipping points, necessitates more aggressive climate policies than traditional models suggest, often requiring sophisticated computational techniques to handle high-dimensional uncertainty. 2021 Erik Kempe Award for work on calculating an optimal CO2 tax Lontzek actively mentors students through research seminars and teaching, emphasizing methodological diversity and interdisciplinary approaches. He leads the Global Challenges Research Seminar through the Global Challenges Lab, providing students with opportunities to conduct innovative research using quantitative decision-making techniques for sustainable development challenges. His teaching portfolio for Summer Semester 2025 includes Quantitative Macroeconomics, Sustainable Finance, and specialized research seminars. He heads the Chair of Computational Economics, which includes scientific staff members Dr. Marco Thalhammer, Dr. Yifan Zhao, and Philipp Olivier, M.Sc., working collaboratively on climate economics and computational methods. The chair's research bridges theoretical economic modeling with practical policy applications, developing dynamic stochastic integrated assessment models capable of handling complex climate-economy interactions under uncertainty.

Yizhi Wangمشاهده پروفایل

استادیار

• Financialization
• Econometrics
• Climate Finance
• +۵ مورد دیگر

Dr Yizhi Wang, FHEA, is a Lecturer (Assistant Professor) in Finance at Cardiff Business School, Cardiff University, UK. He serves as Co-Director of the Cardiff Fintech Research Group and is the Editor-in-Chief of Elsevier’s Finance Research Letters . He is also Associate Editor for International Review of Financial Analysis and Research in International Business and Finance , and Guest Editor for International Review of Economics & Finance and Journal of Chinese Economic and Business Studies . Research Interests: Financialization and Econometrics Climate finance and carbon markets Cryptocurrency and FinTech indices Energy economics and risk management Green finance and ESG investing Behavioral and institutional finance Dr Wang has published extensively in world-leading journals such as Risk Analysis , European Journal of Operational Research , Journal of Economic Behavior & Organization , Energy Economics , and Journal of International Money and Finance . His work spans theoretical modeling, empirical econometrics, and policy-oriented studies. Scientific Awards: Shanghai Institute of International Finance and Economics Best Paper Award Teaching & Supervision: As a Fellow of the UK Higher Education Academy (FHEA), Dr Wang is module leader for undergraduate BS2514: Financial Markets and Institutions and postgraduate BST158: Big Data Analytics for Finance , earning consistently high teaching evaluations (4.8–4.9/5). He is available to supervise doctoral students in Financialization and has mentored graduates now employed at the University of Oxford, Morgan Stanley, and JPMorgan Chase. Labs & Research Groups: Co-Director, Cardiff Fintech Research Group Member, Cardiff Sustainable Finance Research Group Member, Environmental, Ecological, Extinction Accounting, Governance and Economics Research Group Member, Cardiff Business School Research Committee Dr Wang also curates multiple quarterly-updated indices (UCRY, ICEA, CBDCAI, NFTsAI, ACCC, FinTech Index) publicly available at https://sites.google.com/view/cryptocurrency-indices/home .

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.