Find Academic Supervisors

Sandra Cespedes is an Assistant Professor at Concordia University's Department of Computer Science & Software Engineering within the Gina Cody School of Engineering and Computer Science. She previously held roles as an Associate Professor and Head of Research at NIC Chile Research Labs, Universidad de Chile, and maintains an honorary Adjunct Professorship at Universidad Icesi, Colombia. She is also an Associate Researcher at the Advance Center of Electrical and Electronic Engineering (AC3E), Chile. Education: B.Eng. (Telematics Engineering) and Specialization (Management of Information Systems), Universidad Icesi, Colombia (2003, 2007) Ph.D. (Electrical and Computer Engineering), University of Waterloo, Canada (2012) Research Interests: Her research focuses on wireless networks, IoT, vehicular communications, and satellite networking. Key areas include: Design of protocols for constrained IoT devices Vehicular safety systems and cooperative communication Direct-to-satellite IoT (DtS-IoT) architectures Rural connectivity solutions Publications: Her recent work explores satellite IoT protocols, vehicular network optimization, and distributed hypothesis testing. Notable contributions include MAC protocol design for satellite IoT and safety message dissemination in VANETs. Teaching: At Concordia, she teaches undergraduate courses like Data Communications and Computer Networks and Embedded Systems , and graduate courses such as Computer Networks and Protocols . Previously, she taught wireless networking and IoT development at Universidad de Chile.

• Wireless Networks
• Internet of Things (IoT)
• Vehicular Networking
• +6 more

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.

• Software Engineering
• Automated Program Repair
• Software Testing
• +4 more

Tien D. Bui is a Professor in the Department of Computer Science and Software Engineering at Concordia University, Montreal, Canada. He has been affiliated with Concordia for over 30 years, having joined the university in 1984 as a full professor. Previously, he held positions at McGill University and earned his education from Carleton University, the University of Ottawa, the University of Toronto, and York University. His roles include Chair of the Department of Computer Science (1985–1990) and Associate Vice-Rector Research (1992–1996). He currently serves on multiple research boards, including the Board of Governors at Concordia University and editorial roles for journals like the International Journal of Wavelets, Multiresolution and Information Processing. His research focuses on image processing, document analysis, machine learning, and pattern recognition. Notable contributions include work on wavelet-based image segmentation, handwritten document analysis, and applications of sparse representations in texture classification. He has supervised over 20 graduate students and authored/co-authored over 150 publications, including the book Computer Transformation of Digital Images and Patterns (1989). Bui has held visiting positions at the Istituto per le Applicazioni del Calcolo in Rome and the University of California, Berkeley. He has received significant research grants and served on numerous grant selection committees and federal/provincial panels. His work has practical applications in medical imaging, biometrics, and computational fluid dynamics. Current lab members include doctoral and master’s students focusing on advanced topics like control systems and algorithm design. Bui’s academic leadership extends to teaching courses such as Control Systems and Applications, Mathematics for Computer Science, and advanced design and analysis of algorithms.

• Digital Image Processing
• Handwritten Document Analysis
• Signal Processing
• +4 more

Mireille Paquet is an Associate Professor in the Department of Political Science at Concordia University, holding the University Research Chair in Immigration Policies. She directs the Concordia University Institute for Research on Migration and Society (IRMS) and co-directs the RQ3I research network, connecting academic research with Quebec public policy. Education: PhD from Université de Montreal Her research examines comparative immigration policies with focus on bureaucratic influences, political debates around migration technology, and federal-provincial dynamics in Canada. She specializes in Canadian immigration within comparative frameworks including Australia, UK, and US contexts, analyzing how subnational governments shape national migration systems through 'province-building' strategies and evolving selection criteria. Recent publications (2024-2025) reveal intensified focus on intergovernmental complexities in asylum processing, digital migration governance, and Quebec's distinct immigration policy evolution. Her work increasingly addresses racialized immigrant experiences, migration backlogs, and the impact of external shocks like pandemics on policy implementation, demonstrating methodological diversity from survey experiments to comparative institutional analysis. Scientific awards: 2018 Best Book in French Award from the Canadian Political Science Association Member of the College of the Royal Society of Canada Professor Paquet actively supervises graduate students in immigration policy, integration theories, and media-politics intersections. She leads the CFREF-funded 'Bridging Divides' research program and directs multiple inter-institutional collaborations including ERIQA, IRI, and RQ3I. Her policy engagement spans Canadian and international forums, regularly contributing expert commentary to media outlets in both English and French. She directs IRMS while participating in CRIDAQ, BMRC, Weatherhead Research Cluster, and CRIEM, focusing on migrant resilience, intercultural relations, and urban integration. Her research teams bridge academic disciplines and policy sectors, emphasizing knowledge mobilization through the RQ3I network connecting Quebec researchers with policymakers.

• Immigration Politics
• Public Policy
• Federalism
• +4 more

Paul Savary is a Horizon Post-doctoral Fellow and Junior Associate at the Loyola Sustainability Research Centre (LSRC) within Concordia University's Department of Biology. His research focuses on understanding biodiversity patterns through environmental, ecological, and spatial processes, employing graph-theoretical methods. Key projects include analyzing metacommunity structures and urban green space impacts on ecological connectivity. He collaborates with Jean-Philippe Lessard and Pedro Peres-Neto, and his work integrates landscape and genetic data to address ecological connectivity challenges. Research Interests: Paul’s work bridges theoretical and applied ecology, emphasizing graph-based approaches to study dispersal networks, urban biodiversity, and genetic patterns. He explores how landscape features influence species distribution and gene flow in fragmented environments. His projects often involve simulations and spatial modeling tools like Graphab and R's graph4lg package. Publications Highlight: Recent studies (2023–2025) focus on validating graph-based models using genetic and presence-absence data, optimizing landscape resistance metrics, and assessing urban policies for habitat connectivity. These contributions advance methodologies for ecological connectivity analysis in both natural and urbanized landscapes. Awards: No specific awards are listed, though his research aligns with grants supporting ecological sustainability and urban biodiversity initiatives. Advising & Grants: No advising or grant information is explicitly provided. His work is supported through postdoctoral fellowships at LSRC. Labs/Teams: Based at the Loyola Sustainability Research Centre, he contributes to interdisciplinary projects addressing ecological challenges in urban and natural ecosystems.

• Ecology
• Biodiversity Patterns
• Spatial Processes
• +3 more

Andrew Park is an Assistant Professor of Information Systems at the Peter B. Gustavson School of Business, University of Victoria. He holds a PhD and has dual expertise in business and biotechnology, having previously founded and sold a health technology venture. His research focuses on organizational impacts of digital and biotechnologies, innovation ecosystems, and science-based entrepreneurship. He contributes to interdisciplinary journals spanning medicine, engineering, and management. Research interests include cybersecurity leadership, ethical implications of biometric technologies, blockchain applications, and university spin-off innovation. His work bridges management theory with emerging technologies, emphasizing practical implications for firms and economic development. Recent articles explore cybersecurity governance, AI ethics, biometric dignity concerns, and the role of intangible assets in scientific ventures. His award-winning 2022 paper on NFT trust dynamics highlights his focus on digital asset economics. He collaborates in national innovation networks evaluating North American tech ecosystems. No formal grants or labs are explicitly listed, but his entrepreneurial background indicates active industry partnerships.

• Information Systems
• Biotechnology Management
• Personalized Medicine
• +5 more

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.

• Educational Measurement
• Learning Analytics
• Psychometrics
• +3 more

Ruth Milman is an Associate Professor in the Department of Electrical, Computer and Software Engineering at the University of Ontario Institute of Technology. She holds a BASc (Honours Computer Engineering), MASc (Electrical Engineering), and PhD (Electrical Engineering) from the University of Toronto (1995, 1997, 2004 respectively). Her research focuses on advanced control systems, including Model Predictive Control (MPC), systems control theory, nonlinear control, constrained systems, and optimization. She has contributed to adaptive control of electromechanical systems and disturbance rejection in MPC frameworks. Her academic career includes teaching core engineering courses such as Discrete Math, Digital Systems, Probability and Random Signals, Linear Algebra, and Calculus. Her honors include multiple Ontario Graduate Scholarships (1998-2001) and the IEC Everitt Award (1994-1995) for excellence in communications systems. Dr. Milman's publications span over two decades, emphasizing algorithmic advancements in MPC and optimization. Recent work includes non-feasible active set methods for QP subproblems and transient response shaping in control systems. Technical reports highlight her contributions to pressure control and spline-based motor control strategies. Her expertise bridges theoretical control systems with practical engineering challenges, particularly in industrial and electromechanical applications. She maintains an active research agenda with a focus on real-time control systems and system robustness.

• Systems Control Theory
• Model Predictive Control Systems
• Optimization
• +3 more

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.

• User research in gaming
• Game analytics and data science
• Game evaluation and testing
• +2 more

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.

• Evolutionary Computation
• Multi- and Many-Objective Optimization
• High-Dimensional Visualization
• +3 more

Dr. Scott Nokleby is an Associate Dean, Academic and Professor in the Department of Automotive and Mechatronics Engineering at the University of Ontario Institute of Technology. He holds a PhD in Mechanical Engineering from the University of Victoria (2003), and has over two decades of academic leadership and research experience. His primary roles include academic administration and advancing robotics and mechatronics research. Education: PhD (Mechanical Engineering, UVic, 2003), MASc (Mechanical Engineering, UVic, 1999), BEng (Mechanical Engineering with Co-op, UVic, 1997). Research interests focus on advanced robotics topics including parallel manipulators, mobile-manipulator systems, kinematic redundancy analysis, and autonomous systems. His work emphasizes practical applications such as radiation mapping robots, perching drones, and robotic hazard management. Notable contributions include optimal design methodologies for mechanisms and control systems for human-robot interaction. Publications reflect expertise in robotics systems, mechatronics, and nuclear engineering applications. Recent work explores multi-robot task allocation, autonomous navigation, and advanced control algorithms. Awards: Fellow of ASME (2022) Fellow of CSME (2016) CSME Best Paper Award (2014) UOIT Research Excellence Award (2008) CSME I.W. Smith Award (2007) Teaches graduate courses in advanced robotics, mobile robotic systems, and mechanism design. Active in academic administration, he bridges teaching innovation with engineering education through projects like tablet computing integration in design courses. Labs/Teams: Leads robotics research initiatives focused on autonomous systems development, with collaborations spanning nuclear safety, mining automation, and aerospace applications.

• Robotics Engineering
• Mechatronics Systems
• Automation Technologies
• +7 more

Dr. Ahmad Barari is a Professor in the Department of Mechanical and Manufacturing Engineering at the University of Ontario Institute of Technology. He holds a PhD in Mechanical Engineering from Western University (2006), MSc from Sharif University of Technology (1997), and BSc from Amirkabir University of Technology (1995). His research focuses on advanced manufacturing technologies, additive manufacturing, coordinate metrology, surface integrity, and design optimization. He has authored numerous publications and serves on multiple international conference committees. Education highlights include: PhD, Mechanical Engineering, Western University, 2006 MSc, Mechanical Engineering, Sharif University of Technology, 1997 BSc, Mechanical Engineering, Amirkabir University of Technology, 1995 Research interests span Advanced Manufacturing Technologies, Digital Manufacturing, Precision Manufacturing, and FEA-Based Design Optimization. He has contributed to innovations in additive manufacturing processes, surface quality analysis, and computational metrology. His work addresses challenges like measurement uncertainty, surface tribology, and topology optimization. Notable awards include the Best Paper Award at IMS2016 and multiple recognitions as academic advisor for student projects. He actively participates in professional activities such as organizing conference sessions and serving on review panels for NSERC, CFI, and OCE. His professional roles include organizing tracks at ASME, CAD Conferences, and IMECE events, reflecting his leadership in advancing manufacturing research. He also contributes to academic governance through roles like Design Chair for capstone projects.

• Advanced Manufacturing Technologies
• Digital Manufacturing
• Precision Manufacturing
• +7 more

Dr. Angelo J. Canty is an Associate Professor in the Department of Mathematics and Statistics at McMaster University, Canada. His research focuses on computational statistics, genetic data analysis, and resampling methods. B.Sc. (1989) from University College Cork, Ireland M.Sc. (1991) and Ph.D. (1995) from the University of Toronto Postdoctoral work at University of Oxford and EPFL, Lausanne Assistant Professor at Concordia University (1998–2001) before joining McMaster His research spans computational statistics, with key contributions to: Markov Chain Monte Carlo convergence diagnostics Bootstrap and resampling techniques Saddlepoint approximations in statistical inference Efficient algorithm implementation for survey data analysis Genetic data analysis (microarrays, GWAS) His publications highlight a focus on automating convergence assessment (1994–1999), resampling for labor statistics (1999), and saddlepoint approximations in resampling (1996–1999). He developed an influential S-Plus library for resampling methods. Teaching includes: Statistics 4C03/6C03: Generalized Linear Models (Undergraduate/Graduate) Statistics 752: Linear Models and Experimental Design (Graduate)

• Computational Statistics
• Markov Chain Monte Carlo Methods
• Bootstrap and Resampling Techniques
• +4 more

Dr. Katherine Davies is an Assistant Professor in the Department of Mathematics and Statistics at McMaster University. She holds a B.Sc. (2002) and M.Sc. (2004) in Mathematics and Statistics from McMaster, and a Ph.D. in Statistics (2008) from Western University. Prior to joining McMaster, she spent 14 years at the University of Manitoba, where she was promoted to Associate Professor. Her research focuses on statistical theory and modeling, particularly the analysis of lifetime data, censoring methodologies, and distribution theory with applications in engineering and medical sciences. She has supervised multiple graduate students and maintains international collaborations. Dr. Davies teaches undergraduate and graduate courses including Generalized Linear Models, Applied Regression Analysis, and Introduction to Probability. She is an active member of the Statistical Society of Canada and founded the 'Steering Women into Statistics' outreach initiative.

• Statistical Theory and Modeling
• Lifetime Data Analysis
• Censoring Methodologies
• +1 more

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.

• Ecosystem services
• Environmental policy
• Biodiversity management
• +6 more