جست‌وجوی استاد و پژوهشگر

Bin Guoمشاهده پروفایل

استادیار

• Parallel and Distributed Computing
• Graph Algorithms
• Graph Mining
• +۵ مورد دیگر

Bin Guo is an Assistant Professor at the Computer Science Department of Trent University (since Jan. 2024) and an Adjunct Assistant Professor at the Computing & Software Department of McMaster University. He holds a PhD in Computer Science from McMaster University (2023) and an MSc in Applied Computer Science from Winnipeg University (2018). His research focuses on parallel/distributed computing, graph algorithms, and computer security for data analytics, with notable contributions to federated k-core decomposition and secure distributed algorithms. He teaches courses in database systems, operating systems, and computer security at Trent University and has taught at McMaster University. Education: PhD in Computer Science, McMaster University (2023) MSc in Applied Computer Science, Winnipeg University (2018) Research Interests: Parallel and Distributed Computing Graph Algorithms and Mining Computer Security & Privacy Federated Learning Concurrent Data Structures Advising & Grants: Current advisees: Gregory Prouty, Michael Abiona, Syed Zarif Past advisees: Igor Jardim-Martins, Issec Lee Funding sources: Graduate Teaching Assistantships, Research Fellowships, Trent University Research Development Grants Labs & Teams: Leading research projects in parallel graph algorithms and federated security algorithms Collaborating with McMaster University on PhD/Master's co-supervision

• Programming Languages
• Formal Verification
• Weak Memory Models
• +۴ مورد دیگر

Azalea Raad is a Reader (Associate Professor) in the Department of Computing at Imperial College London, leading the Veritas Lab. She holds a PhD in Computer Science from Imperial College London and is a UKRI Future Leader Fellow since 2021. Her research focuses on programming languages, formal verification, and persistent memory systems, particularly addressing challenges in weak memory models, concurrency, and software correctness. Affiliations: Co-director of the UK Research Institute on Verified, Trustworthy Software Systems Adjunct roles at Facebook (2020–2022) and Bloomberg (2022–present) Education: MEng from Imperial College London PhD in Computer Science from Imperial College London Research Interests: Azalea’s work bridges theoretical foundations and practical system implementation, emphasizing: Formal semantics of persistent and weak memory systems Verification frameworks for concurrent and persistent programs Bug detection in libraries and binaries Transactional memory and system validation Publications: Her recent work explores compositional bug detection, persistent programming principles, and scalable non-termination analysis. Key contributions include frameworks like IsaBIL and Memento, and foundational papers on RDMA robustness and C/C++ memory model extensions. Awards: UKRI Future Leader Fellowship (2021–present). Research recognized through collaborations with industry (e.g., Intel PMDK validation). Labs/Teams: Leads the Veritas Lab, advancing formal methods for trustworthy software systems.

Graham Rileyمشاهده پروفایل

مدرس

• High Performance Computing
• Scientific Computing
• Parallel Computing
• +۴ مورد دیگر

Graham Riley is a Lecturer in the School of Computer Science at the University of Manchester and holds a part-time position in the Scientific Computing Department (SCD) at STFC, Daresbury. His research focuses on high performance computing (HPC), software engineering for scientific computing, and performance modeling for parallel machines. Key areas include techniques for developing HPC applications, software architectures for coupled modeling, and performance control in distributed systems. His work emphasizes collaboration with computational scientists in domains such as Earth System Modelling (e.g., UK Met Office), computational chemistry, and biology. He has contributed to projects like the EuroExa architecture for exascale computing and the LFRic weather/climate model porting to FPGAs. Riley's research also explores energy efficiency in HPC systems and FPGA acceleration strategies for scientific workloads. Notable contributions include studies on parallelization strategies, FPGA-based acceleration of climate models, and optimizing OpenCL for heterogeneous architectures. His work aligns with UN Sustainable Development Goals, particularly through contributions to climate modeling and sustainable computing practices. Riley collaborates with institutions like the Met Office and the ESM community in Europe/US. His academic profile reflects a balance between theoretical research and practical application, with a strong focus on bridging computational science and engineering challenges.

• Formal Methods
• Software Engineering
• Model-Based Testing
• +۳ مورد دیگر

Alessandra Cavarra is a University Lecturer in Software Engineering at the University of Oxford, holding roles as Director of Graduate Studies for Professional Programmes and Supernumerary Fellow at Kellogg College. She earned her MSc and PhD in Computer Science from the University of Catania (Italy), with research periods at U.S. and German institutions. Her research focuses on formal methods, UML behavioral diagrams, model-based testing, and integrating formal/semi-formal languages. She teaches postgraduate courses in Object-Oriented Design and Software Testing. Research interests include formal semantics for UML diagrams, tool development for symbolic execution and test case generation, and abstract state machines (ASMs). Her work bridges software engineering theory and practice, emphasizing rigorous methods for system validation. Publications span model-based testing, UML formalization, and concurrency analysis. Key areas include data-flow approaches for multi-agent systems, workflow testing, and formal verification of software models. Recent work addresses challenges in concurrent workflows and abstract state machine analysis. No scientific awards were explicitly mentioned. She has advised at least one student, Aadya Shukla, and contributes to academic service roles. No lab or team affiliations are detailed in the provided information.

Jennie Rogersمشاهده پروفایل

دانشیار

• Trustworthy Database Systems
• Secure Data Sharing
• Privacy-Preserving Analytics
• +۷ مورد دیگر

Jennie Rogers is an Associate Professor of Computer Science at Northwestern University's McCormick School of Engineering. She holds a Ph.D. and MS from Brown University and a BS from Rensselaer Polytechnic Institute. Her research focuses on trustworthy database systems, secure data sharing, privacy-preserving analytics, and federated query processing. She leads projects like VaultDB (a private data federation system) and BigDAWG (a polystore system for heterogeneous data models). Recipient of the NSF CAREER Award (2019) Adjunct at the Center for Native American and Indigenous Research (2020–2023) Education: Ph.D. in Computer Science, Brown University (2013) MS in Computer Science, Brown University (2006) BS in Computer Science, Rensselaer Polytechnic Institute (2003) Research Interests: Secure multi-party computation for private data federations Privacy-preserving query optimization Polystore systems for heterogeneous data models Applications in healthcare and scientific data integration Selected Awards: NSF CAREER Award (2019) SIGMOD Distinguished Service Award (2021) Advising & Grants: Advised over 30 students (PhD, MS, undergrad) Recipient of DARPA, AFRL, and NSF grants totaling $2.5M+ Labs/Teams: Lead the VaultDB and BigDAWG research initiatives, collaborating with institutions like Feinberg School of Medicine and Intel.

Susanne M Furmanمشاهده پروفایل

مدرس

• Human-Computer Interaction
• Cybersecurity
• Usability Engineering
• +۴ مورد دیگر

Susanne M Furman is an Instructor in the Department of Psychology at George Mason University (GMU), concurrently serving as a cognitive scientist in the Visualization and Usability Group at the National Institute of Standards and Technology (NIST). Her roles span academic and federal agency work, focusing on usability engineering and cybersecurity. She holds a PhD in Applied Experimental Psychology (Human Factors) from GMU, with prior experience at IBM, GE, and the U.S. Department of Health and Human Services. Education: B.A. in Psychology, Bloomsburg University of Pennsylvania (1988) M.A. in Applied Experimental Psychology, George Mason University (1990) Ph.D. in Applied Experimental Psychology (Human Factors), George Mason University (1997) Research focuses on usability of cybersecurity tools, biometric systems, and smart home technologies. Key themes include privacy preservation, user mental models of security, and cross-agency collaboration (e.g., with DHS and FBI). Recent work examines consumer trust in smart home ecosystems and lifecycle management of IoT devices. Publications (selected): Her work bridges usability research with federal cybersecurity needs, including foundational studies on contactless fingerprint devices and smart home privacy challenges. Over 25 years of industry and academic collaboration has produced impactful contributions to human-centered cybersecurity standards. Affiliations: Active in NIST’s Human-Centered Cybersecurity projects and GMU’s Psychology department. She contributes to federal usability programs and collaborates with researchers like Julie Haney and Brian Stanton.

• Programming Languages
• Semantics
• Type Systems
• +۵ مورد دیگر

Nikolaos S. Papaspyrou is a Professor at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA), affiliated with the Software Engineering Laboratory and the Division of Computer Science. His research focuses on programming languages, compilers, formal verification, and concurrency. Since October 2021, he has been on leave from NTUA while working as a Software Engineer at Google's V8 JavaScript and WebAssembly engine team. Previously, he served as Director of the Division of Computer Science (2017–2019) and held a sabbatical at Google's Munich compiler group (2015–2016). His academic contributions include pioneering work on Erlang/OTP scalability, concolic testing for functional languages, and static analysis techniques. He has authored numerous publications in top venues like ACM Transactions on Programming Languages and Systems and IEEE conferences. Papaspyrou has supervised over 50 diploma students and multiple PhD candidates, contributing to the education of future researchers and engineers. He actively participates in programming competitions, coaching Greek Olympiad teams, and volunteers in the Hellenic Informatics Society. He teaches advanced courses on programming languages, compilers, and software engineering at NTUA, emphasizing practical applications of theoretical concepts. His educational philosophy integrates problem-solving through programming, as highlighted in his FedCSIS 2013 paper on teaching methodologies.

Stewart Weissمشاهده پروفایل

دانشیار

• Software Quality Assurance
• Computer Science Education
• Computational Biophysics
• +۳ مورد دیگر

Stewart Weiss is an Associate Professor in the Department of Computer Science at Hunter College, part of the City University of New York (CUNY). His research focuses on Software Quality Assurance, computational biophysics, and integrating open-source software into computer science education. He holds a PhD in Computer Science from New York University's Courant Institute (1987), an M.S. from the same institute (1984), and a B.A. in Mathematics from Hunter College (1982), alongside a B.Arch. from The Cooper Union (1973). Dr. Weiss teaches courses such as Software Design and Analysis, Computer Theory, and UNIX Tools. His work spans grants from NSF and PSC-CUNY, including research in protein structure prediction via the kernel energy method and educational initiatives like 'Computing for Social Good.' He has advised on projects like the 'Gateway for Open Source Software Development' in curricula and contributed to tools for adaptive contrast sensitivity testing. His teaching philosophy emphasizes rigorous academic standards and hands-on learning. He has developed extensive resources, including tutorials on UNIX, parallel programming, and C/C++ programming. His research has explored topics ranging from mutation testing frameworks to quantum chemistry applications in molecular modeling.

• Artificial Intelligence and Data Science
• Data Management & Mining
• Machine Learning & Intelligence
• +۳ مورد دیگر

ZHENG Baihua serves as Professor of Computer Science at Singapore Management University's School of Computing and Information Systems (SCIS), concurrently holding leadership roles as Associate Dean for SCIS Post-Graduate Research Programmes and Director of the Master of Science in Computing programme. Currently on leave but maintaining full-time faculty status, his academic career spans over two decades with foundational training from Hong Kong University of Science and Technology. Professor Zheng's research program integrates artificial intelligence, data science, and urban computing to solve critical challenges in mobility and sustainability. His expertise centers on trajectory data management, social network analysis, and spatio-temporal modeling, with significant contributions to trajectory compression algorithms, influence minimization in social networks, and real-time traffic prediction systems. His work bridges theoretical database innovations with practical applications in smart city infrastructure and public health interventions. Analysis of recent publications (2024-2025) reveals a dominant focus on physics-informed trajectory processing, GPU-accelerated indexing for high-dimensional data, and transformer-based models for urban mobility prediction. Key trends include the fusion of graph neural networks with spatio-temporal dynamics, novel approaches to contact tracing through timeline graphs, and differentiable search techniques for structured data discovery. These works consistently target real-world deployment in transportation systems and epidemic control. No scientific awards are documented in available institutional records. Information regarding student supervision, research grants, laboratory facilities, or collaborative teams remains unspecified in current public profiles.

Eric Koskinenمشاهده پروفایل

دانشیار

• Concurrent Programming
• Formal Verification
• Programming Languages
• +۳ مورد دیگر

Eric Koskinen is the Charles Berendsen Chair Associate Professor in the Department of Computer Science at Stevens Institute of Technology. His research focuses on improving concurrent software development for multi-core and distributed systems through advances in programming languages, verification techniques, and formal methods. He holds a PhD from the University of Cambridge and has held roles at Yale, NYU, and industry positions at IBM, Microsoft, and Amazon. Education: PhD (2013) University of Cambridge, MS (2008) Brown University, BS (2001) William & Mary Research Interests: Concurrent programming, formal verification, programming language design, and distributed systems Recipient of over $5M in grants from NSF/ONR/DARPA. Active in conference organization (POPL, PLDI) and has developed verification tools like CityProver and Veracity. Advises PhD students in concurrency research and teaches courses on programming languages, discrete structures, and software verification.

George Karabatisمشاهده پروفایل

استاد

• Cyber-security
• Semantic Information Integration
• Workflow Systems
• +۵ مورد دیگر

George Karabatis is a Professor of Information Systems at the University of Maryland, Baltimore County (UMBC). He currently serves as the Director of Entrepreneurship and Innovation Minor at UMBC and holds roles as Liaison for Programmatic Innovations in the Department of Information Systems. With a Ph.D. and M.S. in Computer Science and a B.S. in Mathematics, he previously worked as a Research Scientist at Telcordia Technologies. His research focuses on cybersecurity (intrusion detection via contextual semantics), semantic information integration, workflow systems, and database applications for mobile devices. Key contributions include developing flow-based detection approaches using semantic networks and exploring contextual anomaly detection for zero-day attacks. Teaching expertise spans courses like Systems and Information Integration (IS 722), Mobile Data Management (IS 720), and Advanced Database Projects (IS 620). His work bridges theoretical foundations with practical implementations in enterprise systems and mobile technologies.

Maitreyee Deyمشاهده پروفایل

پژوهشگر ارشد

• Machine Learning
• Artificial Intelligence
• Low Carbon Technologies
• +۹ مورد دیگر

Dr. Maitreyee Dey serves as a Visiting Fellow in Mechanical Engineering and Design and works as a Post-doctoral research fellow at London South Bank University's Department of Electrical and Electronics Engineering. She concurrently holds the position of Data Mining Lead at Neuville Grid Data Management Limited, where she contributes to significant energy research projects. Her research expertise spans machine learning/artificial intelligence and low carbon technologies, with additional interests in pattern recognition, big data analysis, deep learning, image processing, energy optimization in smart buildings, renewable energy technology, and Computer-aided Diagnosis for smart health applications. Her work directly contributes to UN Sustainable Development Goals related to clean energy and sustainable communities. Analysis of her recent publications reveals a strong research trajectory focusing on two primary domains: power grid analysis using machine learning techniques and microwave-based medical imaging for breast cancer detection. Her work demonstrates sophisticated applications of neural networks and data mining methods to solve complex problems in both energy systems and medical diagnostics. Best Paper Award at the CUE conference, Elsevier (2020) Endorsement by the Royal Academy of Engineering Dr. Dey serves as an Editorial board member for MDPI journals and as an Adhoc reviewer for high-impact publications including IEEE transactions and Nature Scientific Data. She is actively involved in the Access to Innovation (A2i) and Low Carbon London (LCLDN) projects funded by the EU commission through its regional development Fund, working in collaboration between London South Bank University and Neuville Grid Data Management Limited. Her professional affiliations include active membership in IEEE, CIGRE NGN, and the Energy Institute, demonstrating her engagement with key professional organizations in her fields of expertise.

Reza Salkhordehمشاهده پروفایل

مدرس

• Operating Systems
• Solid-State Drives
• Data Storage Systems
• +۵ مورد دیگر

Reza Salkhordeh is a Lecturer and Postdoctoral Researcher at Johannes Gutenberg University Mainz, Germany, where he leads the Efficient Computing and Storage Group. He holds a Ph.D. in Computer Engineering from Sharif University of Technology (2018) and has been affiliated with Ferdowsi University of Mashhad and Sharif University of Technology. His research focuses on operating systems, storage systems, and non-volatile memory technologies, with a particular emphasis on high-performance computing and I/O optimization. He has taught courses such as Storage Systems and Advanced Topics in Operating Systems since 2020. His academic journey includes a B.Sc. from Ferdowsi University (2011), M.Sc. and Ph.D. from Sharif University (2013, 2018). He has held roles such as Technical Lead for the High-Performance Data Storage System (HPDS) project in Tehran, Iran, and has mentored 4 M.Sc. and 6 B.Sc. students. His work spans patented technologies like Reconfigurable Cache Architectures and Load Balancers for I/O caching systems. Research interests include heterogeneous memory management, storage system design, and optimizing I/O performance in distributed environments. His recent publications address challenges in NVMM utilization, garbage collection in SSDs, and I/O tracing for HPC systems. He is actively involved in conference committees (e.g., FAST, ARCS, SC) and has reviewed for top journals like IEEE TPDS and ACM Transactions on Storage. Notable recognitions include membership in Iran’s National Elites Foundation (2012–2015) and top rankings in national exams (3rd in PhD, 35th in MSc). His contributions to storage systems have advanced enterprise-grade architectures and decentralized file systems, with a focus on practical implementations for modern computing challenges.

Jens Lechtenbörgerمشاهده پروفایل

مدرس

• Open Educational Resources (OER)
• Data Warehousing
• Business Intelligence
• +۴ مورد دیگر

Dr. Jens Lechtenbörger is a Faculty member and Lecturer at the Chair of Machine Learning and Data Engineering at the University of Münster's School of Business and Economics. He holds a Doctoral degree (2001) and a diploma in Computer Science (1997) from the University of Münster and Oldenburg, respectively. His roles include serving as Akademischer Oberrat since 2006, Acting Professor (2016), and Fellow for innovation in digital university teaching (2016–2017). He leads projects like Tutor.AI and OER infrastructure development, focusing on Open Educational Resources (OER), data warehousing, and educational technology. Research interests span OER creation, data integration, business intelligence, and machine learning applications in education. He has published extensively on data warehouse design, database systems, and educational technologies. Notable awards include the Best Evolutionary & Swarm Computation Paper Award (2019) and the Dissertation Prize 2003. Teaching responsibilities include courses on data structures, operating systems, and management information systems. He supervises theses on topics like AI-driven learning systems, data privacy, and business logic vulnerabilities. Active in academic service, he chairs committees on digital teaching and curriculum reform at the University of Münster.

Amal Ahmedمشاهده پروفایل

استاد

• Programming Languages
• Compiler Verification
• Secure Compilation
• +۳ مورد دیگر

Dr. Amal Ahmed is a Professor of Computer Science at Northeastern University's Khoury College, where she leads research on programming languages and compilers. Her work develops formal foundations for secure multi-language software systems. Core research areas: Compiler correctness for heterogeneous codebases Type-preserving compilation Secure interoperability (FFI/ABI semantics) Gradual typing theory Recent publications address WebAssembly security, probabilistic program verification, and ABI specification. Methodological innovations include logical relations for compiler verification and multi-language semantic frameworks. Honors and funding: NSF CAREER Award (2015) Google Faculty Research Award (2014) DARPA V-SPELLS grant NSF SHF grants Dr. Ahmed directs the SILC (Secure Interoperability, Languages, and Compilers) group and co-organizes programming languages mentoring workshops. She teaches graduate courses on type theory and compiler verification.