Shafaq Khan is an Assistant Professor in the School of Computer Science at the University of Windsor. She holds a PhD in Computer Science from the University of Salford (2017). Her research spans machine learning, deep learning, data analytics, and database systems with applications in healthcare informatics, agricultural technology, educational systems, and blockchain. Recent work focuses on AI-driven healthcare transformation, privacy-preserving data methods, federated learning for disease prediction, and computer vision applications in agriculture. Additional interests include educational technology for addressing disparities, blockchain implementations in government services, and open-source search engine development. Her work demonstrates consistent integration of cutting-edge computing techniques with practical domain applications.
Ken Salem is a Professor at the Cheriton School of Computer Science, University of Waterloo. His research focuses on database systems, distributed systems, cloud computing, and storage management. He has supervised 12 PhD students to completion, with graduates now working at companies like Google, Qualcomm, and SAP. His research interests include: Database system architecture and optimization Distributed transaction processing Cloud-based data management Energy-efficient computing Storage systems and hardware interactions Recent publications show strong focus on transactional systems, durability mechanisms, and cloud-native database architectures. His work consistently appears in top-tier venues like VLDB, SIGMOD, and IEEE Transactions on Knowledge and Data Engineering. Key projects include: SHADOW systems for high availability DimmStore for memory power optimization NoSE for NoSQL schema design RemusDB for transparent database availability
Nasim Beigi-Mohammadi is an Assistant Professor at the Department of Electrical, Computer and Software Engineering within the Faculty of Engineering and Applied Science at Ontario Tech University. Her research focuses on Adaptive Systems and Autonomic Computing with applications in cloud infrastructure, cybersecurity, and smart grid technologies. PhD in Computer Science from York University (2019) MSc in Computer Science from Toronto Metropolitan University (2013) BEng in Computer Engineering from Shahed University (2008) Her work bridges Software Defined Networking with Self-Adaptive Applications , emphasizing automated threat mitigation (e.g., DDoS attacks), resource optimization in cloud environments, and secure smart grid implementations. Recent publications explore DevOps frameworks for system self-protection and network activity data privacy . Key article trends include: Cybersecurity (DDoS mitigation, intrusion detection), Cloud Computing (software-defined infrastructure, microservices), and Smart Grid Applications (secure communication protocols). Awards include the L'Oscar from York University and NSERC CGS D scholarship. Lassonde School of Engineering Award (L'Oscar) - York University (2017) NSERC Alexander Graham Bell Canada Graduate Scholarship (CGS D) - 2016 Recognition for Research Funding Achievements - York University (2016)
Hans-Arno Jacobsen is a Professor holding the Jeffrey Skoll Chair in Computer Networks and Innovation at the University of Toronto , affiliated with the Department of Electrical and Computer Engineering and Department of Computer Science under the Faculty of Applied Science and Engineering . Full-time faculty member since 2001 Fellow of the IEEE Chair of the Computer Group Jacobsen leads the Middleware Systems Research Group (MSRG) , focusing on scalable distributed systems. His work spans: Core research: Event processing, publish/subscribe systems, service-oriented architectures Applied domains: Blockchain infrastructure, quantum machine learning, cloud computing Cross-disciplinary interests: Energy informatics, sustainable computing, quantum chemistry His publications and grants since 2019 demonstrate sustained leadership in: Quantum computing applications Reproducibility in quantum systems Blockchain optimization Microservices architecture Cyber-physical system engineering Selected scientific awards: Double Test-of-Time Award recipient from VLDB (2019) and ACM Middleware (2015) Event Processing Technical Society's Innovative Principles Award (2011) Major funding includes: NSERC Discovery Grant (2021-2026) for 'Learning Clouds' IBM/NSERC Collaborative Grant (2019-2023) for cloud microservices Ontario Research Fund (2019-2026) for CyPreSS project
Hai Wang serves as Professor in the Department of Finance, Information Systems, and Management Science at Saint Mary's University's Sobey School of Business, with an additional Adjunct Professor appointment in Dalhousie University's Faculty of Computer Science. His career progression from Assistant Professor (2004) to Associate Professor (2010s) to current full Professor demonstrates sustained academic impact within Canadian business education. His educational foundation includes: B.Sc. in Computer Science, University of New Brunswick (1995) M.Sc. in Computer Science, University of Toronto (1997) Ph.D. in Computer Science, University of Toronto (2004) Professor Wang's research integrates technical data science with business applications , featuring core interests in Big Data, Business Intelligence, and Knowledge Management. His work emphasizes practical implementation frameworks for enterprises, particularly focusing on Shared Services optimization and SME data analytics , while maintaining strong connections to Machine Learning and Database Management methodologies. This interdisciplinary approach bridges computer science rigor with business decision-making needs. Analysis of his recent publications (2020-2023) reveals three dominant trajectories: (1) Knowledge Management applications in cybersecurity and small business contexts, (2) Pedagogical innovations in database and business analytics education (including no-code approaches), and (3) Predictive analytics for shared services operations. His work consistently demonstrates translational value from academic research to business practice. His scientific recognition includes: Decision Sciences Journal of Innovative Education Best Teaching Brief Award (2011) Research funding from NSERC supports his ongoing work, while his teaching portfolio spans foundational courses like Business Applications Programming and advanced topics including Business Intelligence and Data Visualization. His mentorship extends through course-based projects and textbook authorship, though formal doctoral advisees aren't documented in public profiles. Current course offerings (2023-2024) confirm active classroom engagement across undergraduate, MBA, and Master's programs. Professor Wang maintains significant scholarly output through textbook development and conference leadership, with research increasingly addressing real-world challenges in business data ecosystems while advancing information systems education methodologies.
Dr. Thomas R Dean is a Professor in the Department of Electrical and Computer Engineering at Queen's University in Kingston, Ontario, Canada, and holds an additional appointment as an Adjunct Associate Professor at the Royal Military College of Kingston. His academic career spans several decades with consistent publication output through 2020, demonstrating active engagement in research and scholarship. His work bridges theoretical computer science with practical security applications, particularly in network protocols and web applications. Dean's research interests focus on software transformation techniques, web application evolution, and network security. His expertise includes software transformation, web site evolution, security of network applications, air traffic control systems, and language formalization. His work demonstrates a consistent thread connecting software engineering principles with security applications, particularly in developing techniques for intrusion detection systems and secure protocol implementations. His publications reveal a strong emphasis on practical applications of theoretical concepts, with numerous collaborations across academic and industrial settings. Analysis of Dean's recent publication record (2014-2020) shows a clear concentration in three interconnected areas: network security protocols, software transformation techniques, and model-based engineering approaches. His work on intrusion detection systems using constraint satisfaction methods appears consistently across multiple publications, demonstrating this as a core research thread. The publications also reveal growing interest in automotive software systems, particularly AUTOSAR implementations and Simulink model analysis, reflecting adaptation to emerging industry needs. Scientific recognition includes: Best paper award at CASCON'04 for Practical Language-Independent Detection of Near-Miss Clones Dean maintains active research collaborations, particularly with colleagues at Queen's University including M.H. Alalfi, J.R. Cordy, and F.T. Imam, as evidenced by co-authorship across multiple publications. His work spans both theoretical contributions and practical tool development, including parser generators, constraint engines, and intrusion detection systems. His research has been supported by publications in reputable venues including CASCON, IEEE conferences, and journals like Software Practice and Experience. Dean leads The Compass Group research team, focusing on software security and transformation techniques. His lab work emphasizes practical applications of software engineering principles to real-world security challenges, particularly in network protocols and web applications. The research approach combines formal methods with practical implementation, resulting in tools and frameworks that address specific security vulnerabilities in modern software systems.
Dr. Mahmoud H. Qutqut is an Assistant Teaching Professor in the Faculty of Computer Science at the University of New Brunswick (UNB) in Fredericton, Canada since September 2023. Previously, he served as Chair of the Cybersecurity and Cloud Computing Department at Applied Science University in Jordan (July 2022–August 2023) and was promoted to Associate Professor there in December 2019. He has held academic positions since 2014, including a visiting role at Queen’s University (2017–2019) where he contributed to research and teaching. His educational background includes a Ph.D. (2014) and M.Sc. (2008) in Telecommunication Systems, and a B.Sc. (2004) in Computer Systems. Research interests focus on smart city technologies, IoT, cybersecurity, and data-driven networks. He actively publishes in top-tier venues such as IEEE Access and has served on technical committees for conferences and journals. Notable achievements include a Teaching Excellence Award nomination (2018) and founding the Cisco Academy at Applied Science University (2015). Dr. Qutqut’s academic career spans teaching roles at Queen’s University, where he instructed courses on computer networks and computing fundamentals. His research bridges theoretical advancements with practical applications in network security, machine learning, and IoT systems. He has supervised impactful student projects, such as winning entries in graduation competitions (2017).
Yuepeng Wang is an Assistant Professor at the School of Computing Science, Simon Fraser University, Canada. He received his PhD and MSc from the University of Texas at Austin and BEng (honors) from the University of Science and Technology of China. Previously, he was a postdoctoral researcher at the University of Pennsylvania. Academic Honors: Distinguished Paper Award (OOPSLA'24, OOPSLA'17) Research Focus: Programming languages, formal verification, program synthesis, software engineering, and databases His research combines program verification and synthesis techniques across database applications, smart contracts, and software refactoring. Recent work focuses on SQL query equivalence, smart contract verification, and synthesis-driven database transformations. He supervises multiple graduate students and teaches advanced courses in programming languages and formal verification. He has contributed 15+ publications to top venues including PLDI, OOPSLA, ICSE, and POPL. His service includes program committee roles at POPL'26, SAS'25, and artifact evaluation committees for OOPSLA'23 and CAV'20. He also received the Distinguished Reviewer Award from PLDI'24.
Michael Mior is an Assistant Professor in the Department of Computer Science at the Rochester Institute of Technology (RIT), where he leads the Data Unity Lab. He holds a PhD from the David R. Cheriton School of Computer Science at the University of Waterloo. His research focuses on database systems, query optimization, NoSQL databases, and performance improvements through code migration to server-side execution. He is particularly interested in automating the translation of application code to run directly on database servers, reducing latency and improving efficiency. His work on Locomotor, published at DBPL '17, explores transparent migration of Python code accessing Redis into Lua scripts for server-side execution. Additional projects include NoSE (automated schema design for NoSQL), NetStore (SDN for key-value stores), and FlurryDB (dynamically scalable relational database using VM cloning). He is also the PMC chair for Apache Calcite, a modular framework for query processing. His research trends emphasize automation, performance, and integration between application logic and database systems, particularly in distributed and heterogeneous environments. Affiliation: Rochester Institute of Technology, Golisano College of Computing and Information Sciences Research Lab: Data Unity Lab Open Source Leadership: Project Management Committee Chair, Apache Calcite
