جستجوی استاد راهنمای دانشگاهی

M. Jason Hinekمشاهده پروفایل

دانشیار

• Computer Science Education
• Cryptology
• Computer Security
• +۳ مورد دیگر

Dr. M. Jason Hinek is an Associate Professor in the Teaching Stream and Associate Director of Recruitment/Outreach at Carleton University's School of Computer Science. He holds a PhD from the University of Waterloo (2007). His research focuses on cryptology, computer security, and computer science education, with earlier work in wood polymer studies via NMR analysis. He teaches courses such as Introduction to Computer Science, Discrete Structures, and Applied Cryptography. Dr. Hinek’s scholarly work emphasizes RSA cryptosystem variants, cryptanalysis techniques, and cryptographic protocol security. His publications explore vulnerabilities in multi-prime RSA, attribute-based encryption, and modular arithmetic optimizations. He has contributed to understanding key exposure attacks, encryption efficiency trade-offs, and lattice-based cryptographic attacks. His teaching responsibilities include foundational computer science courses at both undergraduate levels. No scientific awards are explicitly mentioned in his profile. His research spans theoretical cryptography with practical applications in security systems.

Zinovi Rabinovichمشاهده پروفایل

استادیار

• Artificial Intelligence
• Multi-Agent Systems
• Reinforcement Learning
• +۶ مورد دیگر

Zinovi Rabinovich is an Assistant Professor in the School of Computer Science at Carleton University, Ottawa. He previously held positions at Nanyang Technological University (Singapore), Mobileye Vision Technologies, Bar-Ilan University (Postdoctoral Researcher), and the University of Southampton (Research Fellow). He earned his Ph.D. in Computer Science from the Hebrew University of Jerusalem in 2008. Education: Ph.D. in Computer Science, Hebrew University of Jerusalem, 2008 Research Interests: Focuses on manipulating decision behavior and perceptual control in AI systems, particularly in adversarial scenarios. Current work addresses Behavior Cultivation (Backdoor attacks/Environment Poisoning) against Reinforcement Learning, leveraging deep learning, game theory, and evolutionary methods. Key themes include scalability, stealth, and applicability of attacks across learning frameworks. Projects include Choice Manipulation and Security Games and Mixed Initiative DCOPs under grants from the Ministry of Education (Singapore). Awards: None explicitly listed. Advising & Grants: Advises PhD students: Hang Xu, Rundong Wang, Ridhima Bector Recipient of AcRF Tier-1 grant for Mixed Initiative DCOPs research Labs/Teams: Leads The Lab of Z , focusing on ethically grounded AI and its societal implications.

Michel Barbeauمشاهده پروفایل

استاد

• Wireless Communications and Networking
• Underwater Communications
• Quantum Communications
• +۴ مورد دیگر

Michel Barbeau is a Professor and Director at the School of Computer Science, Carleton University. He holds a Ph.D. in Computer Science from Université de Montréal (1991) and has held academic roles at Université de Sherbrooke (1991–1999) and a visiting position at the University of Aizu, Japan. His research focuses on non-classical wireless networks, including underwater acoustic communication systems, quantum networks, and resilience assessment of cyber-physical systems. He leads projects involving acoustic signal processing, underwater node communication, and challenges like multipath propagation in aquatic environments. His team tested prototypes in Ottawa’s Rideau Canal. His work spans underwater communication protocols, quantum encryption, and AI-driven network optimization. He is active on YouTube and Twitter, and his ORCID profile highlights interdisciplinary contributions. His research emphasizes practical applications in environmental monitoring, coastal navigation, and secure quantum communication frameworks. Education: Ph.D. Computer Science, Université de Montréal (1991) M.Sc. Computer Science, Université de Montréal (1987) B.Sc. Computer Science, Université de Sherbrooke (1985) Research Interests: Underwater Acoustic Networks Quantum Communications and Cryptography Cyber-Physical Systems Resilience Ad Hoc and Mobile Networks Machine Learning for Network Optimization His current projects address challenges such as signal interference in underwater environments and developing quantum-safe cryptographic algorithms. Collaborations involve interdisciplinary teams of students and researchers. Advancement and Grants: Lead projects on underwater surveillance systems Explores quantum encryption protocols for post-quantum security Investigates AI-driven solutions for UAV and MIMO networks Labs and Teams: His research group focuses on experimental prototyping, including underwater acoustic networks and quantum communication frameworks. Collaborations span academia and industry for real-world applications.

Farah Chancharyمشاهده پروفایل

مدرس

• Computer Science
• Cloud Computing
• Data Structures
• +۷ مورد دیگر

Farah Chanchary is a Lecturer and Lab/Course Coordinator at the School of Computer Science, Carleton University. She specializes in areas such as data structures, cloud computing, and educational technologies. Her work spans algorithm design, privacy in advertising, and challenges in e-learning, particularly in Saudi Arabia. She coordinates laboratory and course activities, supporting academic infrastructure. Research Interests: - Data Structures and Algorithms - Cloud Computing and Migration - Privacy-Preserving Models in Advertising - E-Learning Readiness and Challenges - Machine Learning Applications (Neural Networks, Genetic Algorithms) - Geometric Query Processing Publications Trends: Her recent work focuses on efficient data structures for window queries, privacy concerns in online advertising, and cloud computing challenges. Earlier research includes studies on e-learning adoption in Saudi Arabia and neural network applications in rainfall forecasting. No awards or grants are listed. She has no documented advisees. She manages laboratory facilities and course coordination in the School of Computer Science.

Avery Millerمشاهده پروفایل

دانشیار

• Theoretical Computer Science
• Distributed Algorithms
• Graph Theory
• +۵ مورد دیگر

Avery Miller is an Associate Professor in the Department of Computer Science at the University of Manitoba. His research focuses on theoretical computer science, particularly distributed algorithms, graph theory, and algorithmic lower bounds. He holds a Ph.D. from the University of Toronto, supervised by Faith Ellen, and has held postdoctoral positions at Tel Aviv University and Université du Québec en Outaouais. Education: Ph.D. in Computer Science, University of Toronto (Supervisor: Faith Ellen) M.Sc. in Computer Science, University of Toronto (Supervisor: Faith Ellen) B.Math. in Computer Science and Combinatorics & Optimization, University of Waterloo Research interests include distributed computing in anonymous networks, wireless networks, and graph burning. His work explores deterministic protocols, fault-tolerant systems, and the role of information in distributed algorithms. Recent projects involve reconfiguration of multisets, fast rendezvous in labeled networks, and cop-and-robber games on planar graphs. Publications highlight contributions to distributed algorithms, radio networks, and graph theory, including a best paper award at SPAA 2019. His work often bridges theoretical foundations with practical network challenges. Awards: Best Paper Award at SPAA 2019 Academic service includes roles as Organizing Chair of PODC 2021, Treasurer of PODC 2020, and committee memberships in SPAA, DISC, and other conferences. He reviews for top journals like ACM Transactions on Algorithms and Theoretical Computer Science. Teaching includes courses on automata theory, algorithms analysis, and distributed computing. He is part of the Geometric, Approximation, and Distributed Algorithms Lab at the University of Manitoba.

Jian Tangمشاهده پروفایل

استاد

• Database Systems
• Distributed Computing
• Data Mining
• +۳ مورد دیگر

Dr. Jian Tang is a Professor in the Department of Computer Science at Memorial University of Newfoundland. He holds a M.Sc. from the University of Iowa and a Ph.D. from Penn State University. His primary affiliation is within the Faculty of Science. His research focuses on database systems, distributed computing, data mining, and IoT security. Key projects include fault tolerance in distributed systems, workflow management, intrusion detection in IoT networks, and machine learning applications in healthcare and genomics. He has published extensively on topics like autonomous IoT security systems, feature selection methods for microarray data, and probabilistic resource scheduling in grid environments. Dr. Tang’s work bridges theoretical foundations with practical implementations, particularly in cybersecurity, bioinformatics workflows, and scalable distributed systems. His recent publications emphasize real-time autonomous IoT security solutions and machine learning-driven predictive models for healthcare outcomes.

George O.M. Yeeمشاهده پروفایل

استاد مدعو

• Information Security
• Privacy Protection
• Computational Intelligence
• +۳ مورد دیگر

Dr. George O.M. Yee is an Adjunct Professor at the School of Computer Engineering, Carleton University. He holds a Ph.D. from Carleton and is a licensed Professional Engineer (P.Eng.). His research focuses on information security, privacy protection, computational intelligence, software engineering, and performance optimization. He has received numerous awards, including the IARIA Fellow (2017), AINA-2007 Outstanding Service Award, and multiple Nortel and IEEE accolades. His work emphasizes secure system design, privacy compliance, and cybersecurity metrics. Recent publications address behavioral security postures, attack surface reduction, and threat mitigation strategies. He has contributed to frameworks for privacy protection in distributed systems and cloud computing, leveraging computational methods for policy enforcement and vulnerability analysis. Dr. Yee’s awards reflect his industry and academic impact, including awards for innovation (Nortel Gold Pride, 2000) and IEEE recognition. His research aligns with Carleton’s focus on engineering excellence and interdisciplinary collaboration.

Moshe Arye Milevskyمشاهده پروفایل

استاد

• Retirement Income Planning
• Longevity Risk
• Annuities
• +۲ مورد دیگر

Moshe Arye Milevsky is Professor of Finance and CIT Chair in Financial Services at York University's Schulich School of Business. His research focuses on pensions, retirement income solutions, longevity risk management, and the history of financial products. He developed computational innovations in retirement income financing and holds multiple US patents. Milevsky has published 18 books translated into six languages and over 60 peer-reviewed papers. He received the Monash University Faculty of Arts Dean's Research Award (2021) and was named among the 35 most influential people in the US financial advisory business. Recent work examines historical and contemporary tontine designs, longevity risk pooling mechanisms, and biblical references to annuity concepts. Monash University Faculty of Arts Dean’s Research Award (2021)

Banani Royمشاهده پروفایل

استادیار

• Software Maintenance and Renovation
• Software Analytics
• Empirical Software Engineering
• +۴ مورد دیگر

Dr. Banani Roy is an Assistant Professor in the Department of Computer Science at the University of Saskatchewan. Her research focuses on software maintenance, empirical software engineering, program comprehension, and scientific workflow management systems. She explores challenges in quantum computing applications for software engineering, AI-driven code tools, and reproducibility in computational experiments. Her work includes developing frameworks like VizSciFlow for scientific workflow visualization and Nutrient App for environmental monitoring via smartphone applications. Her research interests span topics such as code quality analysis, gender disparities in software systems, and XAI (Explainable AI) challenges. She has contributed to tools like CloneCognition for code clone validation and FSECAM for feature-to-architecture linkage. Her recent studies address developer challenges with large language models and federated learning approaches for real-time bug prediction. Dr. Roy's publications emphasize interdisciplinary applications of software engineering principles in scientific computing, quantum algorithms, and community-driven problem-solving platforms. She advocates for reproducible workflows and FAIR (Findable, Accessible, Interoperable, Reusable) data practices in collaborative scientific research. While no awards are explicitly listed, her extensive contributions to open-source tool development and empirical studies highlight her impact in advancing software engineering methodologies. She collaborates on projects involving legacy system reengineering, cloud-based code clone validation, and asynchronous collaboration frameworks for scientific teams.

Natalia Stakhanovaمشاهده پروفایل

دانشیار

• Cybersecurity
• Malware Analysis
• Software Obfuscation
• +۷ مورد دیگر

Natalia Stakhanova is an Associate Professor and Director of The CyberLab at the University of Saskatchewan, Canada. She is a leading researcher in cybersecurity, with a focus on malware analysis, software obfuscation, mobile security, IoT security, and e-Health security. Her work integrates practical solutions to real-world security challenges, leveraging advanced techniques in reverse engineering, blockchain forensics, and AI-driven security tools. Her research has been recognized with prestigious awards, including the Best Paper Awards at FPS 2023 and EUSPN 2023, and she was named one of Canada’s Top 20 Women in Cybersecurity. She actively contributes to the cybersecurity community through editorial roles (e.g., IEEE TDSC) and conference leadership (e.g., Program Chair of SAD20 and SSPREW19). Stakhanova’s recent work explores AI-generated code security, adversarial analysis of software tools, and blockchain-based healthcare data integrity. Her projects often involve collaboration with industry partners, emphasizing practical impact alongside academic rigor.

Jens Weberمشاهده پروفایل

استاد

• Software Engineering
• Safety and Security Engineering
• Health Informatics
• +۵ مورد دیگر

Jens Weber is a Professor and Associate Dean of Professional Programs & Development at the Faculty of Engineering and Computer Science, University of Victoria. He holds a PhD from the University of Paderborn and is a Professional Engineer (P.Eng.) in British Columbia. His research focuses on software engineering with emphasis on safety and security assurance in critical systems, particularly in healthcare, transportation, and defense sectors. He also investigates systems incorporating artificial intelligence and self-adaptation. He teaches courses on security engineering, software architecture, and formal methods. His affiliations include the School of Health Information Science at UBC and the Faculty of Medicine at UBC. Key research projects include GRAPE VINE (graph transformation tools), Information Security Assurance, Medical Device Software Certification, and Medical Systems Hazard Analysis. He serves on the Board of Engineers and Geoscientists BC, chairs the Academic Integrity Committee, and organized conferences like IEEE Health Informatics 2021. His work emphasizes bridging engineering practices with real-world software deployment challenges, especially in health informatics. Awards include the 2019 Société de Biomécanique Young Investigator Award for human body model validation research. Current initiatives include developing data quality frameworks for clinical systems, tool support for functional graph programming, and safety analysis methodologies for adaptive systems.

Honghao Fuمشاهده پروفایل

استادیار

• Quantum Computing
• Device-independent Quantum Cryptography
• Entanglement Verification
• +۳ مورد دیگر

Dr. Honghao Fu is an Assistant Professor at the Concordia Institute for Information Systems Engineering (Department of Information Systems Engineering), Concordia University. His primary research focuses on quantum computing, device-independent quantum cryptography, entanglement verification, and testing of untrusted devices. He actively seeks students for thesis supervision in these areas. His research interests emphasize foundational aspects of quantum information science, including protocols for quantum state purification, undecidability in quantum correlation problems, zero-knowledge proofs in multi-prover interactive systems, and practical implementations of device-independent cryptography using quantum entanglement. His work bridges theoretical computer science and experimental quantum physics, with applications in secure communication and computational complexity. Recent publications (2020–2025) highlight advancements in quantum state purification techniques, undecidability proofs for quantum correlations, low-latency quantum randomness expansion, and computational self-testing for quantum devices. His research often explores the intersection of quantum theory and cryptographic security, particularly under noisy or untrusted conditions. No scientific awards or grants are explicitly mentioned in the provided text. His advising focus aligns with his research areas in quantum cryptography and information systems engineering.

Serguei A. Mokhovمشاهده پروفایل

دانشیار مدعو

• Computer Science
• Software Engineering
• Cybersecurity
• +۹ مورد دیگر

Serguei A. Mokhov is an Affiliate Associate Professor in the Department of Computer Science and Software Engineering at Concordia University’s Gina Cody School of Engineering. He also holds the position of Affiliate Assistant Professor at the Concordia Institute for Information Systems Engineering. Additionally, he serves as the Manager for Network, Security & HPC within GCS ENCS and AITS under the Gina Cody School. His research focuses on cybersecurity, high-performance computing (HPC), digital forensics, real-time systems, and distributed computing frameworks like OpenISS and GIPSY. He is actively involved in developing tools for forensic analysis (e.g., Forensic Lucid) and real-time interactive systems for performing arts and multimedia applications. His work bridges computer science with creative technologies, emphasizing interdisciplinary collaboration. Notable projects include the OpenISS framework for real-time broadcast services and the GIPSY system for intensional programming. He has also contributed to machine learning applications in recommendation systems and cybersecurity. His teaching and research support roles involve integrating containerization (e.g., Kubernetes) and HPC into academic and industrial contexts. Recent publications highlight advancements in forensic computing, real-time gesture recognition, and knowledge graph-enhanced recommendation systems. His research often addresses challenges in scalability, interoperability, and real-time performance across diverse domains from digital forensics to interactive art installations.

• Software Engineering
• Software Evolution
• Knowledge Modeling
• +۷ مورد دیگر

Dr. Juergen Rilling is a Professor in the Department of Computer Science and Software Engineering at Concordia University. His research focuses on global software analytics, software traceability, knowledge modeling, and security vulnerabilities, with a strong emphasis on semantic web technologies. He leads projects in software evolution, mining software repositories, and integrating crowd-based data into development practices. His work bridges software engineering theory with practical tools like SeClone and SeByte, enhancing code analysis, dependency management, and security practices. Research interests include semantic modeling for security advisories, feature location via crowd-based screencasts, and API trustworthiness assessment. He has contributed to frameworks like SE-EQUAM for software quality metamodeling and Sv-AF for vulnerability analysis. His recent work explores machine learning applications in software ecosystems and developer behavior analysis through platforms like Stack Overflow. Publications span over two decades, with a focus on scalable clone detection, ontological approaches for traceability recovery, and integrating financial pattern analysis for software quality prediction. His tools and methodologies are applied in open-source ecosystems and industrial software maintenance contexts.

Ching Yee Suenمشاهده پروفایل

استاد

• Pattern Recognition
• Image Processing
• Artificial Intelligence
• +۹ مورد دیگر

Dr. Ching Yee Suen is a Professor and Director of the Centre for Pattern Recognition and Machine Intelligence (CENPARMI) at Concordia University. He holds an Honorary Chair in AI & Pattern Recognition. His academic roles include former Chairman of the Department of Computer Science and Associate Dean (Research) in the Faculty of Engineering and Computer Science. Education: PhD from the University of British Columbia (UBC) and Master's from the University of Hong Kong. Research focuses on pattern recognition, handwriting analysis, document analysis, computer vision, and applications in security (e.g., counterfeit detection). Key interests include font design, computational linguistics, and facial recognition. Awarded the IAPR King-Sun Fu Prize (2020), Elsevier Award (2016), and Gold Medal from the University of Bari (2012). Recipient of over 30 industrial grants and prestigious national/international awards. Founded major conferences: ICDAR, ICFHR, and Vision Interface (VI). Lab: CENPARMI, leading research in AI and pattern recognition. Supervised 130+ graduate students and hosted 100+ visiting scholars. Editorial roles include Emeritus Editor-in-Chief of Pattern Recognition and advisory roles in multiple journals.