جست‌وجوی استاد و پژوهشگر

Mei-Ling Ting Leeمشاهده پروفایل

استاد

• Time-to-event data modeling
• Genomic data analysis
• Statistical distribution theory
• +۳ مورد دیگر

Dr. Mei-Ling Ting Lee is a Professor in the Department of Epidemiology and Biostatistics at the University of Maryland, College Park. She specializes in developing statistical models, notably the first hitting-time based threshold regression (TR) for analyzing time-to-event survival data, which has been extended to machine learning applications. As the Founding Editor and Editor-in-Chief of the Lifetime Data Analysis journal, she has significantly contributed to the field of time-to-event data methodologies. Her research encompasses genomic data analysis, statistical distribution theory, nonparametric methods, and applications in epidemiology. Dr. Lee has authored over 150 peer-reviewed articles and a seminal monograph, Analysis of Microarray Gene Expression Data (2004), widely used in genomic research. She has also co-edited influential books, including Lifetime Data Models in Reliability and Survival Analysis (1995) and Risk Assessment and Evaluation of Prediction (2013). Education: BS in Mathematics (National Taiwan University), MS (National Tsing Hua University), MA and PhD in Mathematics/Statistics (University of Pittsburgh). Her work focuses on integrating statistical theory with practical applications, including clinical trials, genomic studies, and public health research. She leads initiatives in statistical software development (e.g., R packages like clusrank ) and advocates for rigorous methodological standards in survival analysis.

Michelle Hoda Wilkersonمشاهده پروفایل

پژوهشگر

• Computational Literacy
• Scientific Computing
• Visual Data Analysis
• +۱۲ مورد دیگر

Michelle Hoda Wilkerson is a learning scientist at the University of California, Berkeley, affiliated with the Berkeley School of Education. She directs the Computing, Reasoning, and Expression (CoRE) Lab, focusing on computational literacy and the integration of scientific computing tools into precollegiate curricula. Her research emphasizes visual data analysis, agent-based simulations, and their social implications in domains like climate and health. Her scholarly contributions appear in journals such as Educational Researcher , Journal of the Learning Sciences , and Science Education . Notable awards include the National Science Foundation Early CAREER Award (2014) and the AERA Division C Jan Hawkins Award (2020). She co-organized the National Academies Workshop on K-12 Data Science Education (2022). Her research highlights the interplay between computational tools, data reasoning, and socio-cultural contexts, advocating for inclusive, humanistic approaches to data science education. Key themes include equity in technology access, teacher education, and leveraging personal experiences in learning environments. NSF Early CAREER Award (2014) AERA Jan Hawkins Award (2020)

Youssef Marzoukمشاهده پروفایل

استاد

• Uncertainty Quantification
• Bayesian Computation
• Inverse Problems
• +۴ مورد دیگر

Youssef Marzouk is a Professor of Aeronautics and Astronautics at MIT, serving as co-director of the MIT Center for Computational Engineering and director of the Aerospace Computational Design Laboratory. His research focuses on integrating physical modeling with statistical inference, emphasizing Bayesian computation, uncertainty quantification, and optimal experimental design. He holds a SB, SM, and PhD from MIT and has been recognized with prestigious awards including the DOE Early Career Award and the Junior Bose Teaching Prize. Education: PhD in Aeronautics and Astronautics, MIT SM in Aeronautics and Astronautics, MIT SB in Aeronautics and Astronautics, MIT Research Interests: Uncertainty Quantification techniques for complex systems Bayesian computational methods and inverse problem solutions Optimal experimental design strategies Interdisciplinary applications in geophysics, environmental science, and engineering Awards: 2022: Report to the President, Center for Computational Science and Engineering 2021: Bayesian Inference Software Framework (hIPPYlib-MUQ) 2012: MIT School of Engineering Junior Bose Award 2010: DOE Early Career Research Award Labs & Leadership: Aerospace Computational Design Laboratory (Director) MIT Center for Computational Engineering (Co-Director) Editorial Board roles: SIAM Journal on Scientific Computing, Advances in Computational Mathematics

Andrew D. Lewisمشاهده پروفایل

استاد

• Geometric Control Theory
• Global Analysis
• Geometric Mechanics
• +۳ مورد دیگر

Andrew D. Lewis is a Professor and Associate Head of the Department of Mathematics & Statistics at Queen's University, Kingston, Canada. His research focuses on geometric control theory, global analysis, and geometric mechanics, with applications to mechanical systems and dynamical systems. He holds a Ph.D. from Caltech, along with M.Sc. and B.Sc. degrees from Caltech and the University of New Brunswick, respectively. His research explores the intersection of geometric methods, topology, and algebra in solving structural problems in control theory and mechanics. He actively mentors graduate students and emphasizes mathematical rigor combined with applied perspectives. Lewis teaches advanced courses in control theory, differential equations, and geometric mechanics, and has developed extensive lecture notes and software tools for academic use. He has organized numerous research events, including the CRM Trimester on Control Geometry and Engineering and the Meeting on Nonlinear Control Theory and its Applications. His work spans theoretical contributions to control systems, geometric mechanics, and applied mathematics, with a focus on controllability, stabilization, and system dynamics. Education: Ph.D., California Institute of Technology M.Sc., California Institute of Technology B.Sc., University of New Brunswick Awards/Honors: None explicitly mentioned in the provided texts. Grants/Advising: Supervised numerous graduate students and postdoctoral researchers, fostering interdisciplinary work in control theory and mechanics.

• Augmented Reality
• Virtual Reality
• Mixed Reality
• +۶ مورد دیگر

Abey Campbell is an Assistant Professor in Computer Science at the School of Computer Science, University College Dublin. He holds roles such as Deputy Programme Director for Computer Science, Director of UCD VR Lab, and 1st Year Stage Coordinator. His research focuses on Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), and Multi-Agent Systems with applications in education, healthcare, and human-computer interaction. Campbell has coordinated modules like Augmented and Virtual Reality, Computer Graphics, Game Development, and Mobile Computing. He earned his BSc and PhD in Computer Science from University College Dublin. His work explores touchless interaction technologies, machine learning agents in STEM education, and ethical implications of emerging technologies. Notable contributions include RenderKernel for real-time rendering systems and studies on AR's role in decision support systems. Campbell has secured a grant from Enterprise Ireland for collaborative design documentation and participates in professional activities like peer reviewing for Frontiers in Virtual Reality and IEEE conferences. His collaborative projects include developing AR tools for veterinary training and evaluating immersive VR experiences in nursing education. The UCD VR Lab under his direction focuses on applied research in spatial computing and interactive systems.

Johes Baterمشاهده پروفایل

استادیار

• privacy-preserving analytics
• federated databases
• differential privacy
• +۶ مورد دیگر

Johes Bater is an Assistant Professor of Computer Science at Tufts University's School of Engineering. He joined Tufts in 2022 after postdoctoral research at Duke University's Database Group and a Ph.D. in Computer Science at Northwestern University. Education B.Sc. in Electrical Engineering (2011) from Stanford University M.Sc. in Electrical Engineering; Computer Systems (2013) from Stanford University Ph.D. in Computer Science (2020) from Northwestern University Research Focus Bater's research focuses on privacy-preserving analytics , balancing security , privacy , and utility in trustworthy database systems . His work spans differential privacy , secure computation , and data federation to enable robust distributed analytics with provable guarantees. Publications & Trends His publications since 2016 emphasize secure multi-party computation (SMCQL, 2016), differentially private indexing (Longshot, 2023), and privacy-utility trade-offs in federated databases. Key subfields include private data sharing , access pattern security , and incremental computation for outsourced systems. Awards & Grants 2022: Cisco Systems grant for "A Usable and Shareable Tool for Software Threat Modeling" Teaching & Service Bater teaches courses like Database Systems , Dissertation Research , and Special Topics in Data Infrastructure . He served on Tufts' CS PhD Admissions Committee (2022) and as a reviewer for the ACM Conference on Computer and Communications Security (2022).

• Finance
• Economics
• Pension Systems
• +۷ مورد دیگر

Jean-Daniel Guigou is an Associate Professor at the University of Luxembourg, affiliated with the Faculty of Law, Economics and Finance and the Department of Finance. His research focuses on pension systems, financial modeling, bankruptcy law, and corporate governance. He has published extensively on topics including trajectory modeling, strategic delegation, and the economic implications of regulatory frameworks such as IFRS 9. His work often integrates statistical methodologies like finite mixture models to analyze economic phenomena. Key themes in his research include the optimal design of pension systems, the dynamics of managerial collusion under asymmetric incentives, and the impact of legal frameworks on financial markets. He has contributed to policy-relevant studies, such as analyses of Luxembourg's mixed pension system and the role of corporate governance in financial development. Guigou’s publications reflect a blend of theoretical and applied economics, with notable contributions to understanding strategic behavior in competitive markets, the robustness of econometric models, and the interplay between law and financial systems. His research bridges academic rigor with practical applications in public policy and financial regulation.

Cory Simonمشاهده پروفایل

دانشیار

• Machine Learning
• Bayesian Optimization
• Computational Materials Science
• +۳ مورد دیگر

Cory Simon serves as Associate Professor in the Department of Chemical, Biological, and Environmental Engineering within Oregon State University's College of Engineering. His research integrates machine learning, optimization, and chemical engineering to advance materials discovery and environmental sensing systems. His academic foundation includes a Ph.D. in Chemical Engineering from the University of California, Berkeley and a B.S. in Chemical Engineering from The University of Akron. Simon's work centers on Bayesian methodologies for scientific challenges, featuring: Bayesian optimization for adaptive materials synthesis Statistical inversion of physical systems with uncertainty quantification Computational design of nanoporous sensor arrays Stochastic algorithms for robotic environmental monitoring Recent publications demonstrate accelerating focus on multi-fidelity optimization for molecular design and atmospheric water harvesting, bridging chemical engineering with computational science through data-driven approaches. Leading The Simon Ensemble research group, Simon champions a versatile 'buffet-style' research philosophy—drawing from mathematics, statistical mechanics, and machine learning to address interdisciplinary problems across chemistry, materials science, and environmental engineering.

Albert Ganمشاهده پروفایل

استاد

• Transportation Engineering
• Highway Safety
• Traffic Simulation
• +۵ مورد دیگر

Dr. Albert Gan is a Professor in the Department of Civil and Environmental Engineering at Florida International University (FIU), affiliated with the College of Engineering and Computing. He holds a Ph.D. from the University of Florida (1996). His research focuses on transportation engineering, emphasizing highway safety, traffic simulation, intelligent transportation systems (ITS), GIS applications, transit planning, and data-driven decision-making. He has developed over 20 transportation software systems, including the Florida Transit Information System (FTIS), and secured over $19M in research funding as PI/Co-PI. Dr. Gan teaches courses like Transportation and Traffic Engineering and has advised 18 Ph.D. and 40+ M.S. students. Research Interests: Highway safety analysis and crash prediction ITS applications for real-time traffic management Data integration and visualization tools for transportation systems GIS-based transportation modeling Transit planning and service optimization Freeway operations and ramp metering strategies Awards & Mentoring: Recipient of FIU’s inaugural Dean’s Doctoral Mentorship Award. His students have won multiple Best ITE Student Paper Awards (2000, 2004, 2005). The FIU ITE Student Chapter, under his advisement, was named International Chapter of the Year five times (2001, 2004, 2005, 2007, 2008). Key Contributions: Authored/co-authored over 230 refereed papers and technical reports. Key projects include Safety Analyst implementation in Florida, evaluation of cable median barriers, and development of crash modification factor (CMF) methodologies. Active in transportation data standardization and public involvement strategies for infrastructure projects. Labs & Collaborations: Leads research at the Lehman Center for Transportation Research. Collaborates closely with Florida Department of Transportation (FDOT) and other state agencies on safety and ITS initiatives.

• Applied Statistics
• Optimization
• Data Visualization
• +۷ مورد دیگر

Zhongyuan (Annie) Yu is a Teaching Associate Professor in the Department of Systems and Enterprises at Stevens Institute of Technology. She holds a PhD in Systems Engineering (2014), and two MS degrees in Operations Research (2012) and Industrial Engineering (2010), both from Georgia Institute of Technology. Her research bridges applied statistics, optimization, data visualization, and socio-economic systems analysis. Key focus areas include healthcare systems engineering, defense acquisitions, and interactive decision support systems. She leads software engineering education initiatives, including serving as Program Director for the Software Engineering Program (2022-2024). Yu has secured major grants from DoD DASD(SE) and NIH, focusing on mega-project management, digital engineering integration, and healthcare policy simulations. Her 2023-2024 research explores HIPAA compliance challenges in software engineering and patient trust in electronic health records. Her publications span health informatics, portfolio optimization networks, and systems engineering methodology. Notable works include developing policy flight simulators for healthcare interventions and semantic integration frameworks for digital engineering interoperability. Teaching responsibilities include courses like Agile Methods for Software Development, Data Analysis & Visualization, and Engineering Economics. She advises capstone projects and maintains active roles in curriculum development for systems and software engineering programs.

Lane Harrisonمشاهده پروفایل

دانشیار

• Information Visualization
• Visual Analytics
• Human-Computer Interaction
• +۳ مورد دیگر

Lane Harrison is an Associate Professor in the Department of Computer Science at Worcester Polytechnic Institute (WPI), where he directs the Visualization and Information Equity lab (VIEW). His research leverages cognitive and perceptual principles to improve information visualization and visual analytics systems, with critical applications in cybersecurity and health-risk communication for high-stakes decision-making. His educational background includes a BS (2009) and PhD (2013) in Computer Science from the University of North Carolina, Charlotte. Prior to WPI, he was a Postdoctoral Researcher at Tufts University's Visual Analytics Lab. Harrison's research focuses on empirical evaluation of visualization techniques , investigating how cognitive principles can optimize user performance with visual representations. He develops design guidelines for effective visualizations in domains like cybersecurity and healthcare, while creating adaptive systems that integrate models of user abilities. His work bridges theoretical foundations with practical applications to address real-world challenges in data interpretation. Analysis of his 2016-2021 publications reveals consistent emphasis on user-centered evaluation methodologies , including crowdsourcing and controlled experiments. Key trends include quantifying exploration behaviors in web visualizations, addressing cognitive biases in data reproduction, and developing healthcare-focused analytics for drug interactions and risk communication. His research demonstrates strong interdisciplinary connections between visualization, cognitive science, and domain-specific applications. His scientific recognition includes: Best Paper Award at ACM CHI 2016 for adaptive interface research Harrison secures significant research funding including an NSF Grant (2022) for visualization studies and participates in an 11-school AI collaboration for intelligence professionals (2025). He teaches data visualization and web programming courses, mentoring students through the VIEW lab on projects applying visualization techniques to social issues and scientific domains. He directs the VIEW lab at WPI, which develops computational methods to understand how people engage with data visualizations while emphasizing equitable information access. Current projects integrate user modeling with visualization systems to optimize design for diverse cognitive abilities and application contexts.

Pedro Duarte Silvaمشاهده پروفایل

دانشیار

• Statistical Modeling
• Discriminant Analysis
• Interval Data Analysis
• +۱ مورد دیگر

Pedro Duarte Silva is an Associate Professor at Católica Porto Business School, Universidade Católica Portuguesa. His research focuses on statistical methods for distributional and interval data, developing parametric models and classification techniques. Recent work includes developing the MAINT.Data R package for interval data analysis and investigating outlier detection methodologies. As part of the Research Center in Management and Economics (CEGE), he contributes to methodological advances in data analysis with applications to management science. Current projects examine optimization approaches for classification problems and symbolic data analysis for official statistics.

Viktor Sowinski-Mydlarzمشاهده پروفایل

مدرس

• Cyber Security
• Data Analytics
• Machine Learning
• +۳ مورد دیگر

Dr. Viktor Sowinski-Mydlarz is a Lecturer in Computer Science and Applied Computing at the School of Computing and Digital Media, London Metropolitan University. He also serves as a post-doctoral researcher at the Cyber Security Research Centre. His research focuses on hybrid frameworks combining semantic and machine learning methods for data analysis, with recent projects involving cloud computing, bioinformatics (e.g., 3D modeling of Coronavirus variants), and cyber security threat intelligence. He teaches programming, software engineering, ethical hacking, computer networking, and cloud computing. His academic background includes a PhD in hybrid data processing frameworks. He has contributed to research funded by Lloyds Banking Group and Innovate UK, including Urban Data Space (air quality analysis) and Microsoft Azure Cluster (NHS prescription data statistics with Machine Learning). Dr. Sowinski-Mydlarz's work emphasizes software integration, containerization, and cloud-based data analytics orchestration. His publications span threat intelligence, cyber security policy validation, and AI-driven hybrid platforms.

Thais Webberمشاهده پروفایل

مدرس

• Healthcare Systems
• Cybersecurity
• User Authentication
• +۳ مورد دیگر

Thais Webber is a Lecturer in Software Engineering and Cybersecurity at Aston University's School of Computer Science and Digital Technologies. Her research focuses on developing secure, user-centered healthcare systems through participatory approaches and longitudinal studies. Recent work explores personalized authentication paradigms, non-invasive diagnostic technologies for conditions like endometriosis, and simulations of healthcare resource allocation during disruptions. Her publications demonstrate strong interdisciplinary collaboration, bridging computer science with clinical healthcare challenges. Methodologies include statistical modeling, system verification, and stakeholder engagement frameworks to address vulnerabilities in medical data systems and improve care delivery efficiency.

• Structural Integrity
• Multiaxial Fatigue
• Additive Manufacturing
• +۷ مورد دیگر

Luca Susmel is a Professor of Structural Integrity and Transforming Lives Fellow at Sheffield Hallam University. His expertise spans static, dynamic, and fatigue assessment of engineering materials and structures, with a focus on notched, welded, and 3D-printed components. He has authored over 350 publications, including 165+ peer-reviewed articles and a seminal book on multiaxial fatigue. His research has earned a high h-index and top 2% global scientist recognition. He serves as Editor-in-Chief of Theoretical and Applied Fracture Mechanics and has developed multiaxial fatigue-assessment software. Education and Career: Susmel has held academic roles at institutions including the University of Padova, Trinity College Dublin, and the University of Sheffield. His work bridges theoretical and experimental investigations, validated through systematic experiments. Notable projects include fatigue assessment of cast iron water pipes and hydrogen effects on metallic materials. Research Interests : Multiaxial fatigue, additive manufacturing materials, fracture mechanics, welded joints, notch fatigue, and fatigue life prediction. His methodologies include critical distance theory and advanced stress analysis approaches. Grants and Projects : Led numerous projects funded by EC, trusts, and private companies. Key areas include HyDeploy (hydrogen pipeline safety) and FRAMED (fatigue assessment of welded joints). Awards : Top 2% global scientist (Clarivate Analytics), Transforming Lives Fellow, high h-index recognition.