جست‌وجوی استاد و پژوهشگر

Ward Romeijndersمشاهده پروفایل

استاد

• Operations Research
• Management Science
• Stochastic Programming
• +۷ مورد دیگر

Prof. Ward Romeijnders is a Full Professor in the Department of Operations Management & Operations Research at the University of Groningen. He holds leadership roles in academic organizations such as Secretary of the Stochastic Programming Society (COSP), Associate Editor of Mathematical Methods of Operations Research, and Board member of LNMB. His research focuses on stochastic programming, optimization under uncertainty, and applications in energy, logistics, healthcare, and finance. He has led projects like the NWO VIDI grant 'Discrete Decision Making under Uncertainty' (2023-2027) and previously the NWO VENI project on planning under uncertainty. Education: Doctorate in Operations Research (details unspecified). Research Interests: Stochastic optimization, risk-averse decision-making, integer programming, and applications in societal challenges. Recent publications span algorithmic advancements in Benders decomposition, robust optimization, and error-bound theories. He has received multiple awards, including the Gijs de Leve Prize (2015-2017) and Willem R. van Zwet Award (2016). As a teacher, he instructs advanced courses on stochastic programming and optimization under uncertainty. Grants: NWO VENI (2017-2020), NWO VIDI (2023-2027). Editorial Roles: Mathematical Methods of Operations Research, Euro WG on Stochastic Optimization.

• Systemic Risk
• Financial Risk Management
• Credit Scoring
• +۴ مورد دیگر

Christophe Hurlin is a Professor at the University of Orleans specializing in finance, risk management, and econometrics. His research spans systemic risk measurement, credit scoring models, machine learning applications in finance, and computational reproducibility in financial research. With over 30 scholarly publications, he has established himself as a significant contributor to financial econometrics and risk management literature. His primary research interests focus on systemic risk measurement methodologies, credit scoring models incorporating machine learning techniques, and the reproducibility of financial research findings. Hurlin's work often bridges theoretical econometric frameworks with practical financial applications, particularly in banking regulation and risk modeling. He has developed innovative tools such as the Risk Map for validating risk models and has contributed significantly to understanding systemic risk through comprehensive surveys and comparative analyses of risk measures. Hurlin's publication record shows a clear evolution from traditional risk measurement techniques toward integrating machine learning approaches in finance, with recent work focusing on the fairness of credit scoring models, Bayesian approaches to default probability calibration, and the intersection of machine learning with regulatory capital requirements. His research demonstrates consistent engagement with both theoretical underpinnings and practical applications in financial risk management. Hurlin has collaborated extensively with researchers across Europe, particularly with colleagues from HEC Paris (notably Christophe Pérignon), creating a substantial body of work on systemic risk, credit scoring, and computational reproducibility. His most cited works include 'Where the Risks Lie: A Survey on Systemic Risk' and 'Nonstandard Errors,' reflecting his influence in both risk management and methodological research. His research has practical implications for banking regulation, financial stability monitoring, and the implementation of machine learning in credit assessment systems. Through his work on computational reproducibility, Hurlin has also contributed to improving research standards in financial economics, advocating for greater transparency and verification in published findings.

• Financial Econometrics
• Volatility Modeling
• Time Series Analysis
• +۴ مورد دیگر

Andrew J. Patton is a Professor in the Department of Economics at Duke University's Trinity College of Arts & Sciences, with a secondary affiliation at Singapore Management University's School of Economics. His office is located at 213 Social Sciences Building, Box 90097, Durham, NC 27708-0204, United States, and his professional website is available at http://econ.duke.edu/~ap172/. Dr. Patton's research focuses on financial econometrics, with particular expertise in volatility modeling, high-frequency data analysis, and dependence structures in financial markets. His work spans several key areas including realized variance methods, copula modeling for financial time series, risk management techniques, and forecast evaluation methodologies. He has made significant contributions to understanding market microstructure, hedge fund risk exposures, and the dynamics of financial correlations. His publication record demonstrates consistent output in top finance and econometrics journals, with recent work exploring machine learning applications in volatility forecasting, granular risk measures, and the impact of high-frequency data on asset pricing models. The research shows a clear trajectory toward increasingly sophisticated modeling of financial dependencies and risk structures. Dr. Patton has received recognition for his scholarly contributions, ranking among SSRN's top 1,427 authors by total paper downloads and top 1,090 by total paper citations. His work is frequently cited in the field of financial econometrics, indicating substantial influence on contemporary research. He maintains active research collaborations with leading economists including Tim Bollerslev, Kevin Sheppard, Tarun Ramadorai, and Robert Engle, among others. These collaborations span multiple institutions and have produced influential work on volatility modeling, risk measurement, and financial market dynamics.

• Medical Physics
• Radiation Oncology
• Proton Therapy
• +۳ مورد دیگر

Sara Margareta Cecilia Pilskog serves as an Associate Professor in the Department of Physics and Technology at the University of Bergen, Norway, with dual affiliation at Haukeland University Hospital's Department of Cancer Treatment and Medical Physics. Her research bridges theoretical medical physics and clinical oncology applications, focusing on precision radiotherapy techniques and biological optimization. Her primary research interests center on proton therapy innovation, where she investigates biological optimization strategies using linear energy transfer (LET) and relative biological effectiveness (RBE) modeling. She develops adaptive radiotherapy frameworks to address inter-fractional motion in pelvic cancers, particularly prostate and rectal malignancies. Her work also pioneers neutron-based in-vivo range verification systems and statistical deformation models for dose accumulation. Current projects emphasize reducing treatment margins through anatomical robustness and optimizing biological dose distributions for organ sparing. Analysis of her 15 most recent publications reveals a dominant focus on improving proton therapy precision for pelvic cancers through biological modeling and motion management. Approximately 70% of her work addresses prostate cancer applications, with significant contributions to adaptive strategies for inter-fractional changes and biological optimization techniques. Her research consistently employs Monte Carlo simulations (particularly FLUKA) and clinical data analysis to translate theoretical models into clinically viable solutions. No scientific awards were documented in the provided materials. While specific advising details remain unreported, her collaborative patterns indicate active mentorship within the University of Bergen's medical physics research ecosystem. Her publications consistently involve junior co-authors from clinical physics teams at Haukeland University Hospital, suggesting hands-on supervision of technical staff and research fellows in radiotherapy innovation projects. Grant funding appears primarily channeled through institutional hospital-university partnerships focused on clinical translation of advanced radiotherapy techniques. Dr. Pilskog operates within the University of Bergen's medical physics research cluster that maintains close operational ties to Haukeland University Hospital's radiotherapy department. This integrated academic-clinical environment enables direct implementation of her research on adaptive proton therapy and biological optimization into clinical workflows, with particular emphasis on pelvic cancer treatment protocols. The team utilizes advanced Monte Carlo simulation platforms and clinical treatment planning systems to develop and validate next-generation radiotherapy approaches.

Brent A. Johnsonمشاهده پروفایل

استاد

• Biostatistics
• Semi-parametric methods
• Missing data analysis
• +۹ مورد دیگر

Brent A. Johnson is a Professor of Biostatistics, Ophthalmology, and Neurology at the University of Rochester Medical Center. He holds joint appointments in the School of Medicine and Dentistry and leads the Biostatistics and Computational Biology Department. His research focuses on methodological advancements in semi-parametric methods, causal inference, and adaptive treatment strategies, with substantive applications in HIV/AIDS, environmental health, and clinical epidemiology. Johnson collaborates widely across disciplines, including cardiology, neurology, and global health, particularly in Sub-Saharan Africa. He directs the Biostatistics Core for the University of Rochester's Center for AIDS Research and serves as an on-call statistician for the Flaum Eye Institute. Education: PhD in Statistics from North Carolina State University (2003), MS in Biostatistics from University of Minnesota (1997), BA in Mathematics from St. Olaf College (1995). Awards include the NSF VIGRE Fellowship and Best Student Paper Award from the American Statistical Association. Research Interests: Dynamic treatment regimes, personalized medicine, missing data methods, biomarker development, and HIV prevention strategies. His lab develops statistical tools for observational studies and clinical trials, with recent work on machine learning approaches for censored outcomes and causal inference. Grants and Funding: NIH grants for HIV/AIDS research, environmental health projects, and methodological development. Collaborations include the AIDS Clinical Trials Group (ACTG), the South African TDF study, and the El Paso Asthma Cohort. Labs/Teams: Directs the Brent Johnson Lab, focusing on statistical methodology for biomedical applications. Key lab members include postdoctoral fellows like John Rice and alumni Li Li (Eli Lilly) and Xin Lu (Sanofi).

Moe Thandar Wynnمشاهده پروفایل

استاد

• Process Mining
• Data Quality
• Business Process Management
• +۳ مورد دیگر

Professor Moe Thandar Wynn is a Co-Director of QUT's Centre for Data Science and holds a Professorship in the School of Information Systems at Queensland University of Technology (QUT). She leads the Process Science Academic Program and serves as the Academic Lead of Research for the School of Information Systems. Her expertise spans Process Mining, Data Quality, and Robotic Process Automation (RPA). Prof Wynn has attracted over AUD 6 million in research funding and holds an h-index of 41 with 8700+ citations. She is a member of the Australian Research Council College of Experts (2023–2025) and has received prestigious awards including the QLD Women in Technology Excellence Award (2024). Her research focuses on formal foundations of process modeling, verification, and automation. She has contributed to international conferences as a co-chair and program committee member, and co-edited special issues on RPA and process dynamics. Prof Wynn collaborates with industries like healthcare, insurance, and agriculture to optimize business processes through data-driven insights. Current research includes privacy-preserving process mining and quality-driven event log enhancement. Education: PhD (QUT, 2006), M. Information Technology (Research, QUT) Key Projects: Hospital Capacity Optimization, Liquid Process Model Collections, Risk-Aware BPM Supervision: Over 10 completed PhD/MSc students in process mining and analytics Awards: Multiple QUT Excellence Awards, ARC College Membership Her lab focuses on advancing process intelligence and RPA, with ongoing efforts in data quality frameworks and process mining standards (e.g., IEEE XES). She actively participates in industry partnerships, such as the CRC Food Agility project, to bridge research and real-world applications.

Robert MacKayمشاهده پروفایل

استاد

• Dynamical Systems
• Mathematical Physics
• Complexity Science
• +۳ مورد دیگر

Robert MacKay is a Professor of Mathematics and Director of Mathematical Interdisciplinary Research at the University of Warwick. His work bridges pure and applied mathematics, focusing on dynamical systems, mathematical physics, and complexity science with applications to economics, engineering, and fusion energy. He leads the Warwick team in the Simons collaboration on Hidden Symmetry and Fusion Energy, addressing challenges in stellarator design. He teaches advanced courses like MA4H0 Applied Dynamical Systems and TCC Thermal Economics, the latter pioneering a thermodynamic approach to macroeconomics. His research interests include nonlinear dynamics, bifurcation theory, and applications to physics (e.g., plasma confinement), biology, and finance. Collaborations include work on magnetohydrodynamic equilibria and single-particle motion in non-axisymmetric magnetic fields. He has secured grants from EPSRC, Royal Society, and the Simons Foundation, supporting interdisciplinary projects such as the Mathematics of Complexity Science and Systems Biology (2009–2011). MacKay holds prestigious awards including Fellowships from the Royal Society (FRS), Institute of Physics (FInstP), and Institute of Mathematics and its Applications (FIMA). His recent work explores thermal macroeconomics, financial market dynamics, and geometric approaches to plasma confinement. He advises PhD students and postdocs in nonlinear dynamics and PDE theory, fostering the next generation of complexity scientists.

Rafael Macián-Juanمشاهده پروفایل

استاد

• Nuclear Safety
• Reactor Thermohydraulics
• Experimental Thermohydraulics
• +۳ مورد دیگر

Prof. Rafael Macián-Juan holds the Chair of Nuclear Engineering (NTech) at the Technical University of Munich (TUM), part of the TUM School of Engineering and Design. He specializes in nuclear safety, reactor thermohydraulics, and advanced nuclear systems. With over 20 years of experience, he led research at the Paul Scherrer Institute (PSI) in Switzerland before joining TUM in 2007. His work focuses on experimental analysis, computational methods for nuclear systems, and radiation applications in medicine. Education: MSc in Energy Engineering (1990, Polytechnic University of Valencia), MSc & PhD in Nuclear Engineering (1993/1996, Pennsylvania State University) Research emphasizes reactor safety through experimental thermohydraulics, coupled neutronic simulations, and innovative fuel design. His 70+ publications address CCFL phenomena, uncertainty quantification, and drift-flux models. Awards include TUM's Golden Teaching Award (2009/2010) and Alpha Nu Sigma membership. Led the development of DYNSUB coupled code system and conducted critical studies on steam bubble condensation in large geometries. His lab integrates experimental facilities with advanced computational tools for safety analysis.

Zijian Diaoمشاهده پروفایل

دانشیار

• Quantum Computation
• Quantum Information Theory
• Natural Language Processing
• +۷ مورد دیگر

Zijian Diao is an Associate Professor in the Department of Mathematics at Ohio University's College of Arts and Sciences, where he contributes to both teaching and research. He is based at the Eastern Campus in Shannon Hall and teaches a wide range of undergraduate mathematics courses. Education: Ph.D. in Mathematics, Texas A&M University, 2001 M.S. in Computer Science, University of Illinois, 2003 B.S. in Automation, University of Science and Technology of China, 1996 His research spans interdisciplinary areas with a strong focus on quantum computation and information theory , where he has made contributions to Grover's algorithm, quantum counting, and quantum circuit design. He has also worked in natural language processing , particularly in multilingual speech-to-speech translation systems like MARS. Additional interests include control theory , partial differential equations , and mathematical modeling . His recent and ongoing publications reflect a blend of theoretical mathematics and applied computational science. The works trend toward quantum algorithms and foundational mathematical proofs, with earlier contributions in NLP and control systems. His research bridges pure mathematics with practical implementations in quantum computing and language technologies. Scientific Awards: Ohio University Regional Higher Education Outstanding Professor Dr. Diao advises undergraduate and graduate students in mathematics and related fields, though specific student names are not listed. He has been involved in research projects supported by academic grants, particularly in quantum computing and interdisciplinary technology development. His curriculum vitae indicates sustained scholarly activity across multiple domains. He is associated with research groups and collaborations in quantum computing, having co-authored works with G. Chen, C. Huang, and others. His work in NLP was part of larger team efforts involving researchers from industry and academia, suggesting active participation in collaborative technical teams.

• Statistical Mechanics
• Statistical Physics
• Error-Correcting Codes
• +۱۲ مورد دیگر

David Saad is a Professor at Aston University, affiliated with the College of Engineering and Physical Sciences, the School of Computer Science and Digital Technologies, and the Applied Mathematics & Data Science group. He also leads the Aston Centre for Artificial Intelligence Research and Application and holds the 50th Anniversary Chair of Complexity Physics. His academic appointments include Professor of Information Mathematics since 1999 and former Head of the Mathematics Group (2006–2012, 2015–2019). His educational background includes: PhD in Engineering, Tel Aviv University (1993) MSc in Physics, Tel Aviv University (1987) BA in Physics and BSc in Electrical Engineering, Technion, Israel (1982) David Saad's research focuses on the application of statistical physics to complex computational and engineering problems. His primary interests include statistical mechanics of disordered systems, error-correcting codes, message-passing algorithms, learning in neural networks, and distributed optimization in networks such as smart grids and optical communication systems. He combines theoretical rigor with practical applications in machine learning, communications, and energy systems. His recent publications (2024–2025) demonstrate a strong trend in interdisciplinary research, bridging physics, computer science, and engineering. Key themes include neuromorphic computing, network inference from data, viral load estimation, and cascading failure modeling, indicating a continued focus on inference, optimization, and resilience in complex systems. His scientific recognition includes: Fellow of the Institute of Mathematics and its Applications Senior Fellow of the Higher Education Academy David Saad has supervised several research students, including H. F. Po, E. Harrison, M. Sheikh, B. Li, E. Manuylovich, and R. Sadeghi, many of whom appear as co-authors on recent publications. He has also been involved in research grants and projects related to smart grids, optical networks, and neuronal network analysis. His work involves collaborations with institutions across the UK and internationally, as evidenced by his research council membership and co-authored outputs. He leads research in the Aston Centre for Artificial Intelligence, focusing on theoretical and applied aspects of machine learning and complex systems. His team applies message-passing techniques to problems in energy distribution, communication networks, and biological data analysis, contributing to both foundational theory and real-world applications.

Alexander Kurapovمشاهده پروفایل

استاد مدعو

• Ocean Modeling
• Data Assimilation
• Coastal Oceanography
• +۷ مورد دیگر

Alexander Kurapov holds a Courtesy Appointment at Oregon State University within the College of Earth, Ocean, and Atmospheric Sciences, Department of Oceanography. He is actively engaged in research involving ocean modeling and data assimilation, with a focus on coastal and shelf processes along the U.S. West Coast and the Bering Sea. His research interests span oceanic data assimilation, coastal ocean modeling, wind-driven circulation, internal tides, shelf mixing, and nearshore flows. These areas are central to understanding coastal dynamics, climate variability, and improving ocean forecasting systems. The recent publications highlight a strong trend in high-resolution numerical modeling, variational and ensemble data assimilation techniques, and analysis of coastal and shelf-scale processes. Topics include internal tide dynamics, sea level variability, glider data integration, and wave-current interactions, primarily in the Pacific Northwest and Bering Sea regions. The work demonstrates consistent application of advanced modeling frameworks to real-world oceanographic problems. Alexander Kurapov has collaborated extensively with leading oceanographers at Oregon State University and beyond, contributing to major projects such as the US Integrated Ocean Observing System (IOOS). While no formal awards are listed, his body of work reflects significant contributions to coastal ocean science. He has advised or collaborated with numerous researchers, though specific students are not named. His work often involves model development, observational integration, and participation in multi-institutional efforts. Kurapov’s research is supported through collaborative grants and institutional resources, though specific funding sources are not detailed in the text. His work is closely tied to modeling teams at Oregon State University, particularly those involved in coastal ocean forecasting, data assimilation, and nearshore dynamics. He contributes to systems like the West Coast Ocean Forecast System (WCOFS) and participates in regional observational-modeling initiatives.

• Statistical Problems in Marketing
• Functional Data Analysis
• Statistical Methodology
• +۲ مورد دیگر

Gareth James is the John H. Harland Dean and Professor of Information Systems & Operations Management at Emory University's Goizueta Business School, a position he assumed in July 2022. Prior to this, he held significant leadership roles at USC Marshall School of Business, including interim dean (2019-2020), vice dean of faculty, and deputy dean (2020-2022). James received his PhD in Statistics from Stanford University, complemented by a BComm in Finance and BS in Statistics from The University of Auckland. His academic journey reflects a strong foundation in both statistical methodology and business applications. James specializes in statistical problems in marketing, functional data analysis, statistical methodology, and high-dimensional regression. His research bridges theoretical statistics with practical business applications, particularly in the areas of machine learning, advertising optimization, and technology adoption. His work demonstrates a consistent focus on developing methodological innovations that address real-world business challenges. His research contributions have been widely recognized, with over 30,000 citations. James has led multiple National Science Foundation research grants and served as associate editor for five top research journals. His most notable scholarly contribution is co-authoring the highly successful textbook "An Introduction to Statistical Learning," which has become a standard reference in the field. Fellow of the American Statistical Association Fellow of the Institute of Mathematical Statistics Dean's Research Awards (two times) Evan C. Thompson Faculty Teaching and Learning Innovation Award Three-time winner of the Marshall School of Business' Golden Apple Award Dean's Ph.D. Advising Award USC Mellon Award Provost's Mentoring Award James is equally distinguished as a mentor and educator. His teaching excellence is evidenced by multiple Golden Apple Awards, while his mentoring impact is reflected in the Dean's Ph.D. Advising, USC Mellon, Evan C. Thompson, and Provost's Mentoring awards. As Dean, he leverages his expertise in data-informed decision making to strengthen Goizueta's mission of preparing principled leaders to have a positive influence on business and society.

• Physical Education
• Sports Science
• Physical Activity Monitoring
• +۳ مورد دیگر

Jesús Viciana Ramírez serves as a University Professor in the Department of Physical Education and Sports at the Faculty of Sports Sciences, University of Granada. His academic work centers on innovative physical education methodologies and technology integration for youth activity promotion. His teaching schedule includes consistent office hours across semesters in Building D - Office 4.3. Research interests focus on physical activity monitoring using wearable technology, gamified teaching models in physical education, and environmental influences on student engagement. His work bridges sports science with educational technology through rigorous validation studies and cluster-randomized trials. Analysis of recent publications reveals dominant trends in Wearable device validation for adolescent activity tracking Intermittent teaching units combining gamification and technology Cross-cultural fitness assessment frameworks with strong emphasis on objective measurement through accelerometers and real-world school implementation. His leadership in the School-Fit and Fit-Person studies demonstrates commitment to evidence-based physical education practices. Current research explores psychological mediators of activity interventions and environmental knowledge assessment through tools like CENAFI.

• Climate Dynamics
• Numerical Weather Prediction (NWP)
• Atmospheric Modeling
• +۳ مورد دیگر

Professor Eigil Kaas is affiliated with the Niels Bohr Institute at the University of Copenhagen . His work spans climate dynamics , numerical weather prediction (NWP) , and atmospheric modeling . As former Section Head of Climate and Computational Geophysics , he leads research on climate-chemistry coupling and sea ice impacts. Education : MSc (1987) and PhD (1993) in Meteorology from University of Copenhagen Research Focus : Climate dynamics and physics Numerical methods in atmospheric models Machine learning for weather prediction Arctic sea ice-climate interactions Thunderstorm electricity and radiation Coupled atmosphere-ocean modeling Article Trends : Recent work combines neural networks with radiative transfer optimization Focus on storm dynamics and gamma-ray flashes Extreme precipitation modeling under climate change Pioneering tidal flow studies in Faroe Island fjords Teaching Legacy : Instructor of Atmospheric Physics and Dynamical Meteorology courses Developed zonally averaged climate model for educational use Mentored 12 PhD/MSc students with DMI/ECMWF collaborations Professional Roles : Chairman of BFI Group 28 (Geosciences & Climate) Scientific Advisory Committee member at ECMWF Project lead in EU ENSEMBLES and PEGASOS initiatives

F. Donelson (Don) Smithمشاهده پروفایل

استاد پژوهشی

• Computer Networking
• Operating Systems
• Distributed Systems
• +۳ مورد دیگر

F. Donelson (Don) Smith is a Research Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill . He holds a Ph.D. in Computer Science (1978) from UNC-Chapel Hill, with prior degrees in Chemistry (1962) and Industrial Management (1964) from the University of Tennessee. Key research areas: Computer networking, multimedia systems, distributed systems Collaboration with: Kevin Jeffay , Jasleen Kaur , and the DiRT Lab Notable contributions include: Co-inventor of U.S. Patents 7,444,720 (2008) and 5,892,754 (1999) Key roles at IBM (1965-1997) in network architecture , protocol development , and multimedia networking Active in professional service: Program Chair, TriComm '91 Co-chair, ACM CSCW '94