جست‌وجوی استاد و پژوهشگر

Marc Paolellaمشاهده پروفایل

استاد

• Financial Econometrics
• Time Series Analysis
• Portfolio Optimization
• +۴ مورد دیگر

Marc Paolella is a Full Professor of Empirical Finance at the University of Zurich's Department of Finance. His academic journey includes roles as Associate Professor (2003–2006) and Assistant Professor (1999–2003) at Kiel University and visiting positions at the University of Geneva. He holds a Dr. sc. pol. (1998) and Habilitation (2002) from Kiel University, alongside degrees from SUNY Stony Brook and Colorado State University. His research focuses on financial econometrics, emphasizing portfolio optimization, risk prediction, and saddlepoint approximation theory. He has authored four textbooks, including works on probability theory, statistical inference, and GARCH models. Over 50 journal articles span leading venues like the Journal of Econometrics and Journal of Financial Econometrics. Paolella's contributions include developing methods like CHICAGO for portfolio risk calculation and the COMFORT model for non-Gaussian returns. He serves as Editor-in-Chief of the journal Econometrics and holds editorial roles at multiple journals. Awards include the Elected Fellowship at the IETI and recognition for impactful research. His teaching spans advanced courses in financial econometrics, probability theory, and mathematical finance. He has supervised numerous theses and leads the Quantitative Finance program at the Science ETH UZH. Research grants include Swiss National Science Foundation funding for portfolio optimization under non-elliptical distributions.

Jürgen Bernardمشاهده پروفایل

استادیار

• Visual Analytics
• Information Visualization
• Interactive Machine Learning
• +۶ مورد دیگر

Jürgen Bernard is an Assistant Professor of Computer Science at the University of Zurich (UZH), affiliated with the Digital Society Initiative (DSI). He leads the Interactive Visual Data Analysis (IVDA) Group and holds a joint position in the Department of Informatics within the Faculty of Business, Economics, and Informatics. His research focuses on interactive visual data analysis, explainable machine learning, and human-centered AI interfaces. Bernard completed his PhD at TU Darmstadt in 2015, followed by postdoctoral roles at TU Darmstadt and the University of British Columbia. He has received prestigious awards, including the EuroGraphics Young Researcher Award (2022) and EuroVis Young Researcher Award (2021). His work emphasizes combining human expertise with algorithms in domains like healthcare, climate science, and digital humanities. Key research interests include visual analytics for time-oriented data, interactive machine learning, and applications in healthcare. His projects address challenges such as medical data interpretation, sensor data analysis, and decision-making support systems. Bernard actively contributes to conferences like IEEE VIS and chairs workshops such as VAHC 2023. Education: PhD in Computer Science (2015, TU Darmstadt); Diploma in Computer Science (2009, TU Darmstadt) Grants: SNF Grant on Personalized Visual Analytics (2024), BMW collaboration on manufacturing analytics Labs/Teams: IVDA Group, DSI Health Community

• 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.

• Nuclear Materials
• Radiation Damage Physics
• Computational Materials Science
• +۴ مورد دیگر

Pär Olsson is a Professor in the Department of Nuclear Science & Engineering at KTH Royal Institute of Technology. His research focuses on computational and experimental studies of radiation damage in nuclear materials, with particular emphasis on understanding defect dynamics, microstructural evolution under irradiation, and the behavior of advanced nuclear fuels. He leads courses such as Multiscale Modeling of Nuclear Materials and Radiation Damage Physics, emphasizing both theoretical and practical aspects of materials science in nuclear contexts. His research interests include the development of advanced accident-tolerant fuels (e.g., UN-UO2 composites), the computational modeling of radiation effects in metals like Fe and W, and the interplay between solute atoms and defects in irradiated materials. His work combines first-principles calculations, kinetic Monte Carlo simulations, and experimental validation to address challenges in nuclear energy systems. Notable contributions include studies on fission product solubility in nuclear fuels, oxygen’s role in tungsten defect evolution, and the thermal performance of UN-based composites. His team’s projects, such as the M4F initiative (Multiscale Modelling for Fusion and Fission Materials), aim to bridge atomistic and continuum-scale models for material design. Pär Olsson collaborates extensively with international institutions and contributes to nuclear materials education through course coordination and supervision of graduate studies in physics and materials science.

Jacob Bernsteinمشاهده پروفایل

استاد

• Geometric Analysis
• Differential Geometry
• Minimal Surface Theory
• +۳ مورد دیگر

Jacob Bernstein is a Professor and Vice-Chair in the Department of Mathematics at Johns Hopkins University (JHU), part of the Krieger School of Arts & Sciences. He holds a PhD from MIT (2009) under Tobias Colding. His research focuses on geometric analysis, particularly minimal surfaces and mean curvature flow. He co-organizes the Analysis and PDE Seminar at JHU and the Metro Area Differential Geometry Seminar with the University of Maryland and Howard University. **Education**: PhD in Mathematics, MIT (2009). **Research Interests**: Geometric analysis, minimal surface theory, mean curvature flow, and their applications in differential geometry and PDEs. His work explores topics like entropy, geometric flows, and singularities in minimal surfaces. **Teaching**: Taught courses including Real Analysis, Multivariable Calculus, Riemannian Geometry, and graduate-level Real Analysis. **Affiliations**: Active in academic leadership roles at JHU and collaborates widely with institutions like UMD and Howard. His work bridges theoretical mathematics with applications in geometry and analysis.

• Artificial Intelligence
• Machine Learning
• Data Mining
• +۵ مورد دیگر

Dr. Milos Hauskrecht is a Professor of Computer Science at the University of Pittsburgh's School of Computing and Information. He holds a PhD from MIT (1997) and an M.Sc. from Slovak Technical University (1988). His primary research focuses on Artificial Intelligence, Machine Learning, and their applications in healthcare, finance, and biomedical informatics. He leads interdisciplinary projects in clinical monitoring, anomaly detection, and predictive modeling of electronic health records (EHRs). Education: PhD in Electrical Engineering and Computer Science (MIT, 1997), M.Sc. in Electrical Engineering (Slovak Technical University, 1988) Affiliations: Department of Computer Science, University of Pittsburgh; School of Computing and Information His research integrates AI with probability theory, statistics, and operations research. Key areas include planning under uncertainty, machine learning for time-series data, and AI-driven solutions for clinical decision support. Current projects involve real-time patient monitoring, hierarchical models for EHR analysis, and control of biological processes. He has advised over 20 PhD students and holds grants from NIH, DARPA, and other agencies. Notable contributions include outlier detection in clinical actions, temporal predictive patterns, and state-space models for healthcare data. His work emphasizes translating AI advancements into practical clinical tools for improved patient care.

Ciarán Hanleyمشاهده پروفایل

مدرس

• Structural Engineering
• Bridge Design and Assessment
• Infrastructure Management
• +۵ مورد دیگر

Dr. Ciarán Hanley is a Lecturer in Structural Engineering at University College Cork (UCC), specialized in bridge and infrastructure systems. He holds a PhD in Civil Engineering from UCC (2017), following a BEng (Ord) and BE (Hons) in Civil Engineering (2010–2012). His research focuses on performance-based design, structural safety, and sustainable infrastructure, with contributions to bridge management systems and life-cycle assessment. He serves as a technical reviewer for journals like Structure and Infrastructure Engineering and ICE - Bridge Engineering , and is a board member of the Civil Engineering Research Association of Ireland. Education: BEng (Ord) Civil Engineering, UCC, 2010 BE (Hons) Civil Engineering, UCC, 2012 PhD Civil Engineering, UCC, 2017 Professional Memberships: Institution of Structural Engineers (IStructE) International Association of Bridge and Structural Engineering (IABSE) Fédération Internationale du Béton (FIB) International Association of Shell and Spatial Structures (IASS) His research interests emphasize probabilistic design, structural reliability, and resilience of infrastructure. Key themes include multivariate analysis of bridge networks and the integration of sustainability into infrastructure management. He has contributed to EU projects like TU1406 and serves as Rapporteur for EuroStruct. His publications span over a dozen peer-reviewed articles in journals like Journal of Structural Integrity and Maintenance and Proceedings of the ICE . Dr. Hanley’s teaching includes courses on structural mechanics, prestressed concrete, and design studios. He was a finalist for Engineers Ireland Chartered Engineer of the Year (2019) and actively engages in consultancy for bridge and marine structure design.

Ruitao Linمشاهده پروفایل

استادیار

• Bayesian adaptive design
• Robust Bayesian methods
• Meta-analytic trial design
• +۶ مورد دیگر

Dr. Ruitao Lin is an Assistant Professor in the Department of Biostatistics at The University of Texas MD Anderson Cancer Center and an Adjunct Assistant Professor at Rice University. He holds a PhD in Biostatistics from The University of Hong Kong (2012–2016) and completed postdoctoral training at the University of Washington and MD Anderson. His research focuses on Bayesian adaptive designs, robust statistical methods, and clinical trial methodologies, particularly in oncology and precision medicine. He leads the development of novel Bayesian approaches for dose-finding in phase I/II trials, meta-analytic trial designs, and high-dimensional data analysis. Dr. Lin is an Associate Editor for Contemporary Clinical Trials , Biometrical Journal , and Pharmaceutical Statistics , and has contributed to software tools like the BOIN design suite and TITE-BOIN12. His work bridges statistical innovation with practical clinical challenges, including late-onset toxicities in immunotherapy and heterogeneous treatment effects. He has secured NIH funding (e.g., R01CA261978) and collaborated with academic and industry partners to advance trial design and analysis. His software platforms, including R packages and Shiny apps, enable clinicians to implement cutting-edge statistical methods in real-world settings. Education : PhD, Biostatistics, The University of Hong Kong (2016); Postdocs at University of Washington (2016–2017) and MD Anderson (2017–2019). Grants : NIH/NCI R01CA261978 (2021–2025), focusing on Bayesian methods for precision oncology trials. Teaching : Teaches clinical trial design courses at Rice University and UTHealth. Labs/Software : Developed the BOIN design suite, TITE-BOIN12, and other tools for dose-finding and phase I/II trials.

Bertram F. Malleمشاهده پروفایل

استاد

• Moral Psychology
• Social Cognition
• Human-Machine Interaction
• +۳ مورد دیگر

Bertram F. Malle is a Professor of Cognitive and Psychological Sciences at Brown University, holding a joint appointment in the Department of Cognitive and Psychological Sciences. He is affiliated with the Humanity-Centered Robotics Initiative and has collaborated with institutions like the Army Research Laboratory and the Office of Naval Research. His academic journey includes a Master’s in Philosophy/Linguistics (1987) and Psychology (1989) from the University of Graz, Austria, followed by a Ph.D. in Psychology from Stanford University (1995). Before joining Brown in 2008, he was at the University of Oregon. His research focuses on moral psychology, social cognition, and human-robot interaction. Key interests include moral judgments, blame attribution, social norms, and the cognitive foundations of human-machine collaboration. He has been funded by NSF, DARPA, and the Department of Defense, among others. Malle’s work bridges psychology, philosophy, and AI, emphasizing moral competence in robots and the societal implications of human-robot interaction. His awards include the SESP Outstanding Dissertation Award (1995), NSF CAREER Award, and the 2019 SESP Scientific Impact Award. He is also a Fellow of multiple prestigious societies, including APS and SPSP. His teaching spans courses like Social Psychology, Moral Psychology, and Multivariate Statistics. Collaborators include experts in computer science and robotics, reflecting his interdisciplinary approach to advancing human-centric AI systems.

• Food Engineering
• Food Packaging
• Food Process Engineering
• +۴ مورد دیگر

Professor Keshavan Niranjan is a faculty member at the University of Reading, serving as Director of the Global Engagement Office. His academic roles include leading international academic programs in teaching and research. He holds a BChem Eng, MChem Eng, and a PhD (tech), and is a Fellow of the Institute of Food Science and Technology (FIFST) and the International Academy of Food Science and Technology. His research focuses on food engineering, particularly in foam stability, sustainable food packaging, high-pressure food processing, and enzyme-assisted extraction. Notable projects include developing plant-based food systems, antimicrobial coatings, and reducing acrylamide in deep-fried products. He supervises PhD projects on topics like date fruit resource recovery and enzymatic protein modification for food processing. Professor Niranjan has authored numerous publications and book chapters, including contributions to Journal of Food Engineering and Food Hydrocolloids . His editorial roles include Editor-in-Chief of Foods and roles at Food and Bioproducts Processing and Scientific Reports . Awards include a Lifetime Achievement Award (2015) and Distinguished Service Award (2019) from the International Association of Engineering and Food.

Catherine Wolframمشاهده پروفایل

استادیار

• Complex Analysis
• Probability Theory
• Geometry
• +۳ مورد دیگر

Catherine Wolfram is a Gibbs Assistant Professor at Yale University and a National Science Foundation (NSF) postdoctoral fellow. She holds a PhD in Mathematics from MIT (2024), advised by Scott Sheffield, and an undergraduate degree from the University of Chicago. Her research focuses on complex analysis, probability, and geometry, with applications to statistical mechanics and random surfaces. She has presented her work at institutions including the University of Michigan, Columbia University, and international conferences such as the World Congress on Probability and Statistics. Her recent activities include talks on dimer models, holography in mathematical physics, and Teichmüller theory. Catherine has also engaged in teaching roles at MIT, leading recitations in probability and multivariable calculus. Her research has been supported by NSF postdoctoral funding, and her work has been published in journals like International Mathematics Research Notices (IMRN). She actively collaborates with researchers in probability, geometry, and mathematical physics, evidenced by her co-authored papers and participation in workshops at IHES, CIRM, and the Fields Institute.

Elli Anastasiadiمشاهده پروفایل

استادیار

• Formal Verification
• Concurrency Theory
• Parallel Programs
• +۷ مورد دیگر

Elli Anastasiadi is an Assistant Professor in the Department of Computer Science at Aalborg University, part of the Technical Faculty of IT and Design. She is a member of the DEIS (Distributed, Embedded and Intelligent Systems) research group, which focuses on formal methods, verification, and intelligent systems. Prior to her current role, she was a postdoctoral researcher at Uppsala University and completed her PhD at Reykjavik University. Education: PhD in Computer Science, Reykjavik University (2022) Master’s in Applied Mathematics and Computer Science, NTUA, Greece Her research centers on formal verification of concurrent and parallel systems , with emphasis on runtime verification, process algebra, and logical foundations. She works extensively with hyperproperties, modal logic, and equational reasoning. Her work bridges theoretical computer science with practical verification tools. Recent publications show a strong trend in logic-based verification , particularly in modal and temporal logics, recursion, and monitor synthesis. Her work often involves complexity analysis and axiomatization of logical systems. Scientific Awards: PhD grant from Reykjavik University research fund She has advised no publicly listed students yet and is actively involved in academic service, including co-organizing workshops and being an invited speaker. She collaborates closely with leading researchers in concurrency theory and formal methods. Labs and Teams: Member of the DEIS research group at Aalborg University, contributing to projects on verification, distributed systems, and intelligent decision-making.

• Decision Analysis
• Health Economics
• Global Health
• +۳ مورد دیگر

Dr. Abigail Colson is a Senior Lecturer in the Department of Management Science at Strathclyde Business School, University of Strathclyde. She specializes in decision and uncertainty analysis with a focus on public health, including expert judgment elicitation methods. Her work addresses global health challenges such as antimicrobial resistance (AMR) and health evaluation in low-resource settings. She holds a PhD in Management Science from the University of Strathclyde, an MPP from the University of Chicago, and a BA in political science and environmental studies from American University. Her research integrates structured expert judgment techniques to inform policy decisions, particularly in cost-effectiveness analysis, benefit-cost prioritization, and health technology assessment. Recent projects include quantifying future AMR trends, evaluating child mental health interventions, and designing antibiotic financing models. She collaborates with international organizations and governments to strengthen healthcare systems in developing countries. Key areas: AMR forecasting, global health economics, expert elicitation protocols Notable projects: EFSA EKE Training, Credible Routes to GB Electricity Collapse Study Professional roles: Principal Investigator on multiple grants, Resident Scholar at Center for Disease Dynamics Dr. Colson’s publications emphasize methodological innovations in decision-making frameworks and their application to pressing global health issues. She develops training programs for structured expert judgment and advocates for evidence-based policy across diverse sectors.

• Construction Engineering
• Simulation Science
• Information Technology in Construction
• +۳ مورد دیگر

Simaan Abourizk, PhD, PEng, is the Dean of the Faculty of Engineering at the University of Alberta and holds the rank of Professor in Construction Engineering and Management. He also served as the NSERC/Alberta Construction Industry Research Chair (1997–2011) and Canada Research Chair in Operations Simulation (2001–2008). His roles include Executive Board membership at the Construction Research Institute of Canada. Education: Doctor of Philosophy in Construction Engineering and Management from Purdue University (1990), Master of Science and Bachelor of Civil Engineering (Honors) from Georgia Institute of Technology (1985 and 1984). Research focuses on advancing simulation technologies for construction and natural resource industries, including: Development of the Simphony simulation environment and COSYE framework Integration of AI, visualization, and scheduling tools (e.g., SmartEst, MTRACK) Optimization of tunneling, modular assembly, and industrial fabrication processes Key awards include the E. Whitman Wright Award (2002), E.W.R. Steacie Memorial Fellowship (2001), and Walter Shanly Award (2001). Current projects emphasize synthetic environments, safety analytics, and data-driven decision support systems in construction. He leads initiatives on risk simulation, resource allocation, and industrial automation.

• Digital Twins
• Smart Cities
• Blockchain Technology
• +۵ مورد دیگر

Noel Crespi is a Professor and Director of Studies at Telecom SudParis, part of Institut Polytechnique de Paris. He leads research in the NeSS group and is affiliated with SAMOVAR, a prominent research laboratory focusing on networks, systems, and services. His work spans multiple domains in telecommunications, networking, and smart systems. His primary research interests include digital twins for smart cities, blockchain technologies, Internet of Things (IoT) security and applications, 5G/6G networking, and machine learning applications in network management. He has published extensively on these topics, with over 100 publications in top-tier journals and conferences. His recent work shows a strong focus on digital twin applications for urban management, particularly in traffic and air quality monitoring. He has developed modular frameworks for smart city digital twins that integrate real-time data from multiple sources. His research also explores blockchain applications for network security, access control, and service provisioning in next-generation cellular networks. Dr. Crespi has received significant recognition for his work on digital twins, with his 2020 paper "Digital twin in the IoT context" in Proceedings of the IEEE being highly cited. His current research explores the integration of AI with digital twin technologies for sustainable urban development. He has supervised numerous PhD students and collaborates extensively with researchers across Europe and internationally. His work often involves interdisciplinary approaches, bringing together computer science, networking, urban planning, and environmental science. Dr. Crespi has been instrumental in developing frameworks for network digital twins, with applications in traffic management, air quality monitoring, and resource allocation in smart cities. His research demonstrates practical implementations in cities like Madrid, showing measurable improvements in urban management.