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Marta Zofia KwiatkowskaView profile

Professor

• Automated verification
• Probabilistic model checking
• Temporal logics
• +3 more

Professor Marta Zofia Kwiatkowska is Professor of Computing Systems and Fellow of Trinity College at the University of Oxford, where she has held a faculty position since 2007. She previously served as Professor of Computer Science at the University of Birmingham (2001–2007), Reader and Lecturer at the University of Birmingham (1994–2001), and Lecturer at the University of Leicester (1986–1994). Her academic career began as Assistant Professor at the Jagiellonian University in Kraków, Poland (1980–1988). Education: BSc/MSc in Computer Science, Jagiellonian University, Kraków MA, University of Oxford PhD, University of Leicester Research Interests: Professor Kwiatkowska spearheaded the development of probabilistic and quantitative verification methods on the international stage. Her work bridges theory and practice through the PRISM model checker—the leading software tool in probabilistic model checking—used worldwide for research and teaching. Application domains include communication and security protocols , nanotechnology designs , power management , ubiquitous computing and systems biology . She investigates automated verification , temporal logics , semantic models for concurrency , real-time systems , and biological process modelling . Current grant funding exceeds £3.7 million from EPSRC, EU and ERC, including the prestigious ERC Advanced Grant VERIWARE. Scientific Awards & Honours: Fellow of the Royal Society Fellow of the ACM Fellow of the European Association for Theoretical Computer Science (EATCS) Fellow of the British Computer Society (BCS) Fellow of the Polish Society of Arts & Sciences Abroad ERC Advanced Grant VERIWARE (€2.046 M, 2010–2015) Top Cited Article Award, Theoretical Computer Science (2005–2010) Best Paper Award, QEST 2006 Doctoral Supervision & Grants: Professor Kwiatkowska actively supervises doctoral students (D.Phil. at Oxford) and post-doctoral researchers. She welcomes applications in areas aligned with her research interests, detailed here . Current students include Charlie Griffin, Daqian Shao, Matthew Yuan and Minghao Liu; past students and researchers number over twenty, many now in faculty or industry leadership roles. Laboratory & Teams: She leads the Oxford Quantitative Verification group within the Department of Computer Science. Ongoing projects include FUN2MODEL, ELSA, FAIR and the flagship PRISM probabilistic model checker. The group maintains strong collaborations with biological, robotics and engineering teams worldwide.

• Engineering sciences
• Materials science
• Aerospace
• +11 more

Ares J. Rosakis is the Theodore von Kármán Professor of Aeronautics and Mechanical Engineering at the California Institute of Technology (Caltech), where he served as Chair of the Division of Engineering and Applied Science from 2009-2015 and previously as Director of the Graduate Aerospace Laboratories (GALCIT). He has held numerous prestigious visiting professorships including at Nanyang Technological University, Northwestern University, Columbia University, Oxford University, and École Normale Supérieure in Paris. Rosakis earned his B.A. and M.A. in Engineering Science from Oxford University in 1978, followed by his Sc.M. (1980) and Ph.D. (1982) in Engineering (Solid Mechanics) from Brown University. He joined Caltech as an Assistant Professor in 1982, was promoted to Associate Professor in 1988, and to full Professor in 1993. In 2004, he was named the Theodore von Kármán Professor, one of Caltech's most distinguished named chairs. Rosakis is globally recognized as the foremost expert in dynamic failure mechanics of solid materials. His pioneering contributions span the dynamic failure of metals, composites, and interfaces. He invented Coherent Gradient Sensing (CGS) interferometry, a novel optical method sensitive to gradients of optical path differences that has been widely adopted in fracture mechanics and thin film stress measurements. His research encompasses dynamic shear-dominated rupture of heterogeneous materials, rupture mechanics of crustal earthquakes (where he experimentally discovered 'intersonic' or 'supershear' ruptures), and reliability of thin films and in-situ wafer level metrology. His work bridges engineering science, materials mechanics, and geophysics with remarkable interdisciplinary impact. His recent publications demonstrate a strong focus on earthquake mechanics and laboratory simulations of seismic events, particularly supershear earthquake ruptures. The research connects fundamental fracture mechanics with real-world geophysical phenomena, revealing how laboratory-scale experiments can illuminate the physics of large-scale earthquakes. His work has established critical links between theoretical models, experimental observations, and geological field evidence. Rosakis has received numerous prestigious awards including: 2024 Foreign Member of the Royal Society, UK 2023 Honorary PhD from National Technical University of Athens 2023 Honorary Degree of Doctor of Engineering from University of Illinois 2021 Zdeněk P. Bažant Medal for Failure and Damage Prevention 2018 Timoshenko Medal from ASME 2016 Elected to the National Academy of Sciences 2011 Elected to the National Academy of Engineering Throughout his distinguished career at Caltech, Rosakis has mentored numerous graduate students and postdoctoral researchers, many of whom have become leaders in their fields. His research has been continuously supported by major grants from the National Science Foundation, Department of Energy, and other federal agencies, focusing on dynamic fracture, earthquake mechanics, and advanced optical measurement techniques. He has served on numerous editorial boards and advisory committees for major scientific organizations. At Caltech, Rosakis leads research in the Graduate Aerospace Laboratories (GALCIT), where he has established world-class experimental facilities for studying dynamic fracture and earthquake mechanics. His laboratory features high-speed imaging systems capable of millions of frames per second, infrared diagnostics for temperature field measurements, and specialized equipment for simulating earthquake ruptures at laboratory scale. His research group combines experimental, theoretical, and computational approaches to address fundamental questions in solid mechanics and their applications to geophysics and materials engineering.

Peng ShigeView profile

Professor

• Nonlinear expectations and stochastic calculus
• Probability theory
• Nonlinear partial differential equations
• +5 more

Peng Shige is a Professor of 1st class at the School of Mathematics, Shandong University, China. He has held the Distinguished Professor title under the Ministry of Education (Cheung Kong Scholarship) since 1999. His academic journey includes degrees from Shandong University (Physics diploma, 1971-1974), Paris-IX (1985), and Aix-Marseille University (PhD 1986, Habilitation 1992). Research focuses on nonlinear expectations, stochastic calculus, partial differential equations, and financial mathematics. Key contributions include foundational work on backward stochastic differential equations (BSDEs), the g-expectation framework, and the G-expectation theory extending probability axioms to nonlinear settings. These innovations have advanced stochastic control, financial risk modeling, and differential games. Honors include the 2020 Future Science Award, 2011 Princeton Global Scholar, and 2005 Chinese Academy of Sciences Academician status. He delivered a plenary lecture at the 2010 International Congress of Mathematicians. Peng's work integrates theoretical breakthroughs with applied domains like financial engineering. His research has been widely cited (~8k citations) and shaped modern stochastic analysis methodologies.

• Numerical Analysis
• Partial Differential Equations
• Finite Element Method
• +3 more

Dirk Praetorius is a Professor of Numerics of Partial Differential Equations (PDEs) at the Technische Universität Wien (TU Wien) , affiliated with the Institute for Analysis and Scientific Computing (ASC) within the Faculty of Mathematics and Geoinformation . He leads the research group on Numerics of PDEs and has held various leadership roles, including Institute Director (since 2020) and head of the Numerics research area. His work focuses on numerical methods for PDEs, including Finite Element Methods (FEM), Boundary Element Methods (BEM), adaptive algorithms, and computational micromagnetics. Education and Career: Praetorius earned his Diplom in Mathematics (2000) and PhD in Applied Mathematics (2003) from TU Wien, followed by a Habilitation in Numerical Analysis (2005). He has been a faculty member at TU Wien since 2005, progressing from Assistant Professor to full Professor in 2017. He has also held visiting positions at institutions such as the University of Jyväskylä and RICAM (Linz). Research Interests: His research spans numerical analysis, adaptive FEM/BEM, a-posteriori error estimation, matrix compression, and computational micromagnetics. He has contributed to modeling spin dynamics, magnetic skyrmions, and multiscale systems. His work emphasizes efficient algorithms for large-scale problems and optimal computational complexity. Awards and Editorial Roles: Praetorius received the TU Best Teacher Award (2021) and TU Best Lecture Award (2019). He serves as Senior Editor for Computational Methods in Applied Mathematics (CMAM) and on the editorial board of Applied Numerical Mathematics (APNUM) . He co-founded the outreach initiative TUForMath to promote mathematics education. Grants and Projects: He leads or co-leads several research projects funded by the Austrian Science Fund (FWF), including the collaborative SFB "Taming Complexity in Partial Differential Systems" (2017–2025) and international collaborations with Germany. His work addresses topics like functional error estimates, nonlinear PDEs, and computational design of magnetic devices. Labs and Teams: He contributes to the ASC Institute and coordinates interdisciplinary projects involving computational physics and engineering. His team develops software tools like MooAFEM and Commics for micromagnetic simulations.

• Software Architecture
• Microservices
• Cloud Computing
• +7 more

Uwe Zdun is a Professor at the Faculty of Computer Science, University of Vienna, where he serves as Vice-Director of Studies for Computer Science and Head of the Research Group Software Architecture. His teaching portfolio includes core courses such as Software Engineering 2, Advanced Software Engineering, and Practical Software Courses for Bachelor's and Master's theses across multiple semesters (2024W-2025S). His research spans software architecture with emphasis on microservices, cloud computing, and DevOps. Key focus areas include architectural design decisions, infrastructure-as-code conformance, security in distributed systems, and the integration of machine learning operations (MLOps/RLOps). He investigates cognitive aspects of architecture practices through controlled experiments and develops model-driven approaches for quality assessment in complex systems. Recent publications (2024-2026) reveal three dominant trends: (1) Security and coupling analysis in infrastructure-as-code deployments, (2) MLOps/RLOps integration for Industry 4.0 cyber-physical systems, and (3) Performance optimization patterns for CI/CD pipelines and autoscaling. His work bridges theoretical architecture models with industrial practice, particularly in microservice ecosystems and reinforcement learning applications. Professor Zdun leads the Research Group Software Architecture at the University of Vienna's Faculty of Computer Science. The group focuses on empirical validation of architectural patterns, tool development for conformance checking, and advancing design decision methodologies in cloud-native and AI-driven systems.

• Antenna Design
• Microwave Engineering
• Dielectric Materials
• +2 more

Wolfgang Bösch is a Professor at Graz University of Technology's Institute of Microwave and Photonic Engineering, specializing in advanced RF components and measurement techniques. His research advances high-frequency systems through innovations in antenna technology and electromagnetic theory. Research domains include: metamaterial-based antennas, precision measurement calibration, microwave filter optimization, and 3D-printed RF components. Recent work demonstrates strong focus on millimeter-wave systems and reconfigurable antenna arrays. Publications highlight expertise in: machine learning for filter design, metasurface applications, PCB transitions for high-frequency systems, and uncertainty quantification in RF engineering. Research consistently addresses miniaturization and performance optimization challenges. Awards recognize contributions to measurement science and antenna design: Fellow of IET, Houska Prize, and best paper awards. Current laboratories investigate liquid crystal antenna systems and error calibration methodologies for next-generation wireless systems.

• Financial Enterprise Management
• Enterprise Risk Management
• IT-based Enterprise Management
• +3 more

Prof. Walter Schwaiger is a Full Professor at TU Wien’s Faculty of Mechanical and Industrial Engineering, leading the Institute of Management Science. His academic roles include serving as Head of the Faculty Council since 2010 and holding various curriculum committee positions. He teaches critical courses such as Financial Management, Enterprise Risk Management, and IT-based Management across bachelor’s and master’s programs. His research focuses on three core areas: Financial Enterprise Management (stochastic NPV modeling for renewable energy investments), Enterprise Risk Management (risk maturity assessments via ERMMA studies), and IT-based Management (ontology-driven accounting frameworks like OntoREA). Recent work includes predictive analytics applications in credit risk scoring and pandemic-driven default prediction studies. Prof. Schwaiger has authored influential textbooks like IFRS-Finanzmanagement series and pioneered the REA-based ERP-Control system. He actively contributes to management control research, publishing in venues like Controlling and WingBusiness , and collaborates with institutions like Funk Stiftung on large-scale ERM maturity studies. His professional service includes leading faculty strategy groups and quality management initiatives at TU Wien, reflecting his commitment to institutional governance and academic excellence.

• Engineering Sciences
• Materials Science
• Aerospace
• +7 more

Ares Rosakis is the Theodore von Kármán Professor of Aeronautics and Mechanical Engineering at the California Institute of Technology (Caltech). He has served as Chair of the Division of Engineering and Applied Science (2009–2015) and Director of the Graduate Aeronautical Laboratories (GALCIT) (2004–2009). Rosakis holds visiting professorships at Nanyang Technological University (2018–2023) and Northwestern University (2018). Education : B.A. and M.A. in Engineering Science (Oxford, 1978); Sc.M. and Ph.D. in Engineering (Solid Mechanics, Brown University, 1980–1982) Academic Career : Caltech faculty since 1982 (Assistant, 1982; Associate, 1988; Full Professor, 1993) As a world-leading expert in dynamic failure mechanics of solid materials, Rosakis has pioneered research in dynamic ductile failure of metals, intersonic/supershear ruptures in composites and earthquakes, and Coherent Gradient Sensing (CGS) interferometry . His work spans experimental mechanics, solid mechanics, geophysics, and thin film stress measurement. His 15 most recent articles (2010–2014) focus on dynamic shear ruptures , fault mechanics , brittle failure , high-strain-rate deformation , and laboratory earthquake simulations , reflecting his cross-disciplinary expertise in materials science, geophysics, and mechanics. Scientific Awards & Recognitions Foreign Member of the Royal Society (2024) Two Honorary Doctorates (2023) U.S. National Academy of Engineering (2011) NASA Group Achievement Award (2009) Timoshenko Medal (2018) Multiple SEM and ASME awards (1989–2013) Research Leadership includes directing GALCIT and developing advanced optical and infrared diagnostic methods for real-time crack propagation and temperature measurement. His work bridges fundamental mechanics with applied material failure analysis , influencing aerospace, seismology, and nanotechnology.

Bano Mehdi-SchulzView profile

Assistant Professor

• Ecohydrology
• Water Quality Management
• Climate Change Impacts
• +4 more

Bano Mehdi-Schulz is an Assistant Professor at the University of Natural Resources and Life Sciences, Vienna (BOKU), leading the 'Eco-hydrological and Land Use Modelling' group at the Institute of Hydrology and Water Management. She is a Substitute Member of the Ethics Committee. Her research focuses on ecohydrology, integrating hydrological and agricultural sciences to address water quality impacts from anthropogenic changes and future climate scenarios. Education: B.Sc. in Soil Science, M.Sc. in Agricultural Engineering, and Ph.D. from McGill University's Department of Geography. Awards include the Alexander Graham Bell Canada Graduate Scholarship (2009) and FWF Elise Richter Fellowship (2019). Her work bridges natural and social sciences, employing models to assess land use change and water resource management. Research Interests: Quantifying impacts of land use and climate change on water quality, ecohydrological modeling uncertainty, sustainable intensification strategies, and nitrate transport dynamics. Her team explores how farming practices and climate interact to influence water systems, with projects like ALUCSI (FWF-funded) and NitroClimAT (ACRP). Grants & Projects: Recent projects include ALUCSI (2019-2023), NitroClimAT (2018-2022), and UnLoadC3 (2014-2017). Current student advisees include researchers studying SWAT model uncertainty, sustainable intensification pathways, and water quality in East African basins. Labs/Teams: Leads the Eco-hydrological and Land Use Modelling group, collaborating with institutions like IIASA and SEC. Research emphasizes model coupling (e.g., SECLAND-SWAT) and satellite data integration for data-scarce regions.

Nikolina BanView profile

Assistant Professor

• Climate Modeling
• Mountain Climate
• Convection-Permitting Models
• +4 more

Dr. Nikolina Ban is an Assistant Professor at the Department of Atmospheric and Cryospheric Sciences (ACINN) at the University of Innsbruck, Austria. Her research focuses on high-resolution climate modeling, convection-permitting models, and mountain climate dynamics. She leads projects such as 'Mountain Climate at the Kilometre-Scale Resolution' and collaborates with international teams like TEAMx-UIBK and the CORDEX-FPSCONV-Team. Key areas include extreme rainfall projections, hail/lightning diagnostics, and the impact of climate change on Alpine regions. Expertise: Regional climate modeling, convection-permitting approaches, mountain climate variability. Key Projects: Third Pole climate simulations, Alpine hydrological studies, and national climate scenario development in Austria. Her work addresses challenges in resolving fine-scale climate processes over complex terrains. Recent studies emphasize improving projections of precipitation extremes and understanding model uncertainties. Collaborations span institutions globally, including the Swiss Federal Institute of Technology (ETH Zurich) and the University of California, Los Angeles (UCLA). Publications highlight advancements in ensemble-based climate simulations and the added value of kilometer-scale models for capturing temperature and wind patterns in alpine regions. Ongoing research includes evaluating dynamical downscaling techniques for reliable regional climate change assessments.

• Optimization and optimal control
• Inverse problems
• Mathematical imaging
• +5 more

Karl Kunisch is a Professor at the Department of Mathematics and Scientific Computing at the University of Graz and serves as Scientific Director of the Radon Institute of the Austrian Academy of Sciences in Linz. With a distinguished career spanning several decades, he has established himself as a leading researcher in optimization and control theory. Prof. Kunisch completed his PhD and Habilitation at the Technical University of Graz in 1978 and 1980, respectively. His academic journey includes significant positions at Brown University's Lefschetz Center for Dynamical Systems, INRIA Rocquencourt, Universite Paris Dauphine, and he previously served as a professor of numerical mathematics at the Technical University of Berlin. Research Interests: Prof. Kunisch's research focuses on optimization and optimal control, inverse problems and mathematical imaging, numerical analysis and applications, with current emphasis on life sciences applications. His specific areas include Optimal Control of Partial Differential Equations, Nonsmooth Optimization in Function Spaces, and Applications of Optimization and Control in the Life Sciences. His work bridges theoretical mathematics with practical applications across various scientific domains. His recent publications demonstrate a continued focus on advancing the theoretical foundations of optimal control while developing practical numerical methods. Key trends include work on infinite horizon control problems, feedback stabilization techniques, applications to PDE-constrained optimization, and the integration of machine learning approaches with traditional control theory. His research group actively explores connections between theoretical developments and applications in the life sciences. Scientific Recognition: W.T. and Idalia Reid Prize 2021 SIAM Fellow (2017) European Research Council Advanced Grant (2015) Alwin Walther Medaille (2008) SIAM Outstanding Paper Prize (2006) Prof. Kunisch has made substantial contributions to the mathematical community through his editorial work, serving as editor for prestigious journals including SIAM Journal on Control and Optimization, SIAM Journal on Numerical Analysis, and the Journal of the European Mathematical Society. He leads the Research Group on Optimization and Optimal Control at the Johann Radon Institute for Computational and Applied Mathematics (RICAM) and is involved in the ERC-Project OCLOC "From Open to Closed Loop Control".

• Data Mining
• Machine Learning
• Clustering Algorithms
• +3 more

Anna Beer is a researcher in the Faculty of Computer Science, specializing in data mining and machine learning with a focus on density-based clustering, spectral clustering, and interactive clustering frameworks. She holds a BSc and MSc in computer science and maintains an ORCID profile (https://orcid.org/0000-0002-6890-997X) for her research contributions. Research Themes: Development of clustering algorithms (e.g., DISCO, Scar, LUCKe), fairness in density-based clustering (FairDen), and applications to molecular dynamics and climate research (DROPP). Collaborations: Works with colleagues like Ira Assent, Christian Plant, and Lars Krieger, with recent contributions to conferences like ICLR 2025. Activities: Presented research on density-connectivity distance at a 2023 oral contribution. Publications: 9 publications since 2019, including 3 in 2025 and 6 in 2024, covering topics from cluster evaluation to deep active learning strategies.

Sonja WogrinView profile

Professor

• Optimization
• Bilevel Programming
• Capacity Expansion Planning
• +5 more

Sonja Wogrin is a University Professor (Univ.-Prof.) at Graz University of Technology (TU Graz), where she has been heading the Institute for Electricity Economics and Energy Innovation since August 2021. She holds a Dipl.-Ing. in Technical Mathematics from TU Graz (2008), a Master of Science in Computation for Design and Optimization from MIT (2008), and a doctorate in Electricity Systems from Universidad Pontificia Comillas (2013). Her educational background includes: Doctorate in Electricity Systems, Universidad Pontificia de Comillas (June 2013) Dipl.-Ing. in Technical Mathematics, Graz University of Technology (October 2008) Master of Science in Computation for Design and Optimization, MIT (June 2008) Professor Wogrin's research focuses on decision support systems in the energy sector, optimization methodologies, and particularly the problem of generation capacity expansion. Her work spans several key areas including bilevel programming, capacity expansion planning, energy storage systems, and time series aggregation for energy system optimization. She has made significant contributions to understanding how to integrate renewable energy sources into power systems while maintaining economic efficiency and grid stability. Her research often addresses the challenges of decarbonizing electricity systems through advanced mathematical modeling and optimization techniques. Her recent publications demonstrate a strong focus on improving the computational efficiency of energy system models while maintaining accuracy, with particular attention to the integration of renewable energy sources, energy storage systems, and the development of resilient energy communities. She has pioneered work on time series aggregation methods that balance computational tractability with model accuracy, which is crucial for long-term energy planning under uncertainty. Professor Wogrin has received several prestigious awards and fellowships including: 4th EASE Student Award for "Co-Optimisation of energy storage technologies in tactical and strategic planning models" (2019) Beca de movilidad para investigadores "NILS Ciencia y Sostenibilidad" (2015) Beca Erasmus "Personal Docente/Investigador" de formación (2016) Beca Iberdrola de ayuda a la investigación en energía y medio ambiente (2020) She leads multiple significant research projects including EU - NetZero-Opt, RINGs, iKlimET, V2G-QUESTS, and CIDEAL, which focus on optimizing energy systems for net-zero emissions, resilient energy networks, climate and energy system modeling, vehicle-to-grid integration, and industrial decarbonization. Her work has substantial practical implications for energy policy and grid operations in Austria and beyond. Professor Wogrin collaborates extensively with industry partners including Austrian Power Grid AG, KELAG, and Netz Niederösterreich, ensuring her research addresses real-world energy challenges. Professor Wogrin leads the research group at the Institute for Electricity Economics and Energy Innovation, which develops advanced optimization models for energy systems. Her team has created the LEGO (Low-carbon Expansion Generation Optimization) model, an open-source tool for energy system optimization that has gained international recognition. The group's work spans from fundamental optimization methods to practical applications in energy system planning and operation, with a strong emphasis on computational efficiency and model accuracy.

Martin Ostoja-StarzewskiView profile

Professor

• Continuum Mechanics
• Stochastic Mechanics
• Fractal Media
• +7 more

Martin Ostoja-Starzewski , Ph.D. (McGill), is a Professor of Mechanical Science & Engineering at the University of Illinois at Urbana-Champaign , with affiliate appointments at the Beckman Institute and National Center for Supercomputing Applications . His research spans continuum mechanics , stochastic wave propagation , and fractal media , focusing on scaling laws and the statistical-to-representative volume element transition. 2006–Present: Professor, UIUC 2001–2005: Canada Research Chair, McGill University 2023: Rothschild Distinguished Visiting Fellow, University of Cambridge 2022: Member, European Academy of Sciences and Arts 2024: Academia Europaea Foreign Member His work pioneered continuum mechanics with spontaneous second law violations and tensor random fields for stochastic PDEs. He authored four foundational books, including Tensor-Valued Random Fields for Continuum Physics (2019), and edited 16 special issues. Recent 2025–2023 articles explore odd elasticity , fractal thermodynamics , and stochastic wavefronts , bridging non-equilibrium thermodynamics to granular Couette systems . Scientific accolades include the Worcester Reed Warner Medal (2018) and ASME , AAM , SES fellowships. As part-time faculty at Beckman Institute (2008–Present), he integrates bioimaging with mechanics across electrosurgery and traumatic brain injury modeling.

Sara van de GeerView profile

Professor

• Mathematics for machine learning
• High-Dimensional statistics
• Empirical processes
• +2 more

Sara van de Geer is a Full Professor at the Seminar for Statistics within the Department of Mathematics at ETH Zürich since 2005. She previously held academic positions at the University of Leiden, Université Paul Sabatier (Toulouse), and others. She earned a Master's (1982) and Ph.D. (1987) in Mathematics from Leiden University. Her research focuses on high-dimensional statistics, empirical processes, and mathematical foundations of machine learning. Van de Geer has received prestigious recognitions including the Van Wijngaarden Award (2016), Knight in the Order of Orange-Nassau (2015), and membership in Leopoldina (2013). She served as President of the Bernoulli Society (2015–2017) and Chair of the Seminar for Statistics at ETH Zürich. Her contributions include landmark works on statistical learning theory and high-dimensional inference, with key publications in top journals like Annals of Statistics and SIAM/ASA Journal on Uncertainty Quantification. Her academic leadership includes organizing Saint Flour Lectures, Wald Lectures (2016), and delivering plenary lectures globally. Her research bridges theoretical statistics with applied methodologies, emphasizing rigorous mathematical frameworks for modern data analysis challenges.