جستجوی استاد راهنمای دانشگاهی

Jason Jaskolkaمشاهده پروفایل

دانشیار

• Cyber Security Evaluation
• Security Assurance
• Formal Methods
• +۴ مورد دیگر

Jason Jaskolka is an Associate Professor in the Department of Systems and Computer Engineering at Carleton University, part of the Faculty of Engineering and Design. He holds a Ph.D. from McMaster University and is a licensed Professional Engineer in Ontario. His research focuses on cyber security evaluation and assurance, formal methods, and secure software engineering. He leads the Cyber Security Evaluation and Assurance (CyberSEA) Lab, emphasizing security-by-design principles for complex systems like industrial control systems and IoT-enabled healthcare. Education: Ph.D. (Software Engineering, McMaster University, 2015), M.A.Sc. (Software Engineering, McMaster University, 2010), B.Eng. (Software Engineering and Game Design, McMaster University, 2009). Research interests include: Cyber Security Evaluation & Assurance, Data-Driven Security Metrics, Formal Verification of Security Properties, Secure Software Architecture Design, and Industrial Cyber-Physical Systems Security. His work addresses challenges in threat modeling, compliance with security standards, and mitigating implicit system vulnerabilities. Recognition includes the 2021 New Faculty Excellence in Teaching Award for innovative pedagogy. He actively supervises graduate students in funded research positions. Key collaborations include Health Canada's Scientific Advisory Committee on Digital Health Technologies and the U.S. Department of Homeland Security’s Cybersecurity Postdoctoral Fellowship at Stanford University. Labs/Teams: CyberSEA Lab, focusing on developing rigorous security evaluation frameworks and tools for software-dependent systems.

Michael Weissمشاهده پروفایل

دانشیار

• Open Source Ecosystems
• Technology Innovation Management
• Cybersecurity
• +۴ مورد دیگر

Michael Weiss is an Associate Professor in the Department of Systems and Computer Engineering at Carleton University, affiliated with the Technology Innovation Management (TIM) program. He holds a Dr.rer.nat. (Mannheim) and Dipl.-Ing. (Munich). His research focuses on open source ecosystems, cybersecurity, and innovation management, with over 150 peer-reviewed publications. Weiss chairs conferences like MCETECH and PLoP, and serves on the Hillside Group board. Education: Dr.rer.nat. (Computer Science, 200?), Dipl.-Ing. (Computer Engineering, 200?) Research interests include open source governance, business process modeling, and patterns for collaborative systems. His work bridges technical and organizational aspects of innovation, emphasizing community-driven development and ethical technology use. Recent projects apply topic modeling and machine learning to analyze cybersecurity threats and domain-specific ecosystems. Publications span journals like Technology Innovation Management Review and conferences such as ACM PLoP. Notable contributions include frameworks for license compliance analysis and methodologies for managing remote software projects. Weiss also explores emerging technologies' societal impacts, including AI ethics in education. Advising focuses on graduate students in TIM and Systems Engineering programs. Collaborates with industry on open source security initiatives and contributes to standards through the Hillside Group. Active in innovation education, developing tools like the Community Design Canvas for fostering collaborative problem-solving communities.

Lilian Ngمشاهده پروفایل

استاد

• International Finance
• Corporate Finance
• Environmental Finance
• +۵ مورد دیگر

Lilian Ng is the Professor of Finance and Scotiabank Chair in International Finance at the Schulich School of Business, York University . Her research focuses on international finance, corporate finance, environmental finance, and market integration. She has held this position since at least 1999, as indicated by institutional records. Ng has been recognized for her contributions with numerous awards, including the 2023 Academy of International Business Best Paper Award and the Moskowitz Prize (2019). Her work examines topics such as green innovation under regulatory pressures, voluntary disclosure strategies in conglomerates, and the impact of global outsourcing on corporate transparency. Notable publications include studies on corporate decarbonization, labor voice in governance, and the dynamics of market integration using machine learning. Ng has also secured significant grants, including SSHRC Insight Research Grants for projects on climate change mitigation and pension investment policies. Education: While specific degree details are not explicitly stated, her academic career began at the Sheldon B. Lubar School of Business (1999) and later at the Schulich School of Business. Grants: Principal Investigator for SSHRC grants totaling over $158k, focusing on climate change and pensions. Awards: Over a dozen international recognitions for papers analyzing CSR, market integration, and financial transparency. Her research frequently intersects with policy implications, emphasizing how environmental regulations, global supply chains, and investor behavior shape corporate strategies and market outcomes. She is a leading voice in bridging theoretical finance with real-world applications in sustainability and governance.

Chadi Assiمشاهده پروفایل

استاد

• Wireless Networks
• Information Security
• Cybersecurity
• +۶ مورد دیگر

Chadi Assi is a Professor and Tier II Concordia Research Chair at the Concordia Institute for Information Systems Engineering, Concordia University. His research focuses on wireless networks, information security, and smart grid systems, with particular emphasis on reconfigurable intelligent surfaces (RIS), integrated sensing and communication (ISAC), cybersecurity for electric vehicles (EVs), and machine learning-driven network optimization. He has pioneered work on mitigating cyber-physical attacks in power grids and IoT ecosystems, while advancing cooperative communication protocols like RSMA and NOMA. His technical contributions span theoretical frameworks for energy efficiency maximization in hybrid SDMA/NOMA schemes, low-complexity RIS element selection algorithms, and adversarial PINN models for grid dynamics. He also investigates vulnerabilities in EV charging infrastructure and O-RAN synchronization protocols, proposing robust detection mechanisms like PEACE and Grid Mirror. His interdisciplinary work bridges communications, power systems, and AI, addressing challenges in 5G/6G security and resilient IoT provisioning. Key Research Areas: RIS-enabled ISAC networks, EV cybersecurity, meta-learning in communications, IoT malware analysis Current Projects: Grid resilience against load-altering attacks, Movable antenna optimization, federated learning for AGC systems Recent publications (2024-2025) emphasize deep reinforcement learning frameworks for RIS-aided networks, cooperative RSMA performance enhancement, and defense mechanisms against dynamic trigger-based attacks. He has also developed novel datasets for advanced persistent threats and frameworks like ChargePrint for EV charging security analysis. His work is published in top venues including IEEE Transactions on Smart Grid, IEEE JSAC, and IEEE ICC, reflecting contributions to both theoretical advancements and practical system implementations.

Rachida Dssouliمشاهده پروفایل

استاد

• Software Engineering
• Quality Assurance
• Service Engineering
• +۷ مورد دیگر

Rachida Dssouli is a Professor at the Concordia Institute for Information Systems Engineering (Concordia University). Her research focuses on advanced software engineering methodologies, quality assurance systems, and distributed computing frameworks. She specializes in model-based testing, federated learning optimization, and big data quality management. Her work integrates formal verification techniques with modern machine learning approaches to address challenges in edge computing, IoT, and safety-critical systems. Key research areas include: Development of hybrid swarm intelligence algorithms for optimizing large language model deployment in edge-cloud environments Design of reinforcement learning frameworks for robotics motion planning and IoT device scheduling Creation of interpretable machine learning tools for fault detection in software systems Establishment of holistic big data quality frameworks for continuous monitoring and unstructured data analysis Formal verification methods for avionics systems using multi-agent models Her recent work demonstrates trends toward AI-driven solutions for testing methodologies (e.g., SHAP-Driven fault detection) and edge-cloud integration (e.g., MIMO-based computation offloading optimization). The 2025 publications highlight advancements in federated learning and trust-aware IoT scheduling. Earlier works (2018-2020) emphasize foundational contributions to cloud trust models, big data quality metrics, and safety-critical system testing. Her research also addresses emerging technologies for developing countries through frameworks like neurodegenerative disease monitoring systems and mobile application requirements engineering. She has contributed to service-oriented architectures for healthcare systems and cloud-based resource orchestration strategies.

Arash Mohammadiمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Medical Imaging
• Cybersecurity
• +۴ مورد دیگر

Arash Mohammadi is an Associate Professor at the Concordia Institute for Information Systems Engineering (Concordia University), specializing in artificial intelligence, medical imaging, and cybersecurity. His research focuses on advancing AI-driven solutions in healthcare diagnostics, autonomous systems, federated learning, and edge computing. He supervises graduate programs in Information Systems Security, Electrical and Computer Engineering, and related disciplines. Key research interests include medical image classification using deep learning, reliability of autonomous driving systems, and secure communication in smart grids. His work integrates transformer architectures, Bayesian methods, and graph neural networks to address challenges in healthcare, robotics, and network optimization. Notable contributions include frameworks for lung nodule malignancy prediction, ECG-based emotion recognition, and secure federated learning in resource-constrained environments. Dr. Mohammadi has published extensively in top-tier venues such as IEEE conferences and journals, with a focus on practical applications of AI in healthcare and engineering systems. He actively engages in interdisciplinary projects involving biomedical signal processing, human-computer interaction, and resilience engineering for cyber-physical systems.

Jinqiu Yangمشاهده پروفایل

دانشیار

• Software Engineering
• Automated Program Repair
• Software Testing
• +۴ مورد دیگر

Jinqiu Yang is an Associate Professor in the Department of Computer Science and Software Engineering at Concordia University. His research focuses on software reliability, automated program repair, software testing, and quality assurance of machine learning systems, particularly in autonomous vehicles. He holds a PhD and MASc from the University of Waterloo and a B.Eng. from Nanjing University. Yang has been a tenure-track faculty member at Concordia since 2018, following research roles at IBM Watson and IBM CAS. Research Interests: Automated Program Repair Software Testing Machine Learning Systems Text Analytics of Software Artifacts Mining Software Repositories Autonomous Systems Quality Assurance Key Contributions: His recent work includes detecting concept drifts in ML systems (ICSE-25) and investigating social bias in LLM-generated code (AAAI-25). He leads the O-RISA Lab and has authored over 50 peer-reviewed publications, including distinguished papers at MSR-2018. Yang currently holds grants such as the NOVA FRQNT-NSERC Program (2024-2027) and the NSERC Discovery Grant (2019-2025). Service & Awards: Editorial Board Member of the Empirical Software Engineering Journal (EMSE) and active PC member in top venues like ICSE and FSE. Recipient of the IBM CAS Fellowship and ACM SIGSOFT Distinguished Paper Award. Teaching & Students: He mentors students in Master's and PhD programs, with funding available. His lab focuses on cutting-edge topics like secure code generation and autonomous vehicle reliability.

• Educational Measurement
• Learning Analytics
• Psychometrics
• +۳ مورد دیگر

Guher Gorgun is a Professor affiliated with the Faculty of Education at the University of Alberta, holding a role in the Dean’s Office. Their research focuses on educational measurement, psychometrics, and learning analytics, with a strong emphasis on leveraging machine learning and natural language processing for advancing assessment design and analysis. Key contributions include work on adaptive testing frameworks, automated question generation, and anomaly detection in educational data. Research interests span test-taking engagement dynamics , non-cognitive skill measurement , and data-driven approaches to formative assessment . Recent studies explore the intersection of AI and educational assessment, including LLM applications for item generation and bias mitigation in predictive models. They have published extensively on topics like response time modeling, Bayesian knowledge tracing, and the psychometric evaluation of cross-cultural instruments. Publications highlight innovation in digital assessment analytics, such as behavioral engagement modeling and sequential process analysis. While no formal awards are listed, their prolific output reflects significant contributions to the field of educational measurement. Advising and grant details are not explicitly mentioned, but their research collaborations likely involve interdisciplinary teams focused on educational technology and data science.

Loutfouz Zamanمشاهده پروفایل

دانشیار

• User research in gaming
• Game analytics and data science
• Game evaluation and testing
• +۲ مورد دیگر

Dr. Loutfouz Zaman is an Associate Professor in the Game Development and Interactive Media department at Ontario Tech University , part of the Faculty of Business and Information Technology . He holds a PhD in Computer Science with a focus on Human-Computer Interaction from York University. His research explores visual programming interfaces, game analytics, and extended reality technologies, with a focus on practical applications such as automated bug detection and user experience optimization. Dr. Zaman has collaborated on projects funded by MITACS, NSERC, and industry partners, addressing challenges in healthcare incident management, language learning gamification, and air traffic control simulation training. He teaches courses ranging from introductory game math to graduate-level topics in human-computer interaction and machine learning for game analytics. Education: Bachelor of Science in Computer Science (Software Systems) – Concordia University Master of Science in Computer Science (Human-Computer Interaction) – York University PhD in Computer Science (Human-Computer Interaction) – York University Research Interests: Dr. Zaman’s work spans user research in gaming, game evaluation methodologies, and emerging technologies like AR/VR. His team focuses on developing tools for visual game analytics and automated testing, with recent projects including mixed reality fitness gaming interfaces and deep learning-based bug detection systems. Grants & Collaborations: His industry partnerships include projects on healthcare incident management during pandemics, CRM gamification, and pet identification systems using computer vision. He actively seeks doctoral candidates to expand research in visual analytics, XR technologies, and automated bug detection. Labs & Affiliations: Dr. Zaman is affiliated with the Software and Informatics Research Centre (SIRC) and contributes to the university’s efforts in bridging academic research with real-world applications.

• Evolutionary Computation
• Multi- and Many-Objective Optimization
• High-Dimensional Visualization
• +۳ مورد دیگر

Dr. Amin Ibrahim is an Associate Teaching Professor in the Faculty of Business and Information Technology at Ontario Tech University, specializing in evolutionary computation, optimization, and machine learning. He holds a PhD and MASc in Computer Engineering from Ontario Tech University and a BASc in Computer Engineering from the University of Toronto. His research focuses on multi- and many-objective evolutionary algorithms, high-dimensional visualization, and applying optimization techniques to big data challenges. He has won two Teaching Excellence Awards at Ontario Tech University (2008 and 2018) and contributed to peer-reviewed journals, book chapters, and conferences. Education: PhD in Computer Engineering, Ontario Tech University MASc in Computer Engineering, Ontario Tech University BASc in Computer Engineering, University of Toronto Research interests span evolutionary algorithms, machine learning applications, and optimization-driven solutions for complex systems. Recent work includes electric vehicle infrastructure planning and resilient supply chain design. His articles address multi-objective optimization, risk management, and sustainable transportation. Awards and Honors: Teaching Excellence Award (2008, 2018) Graduate Continuing Scholarship (2008) Graduate Entrance Scholarship (2007) Professional Involvement: Session chair at IEEE World Congress on Computational Intelligence (2016), workshops on cybersecurity and supply chain management, and contributions to IBM CASCON (2008). Active in the Business Analytics & AI Research Group, focusing on transforming data into actionable insights for business decision-making. Teaches courses ranging from cryptography to discrete mathematics and business analytics.

Caroline Palmerمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Music Perception and Production
• Auditory-Motor Synchronization
• +۳ مورد دیگر

Caroline Palmer is a Professor in the Department of Psychology at McGill University and holds the Distinguished James McGill Professorship in Cognitive Neuroscience of Performance. She directs the NSERC-CREATE training grant in Complex Dynamics and is an Associate Member of the Schulich School of Music. Her research focuses on understanding how music influences human behavior, particularly through auditory-motor synchronization, nonlinear dynamics, and temporal coordination in ensemble performance. She explores how rhythmic patterns in music and speech engage attention, memory, and emotion, with applications to social interaction and health. Key research themes include the role of endogenous rhythms in interpersonal synchronization, the physiological effects of musical engagement, and the dynamics of human-machine collaboration. Awards include Fellowship in the Royal Society of Canada. Her work integrates neuroscience, psychology, and computational modeling to explain how music shapes human movement and social connection. Grants and collaborations include leadership in interdisciplinary training programs and partnerships with the Schulich School of Music. She maintains the Sequence Production Lab, investigating neural and behavioral mechanisms underlying skilled performance. Recent studies highlight music's impact on cardiac dynamics, respiratory synchrony, and dyadic coordination in social contexts.

Kai Chanمشاهده پروفایل

استاد

• Ecosystem services
• Environmental policy
• Biodiversity management
• +۶ مورد دیگر

Kai M. A. Chan is a Full Professor and Canada Research Chair (Tier 1) in Re-Wilding and Social-Ecological Transformation at the University of British Columbia (UBC), leading the CHANS Lab. He holds dual appointments in the Institute for Resources, Environment and Sustainability and the Institute for Oceans and Fisheries. His research focuses on interdisciplinary sustainability science, integrating ecology, policy, and ethics to address global environmental challenges. Education: PhD (Ecology & Evolutionary Biology) from Princeton University, MSc from Stanford University, and postdoctoral training at Stanford’s Center for Conservation Biology. He has held visiting roles at UC Santa Barbara and is a Fellow of the Leopold Leadership Program and Royal Society of Canada. Research interests center on social-ecological systems transformation, rewilding, and relational values. He co-leads CoSphere, a global initiative fostering sustainability advocacy. His work bridges natural and social sciences, emphasizing equitable outcomes and ecological restoration. Key contributions include foundational ecosystem services frameworks, transformative change research, and leadership in the IPBES Global Assessment. His lab supports 15+ graduate students and postdocs, focusing on topics like urban biodiversity, climate policy, and conservation messaging. Awards: UBC Killam Fellowship, Clean50 Sustainability Leader, and multiple grants from NSERC/SSHRC. He edits People and Nature and advises governments globally on ecosystems and climate resilience.

Melike Erol-Kantarciمشاهده پروفایل

دانشیار

• AI-enabled wireless networks
• 5G and 6G communications
• Smart grids
• +۷ مورد دیگر

Melike Erol-Kantarci is an Associate Professor and Tier 2 Canada Research Chair in AI-enabled Next-Generation Wireless Networks at the School of Electrical Engineering and Computer Science, University of Ottawa. She is the founding director of the Networked Systems and Communications Research (NETCORE) laboratory. She holds a PhD and has over 140 peer-reviewed publications, with an h-index of 37. Her research focuses on AI-driven wireless networks, 5G/6G communication systems, smart grids, and cybersecurity. Education: PhD in Electrical Engineering (not explicitly stated, inferred from profile). Research interests include AI-enabled wireless networks, smart grids, IoT, and underwater sensor networks. She has received awards such as the 2019 N2Women recognition and IEEE Best Tutorial Paper Award (2017). She serves on editorial boards of IEEE journals and has organized international conferences. Her recent articles emphasize AI applications in 6G networks, secure communications, federated learning, and resource allocation. Key trends include leveraging LLMs for network orchestration, combating adversarial attacks, and optimizing next-gen wireless architectures. Her work on beam selection, ISAC, and RIS-assisted systems addresses critical challenges in 5G/6G. Awards include the Canada Research Chair and best paper recognitions. She actively contributes to open RAN standards and has co-edited books on smart grids and intelligent transportation. Her lab, NETCORE, drives innovation in networked systems.

• Aquatic Conservation
• Fisheries Management
• Ecohydrology
• +۳ مورد دیگر

Mark Poesch, PhD, is an Associate Professor in the Department of Renewable Resources at the University of Alberta, Faculty of Agricultural, Life and Environmental Sciences. His research focuses on aquatic conservation, fish and fisheries management, ecohydrology, and ecosystem modeling. He specializes in freshwater systems, addressing species imperilment through studies on anthropogenic disturbances such as land-use change, hydrologic alteration, climate change, and invasive species. Dr. Poesch’s work spans Canada, including British Columbia, Alberta, Saskatchewan, the Northwest Territories, and Ontario. He develops innovative assessment methods, including functional diversity metrics and habitat connectivity models, and contributes to restoration strategies like habitat offsets. His research integrates field studies, laboratory analyses, and broad-scale data to address conservation challenges. Key Roles: Associate Editor of the Canadian Journal of Fisheries and Aquatic Sciences, member of COSEWIC Freshwater Fishes Subcommittee, and leader in recovery teams for endangered species like the Mountain Sucker and Redside Dace. Education: PhD (specific institution not explicitly stated). Teaching: Teaches courses on fisheries management (REN R 376), directed research (REN R 402A/B), and advanced management strategies (REN R 476/576/771). Community Engagement: Leads initiatives like Tracking Change (indigenous youth engagement) and U School, introducing students to fish biology. His research emphasizes interdisciplinary approaches, combining ecological science with policy and traditional knowledge to address freshwater biodiversity threats. Current projects include assessing Prussian carp invasions, climate change impacts, and habitat mitigation strategies.

Jonathan Hudsonمشاهده پروفایل

دانشیار

• Machine Learning
• Artificial Intelligence
• Evolutionary Computation
• +۲ مورد دیگر

Dr. Jonathan Hudson is an Associate Professor (Teaching) in the Department of Computer Science at the University of Calgary, Faculty of Science. He holds a PhD in Computer Science from the same institution (2019), following an MSc (2011) and BSc (2009) in Computer Science with a minor in Pure Mathematics. His research focuses on improving machine learning and artificial intelligence through evolutionary exploratory testing, emphasizing risk assessment and management. Teaching interests include active learning, formative feedback integration, and scaffolding skills development in problem-solving contexts. Dr. Hudson has received notable awards, including the NSERC Teaching Excellence Award (2020), and has secured grants for pedagogical initiatives such as the AEGIS Rescue Simulator (2025-2028) and Self-Disclosing Chatbots for fostering common humanity in introductory CS classes (2022-2024). He currently teaches courses like CPCS 383 (Explorations in AI/ML) and CPSC 433 (Artificial Intelligence). While unavailable for graduate supervision, he mentors undergraduate capstone and CPSC 502/503 students.