Find Academic Supervisors

Mohammad ShahradView profile

Assistant Professor

• Cloud Computing
• Sustainability
• Large-Scale Computing Systems
• +3 more

Mohammad Shahrad is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of British Columbia (UBC) and an Associate Faculty Member of UBC's Computer Science Department. He leads the UBC Cloud Infrastructure Research for Reliability, Usability, and Sustainability (CIRRUS) Lab. His research focuses on sustainable and efficient large-scale computing systems, particularly in cloud resource management and serverless systems. Education: Ph.D. in Electrical Engineering, Princeton University (2020) M.A. in Electrical Engineering, Princeton University (2016) B.Sc. in Electrical Engineering, Sharif University of Technology, Tehran (2014) Research Interests: Shahrad's work emphasizes energy-efficient cloud computing, serverless architecture optimization, and sustainability in distributed systems. His projects address challenges like carbon footprint reduction, resource allocation, and cold-start delays in serverless platforms. He employs interdisciplinary approaches, combining system design, algorithm development, and empirical analysis to tackle real-world cloud infrastructure problems. Recent Contributions: His research trends include carbon-aware scheduling, geospatial shifting for sustainability, and developer-centric compliance tools for serverless applications. These efforts aim to balance performance, cost, and environmental impact in modern cloud ecosystems. Scientific Awards: Community Award at USENIX ATC '20 for Serverless in the Wild: Characterizing and Optimizing the Serverless Workload at a Large Cloud Provider Advising & Grants: As CIRRUS Lab lead, Shahrad mentors researchers in cloud infrastructure and sustainability. While specific grant details are not listed, his work reflects substantial industry collaboration (e.g., Microsoft Research, Azure). Labs/Teams: The CIRRUS Lab focuses on creating sustainable cloud solutions through open-source frameworks like OpenPiton and collaborative industry partnerships.

Nick HarveyView profile

Professor

• Theory of Machine Learning
• Randomized Algorithms
• Convex Optimization
• +3 more

Dr. Nick Harvey is a Full Professor in the Department of Computer Science at the University of British Columbia (UBC), with an affiliation to the Department of Mathematics. He leads the Mathematics of Information, Learning and Data (MILD) research cluster. His research focuses on randomized algorithms, machine learning theory, and convex optimization, with notable contributions to algorithm design and analysis. Harvey has taught courses such as Randomized Algorithms (CPSC 436R/536N), Theory of Computing (CPSC 421), and Advanced Algorithms (CPSC 420). He has received prestigious awards including the NeurIPS 2018 Best Paper Award and the CS-Can/Info-Can Outstanding Young Research Prize (2014). His work emphasizes probabilistic techniques in algorithms, including applications in graph theory, streaming algorithms, and privacy-preserving methods. Harvey supervises graduate and undergraduate students, contributing to their academic and professional development. His research group explores cutting-edge topics in algorithmic theory and machine learning, with ongoing projects in algorithmic fairness, optimization, and data science. Key achievements include advancing the Lovász Local Lemma, developing efficient graph sparsification techniques, and pioneering work on the complexity of matrix completion. Harvey's teaching philosophy prioritizes clarity and rigor, reflected in his award-winning pedagogy. He actively engages in academic service, including curriculum development and conference organization.

• Operating Systems
• Storage Systems
• Programming Languages
• +3 more

Norman C. Hutchinson is an Associate Professor in the Department of Computer Science at the University of British Columbia (UBC), within the Faculty of Science. He specializes in operating systems, storage systems, programming languages, computer communications protocols, and virtual machine monitors. His research emphasizes scalable distributed systems, storage efficiency, and virtualization technologies. Teaching Hutchinson teaches courses such as CPSC 110 (Computation, Programs, and Programming), CPSC 210 (Software Construction), CPSC 313 (Computer Hardware and Operating Systems), and CPSC 317 (Introduction to Computer Networking). His teaching spans foundational to advanced topics in computer science, reflecting his expertise in systems and networking. Awards and Recognition UBC Computer Science Undergraduate Team Award (2011) CS Department Teaching Award Faculty of Science Achievement Award USENIX Symposium on Networked Systems Design and Implementation Award Research Focus Hutchinson’s research explores scalable storage systems , virtual machine replication , and distributed protocols . Notable projects include SPEX (scalable publish/subscribe systems), Innesto (searchable key-value stores), and Remus (high-availability virtual machine replication). His work addresses challenges in consistency, performance, and reliability in distributed environments. Grants and Labs His research is supported by grants focusing on cloud storage, distributed systems, and virtualization. He collaborates with industry and academic partners to advance practical solutions for modern computing challenges.

Trevor HallView profile

Professor

• Photonic Networks
• Optoelectronics
• Fiber Optics
• +4 more

Trevor Hall is a Professor and University Research Chair in Photonic Circuits & Integration at the University of Ottawa's School of Electrical Engineering and Computer Science. Previously, he held positions at King's College London, including Professor Emeritus in Optoelectronics. He earned his BA and MA from Cambridge University and his PhD from University College London. His research focuses on photonic networks, optoelectronic systems, and integrated photonics, with over 200 publications and five patents. Key areas include fiber optics, electromagnetic scattering, and optoelectronic signal processing. He has led industry-academic collaborations and contributed to strategic planning in academic leadership roles. Dr. Hall has served on numerous national and European research councils, including EPSRC and DTI committees, and held leadership roles in academic and community institutions. His honors include Fellow of the UK Institute of Physics and Chartered Engineer status. Current projects emphasize photonic packet switches and high-capacity optical communication systems. His work integrates advanced photonics with emerging technologies like 6G and blockchain, addressing challenges in high-speed data transmission and system stability. Collaborations span industrial partners such as Fujitsu, Qinetiq, and Nortel.

Burak KantarciView profile

Professor

• Internet of Things (IoT)
• AI-based Security
• Vehicular Networks
• +6 more

Dr. Burak Kantarci is a Full Professor at the School of Electrical Engineering and Computer Science, Faculty of Engineering, University of Ottawa. He holds a University Research Chair in AI-Enabled Secure Networking for Smart Critical Infrastructures and a courtesy faculty appointment at Clarkson University. His research focuses on IoT, AI-based security, vehicular networks, and edge computing. Education and Career: Previously an Assistant Professor at Clarkson University (before joining University of Ottawa) and a Research Fellow at University of Ottawa (2009–2014). He is a Professional Engineer (P.Eng) in Ontario. Research Interests: Includes continuous authentication, communication models for big data, crowdsensing, and vehicular sensing. He leads the NEXTCON-SCVI Labs and has published over 200 peer-reviewed works. Articles Trends: Recent work emphasizes AI-driven security solutions, autonomous systems safety, and 5G/6G networking challenges. Topics include adversarial detection, UAV optimization, and edge computing efficiency. Awards: Distinguished Lecturer (IEEE Communications & Systems Societies), ACM Distinguished Speaker, Senior Member (ACM/IEEE). Grants & Advising: Principal Investigator on NSERC/CFI/NSF-funded projects. Advises on grants focused on smart infrastructure and secure networking. Labs/Teams: Founder of NEXTCON-SCVI Labs, focusing on communications, computing networks, and smart vehicles innovation.

Timothy Christian LethbridgeView profile

Professor

• Software Engineering
• Artificial Intelligence
• Machine Learning
• +3 more

Timothy Christian Lethbridge is a Professor of Software Engineering and Computer Science at the University of Ottawa, where he has held roles including Vice-Dean (Governance) and Acting Associate Dean. His research focuses on software engineering tools, model-driven development (notably the Umple project), and education. He earned his PhD in Computer Science from the University of Ottawa (1994) and earlier degrees from the University of New Brunswick. Research Interests: Complexity Reduction in Software Engineering Modeling Tools (e.g., Umple for state machines and class diagrams) Enterprise Architecture in Education Software Engineering Education Usability and Human-Computer Interaction in Software Tools Large Language Models in Assurance Cases Awards and Memberships: Fellow of the Canadian Information Processing Society (CIPS) Professional Engineer (P.Eng) Senior Member of IEEE and ACM Teaching and Students: Supervised over 30 graduate students, currently advising Abdulaziz Algablan, Aliaa Alghamdi, and Emmanuel Celestine Ayeleso. Teaches courses like Software Engineering Capstone (SEG4910/11) and Software Usability (CSI5122). Labs: Leads the CRuiSE Lab, focusing on software engineering and usability research.

Hussein MouftahView profile

Professor

• Telecommunication Networks
• Optical Networking
• Wireless Communication Networks
• +5 more

Hussein Mouftah is a Distinguished University Professor and Tier 1 Canada Research Chair at the University of Ottawa , affiliated with the School of Electrical Engineering and Computer Science (formerly SITE). He has made groundbreaking contributions to telecommunication networks , including optical, wireless, and IoT systems, while pioneering research in smart grids and connected autonomous vehicles . B.Sc. and M.Sc. from University of Alexandria (1969, 1972) Ph.D. from Laval University (1975) Academic career: Queen's University (1979–2002), University of Ottawa (2002–present) His research spans computer networks , optical networking , wireless communications , and smart city technologies , with recent work focusing on 6G-enabled ITS, vehicular edge networks, and dynamic wireless charging for UAVs/CAEVs. Publications highlight machine learning integration and cybersecurity challenges in IoT/autonomous systems. Key awards include the Royal Society of Canada Thomas W. Eadie Medal , IEEE McNaughton Gold Medal , and 24 Best Paper Awards . He has secured ~$40M in grants and mentored 95 Master’s, 63 Ph.D.s, and 30 postdocs.

Amir H. RazaviView profile

Professor

• Machine Learning
• Natural Language Processing (NLP)
• Cybersecurity
• +3 more

Amir H. Razavi is a part-time Professor in the School of Electrical Engineering and Computer Science at the University of Ottawa. He holds a PhD in Machine Learning and NLP from the same institution (2012) and a Master's in Computer Software Engineering from the University of Tehran. His career spans over a decade of industry experience as a senior data scientist and team lead in Big Data analytics across cybersecurity, telecommunications, and financial sectors with companies like Bell Canada and BlackBerry. His research focuses on applying ML and NLP to cybersecurity (e.g., threat detection, DLP), behavioral analysis, fraud detection, and maritime risk mining. His academic contributions include over 25 peer-reviewed publications in venues like IEEE conferences and journals, with a focus on DNS-based cybersecurity, social network analysis, and NLP applications in healthcare and psychology. He has also managed large-scale enterprise projects in fraud management and customer care within telecommunications. Education: PhD in Machine Learning & NLP, University of Ottawa (2012) MSc in Computer Software Engineering, University of Tehran Research interests span: • ML-driven cybersecurity solutions (e.g., DNS exfiltration detection) • NLP applications in healthcare diagnostics and dream analysis • Privacy-preserving data models and risk assessment frameworks • Hybrid machine learning systems for adaptive learning and recommendation engines Labs/Teams: Collaborations include BlackBerry and Bell Canada on CTI projects, and interdisciplinary work with psychologists on dream sentiment analysis. Active contributor to ResearchGate with 17,304 reads and 1,668 citations.

• Nanotechnology
• Quantum Computing
• Atom Scale Fabrication
• +4 more

Robert Wolkow is a Professor in the Department of Physics at the University of Alberta, holding the iCORE Chair of nanoscale Information and Communication Technologies. He leads the Hybrid Nano-Electronic Systems program at the National Institute for Nanotechnology and serves as Chief Technical Officer of Quantum Silicon Inc. His research focuses on atom-scale fabrication, quantum computing, and ultra-low-power electronics. Wolkow has pioneered techniques in atomic-scale device manufacturing using scanning probe microscopy and hydrogen lithography. Education: BSc (Waterloo, 1982), PhD (Toronto, 1987). Postdoctoral training at IBM Yorktown Heights and AT&T Bell Laboratories preceded his senior roles at the National Research Council of Canada. He has held leadership positions including Scientific Director of the Hitachi electron microscopy product development Centre. Research interests emphasize atomic-scale engineering of silicon surfaces, including dangling bond logic systems, quantum dots, and nanoelectronic devices. His work bridges fundamental physics with applied technologies like quantum computing and nanofabrication automation. Recent publications highlight advancements in editable atomic-scale devices, charge defect simulations, and machine learning-driven nanoscale manufacturing. Wolkow’s innovations include the first atomic-scale transistor and methods for precise atomic positioning. His labs integrate scanning tunneling microscopy, nanomanipulation, and computational modeling to explore silicon’s quantum and electronic properties at the atomic limit. Collaborations span academia and industry, driving applications from quantum sensors to next-generation computing architectures.

• Applied Electromagnetics
• Wireless Communications
• Antenna Design
• +5 more

Dr. Xingqi Zhang is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Alberta, Canada. He holds adjunct professorships at University College Dublin (Ireland) and has held visiting positions at the University of Toronto and Queen Mary University of London. His research focuses on applied electromagnetics and wireless communications, emphasizing high-performance computational models for 5G/6G/THz systems, intelligent transportation, underwater communications, IoT, and biomedical applications. Education: B.Sc. (Honors) from Harbin Institute of Technology, M.A.Sc. and Ph.D. from the University of Toronto. Research interests include physics-based wireless channel modeling, radio wave propagation in diverse environments, multiphysics modeling for electromagnetic and biomedical systems, reconfigurable intelligent surfaces (RIS), antenna design, and machine learning applications in communications. He leads a Horizon 2020-funded project on future wireless networks and collaborates with global academia and industry. Awards: ACES Early Career Award, RIA Charlemont Award, and multiple best paper awards. He serves as an associate editor for IEEE journals and technical committee roles in flagship conferences. Teaching: Currently teaches ECE 209A/B (Fundamentals of Electrical Engineering) in 2025 terms. His group oversees projects in channel modeling, integrated sensing/communication, and machine learning-based parametric modeling.

• Educational Measurement
• Psychological Testing
• Automatic Item Generation
• +5 more

Dr. Mark J. Gierl is a Professor of Educational Psychology at the University of Alberta's Faculty of Education, holding the Tier 1 Canada Research Chair in Educational Measurement. His research focuses on automatic item generation (AIG), assessment engineering, and psychometric methods for evaluating test translation. He authored the 2021 book Advanced Methods in Automatic Item Generation , co-authored with Hollis Lai and Vasily Tanygin. His work integrates cognitive modeling, automated test assembly, and multilingual automated scoring systems. Education: PhD in Educational Psychology from the University of Illinois Urbana-Champaign (College of Education). Research interests include large language model applications in assessment, AIG for medical and science education, and cross-linguistic scoring frameworks. Key contributions include developing AIG systems for secure testing and validation frameworks for generated items across disciplines. Research highlights: Over 50 peer-reviewed articles on topics like neural semantic analysis for video assessment, automated bone loss measurement in dentistry, and LLM-driven reading comprehension item generation. His work emphasizes ethical AI integration in educational measurement, test security, and multilingual assessment equity. Awards: Holder of the prestigious Tier 1 Canada Research Chair since 2021. His work bridges advanced computational methods with foundational psychometric principles to revolutionize modern testing practices.

Marina GavrilovaView profile

Professor

• Machine Learning
• Biometric Security
• Image Processing
• +4 more

Marina Gavrilova is a Professor and Associate Head (Research and Strategic Planning) in the Department of Computer Science at the University of Calgary. Her research focuses on biometric security, machine learning, pattern recognition, and interdisciplinary computational sciences. She is a co-founder of the Biometric Technologies Laboratory and the SPARCS laboratory, and serves as Founding Editor-in-Chief of Springer's Transactions on Computational Sciences. Her work spans ethical AI frameworks, multimodal biometric systems, and healthcare applications. Dr. Gavrilova holds Senior ACM and IEEE membership statuses and has received prestigious awards including the Canada Foundation for Innovation Grant and the University of Calgary’s U Make a Difference Award. Her editorial roles include positions with IEEE Transactions on Computational Social Sciences, IEEE Access, and multiple biometrics journals. Her research explores emotion-aware de-identification systems, trustworthy AI, and bias mitigation in healthcare machine learning. Key contributions include advancements in generative adversarial networks, fusion strategies for multimodal data, and computational methods for medical imaging. She advocates for ethical AI practices and interdisciplinary collaboration to address societal challenges in security and privacy. Lab affiliations include the Biometric Technologies Lab and SPARCS Lab, which focus on computational security and interdisciplinary research. Ongoing work emphasizes social behavioral biometrics, autonomous systems, and AI-driven healthcare solutions.

Rei Safavi-NaeiniView profile

Professor

• Information-Theoretic Security
• Quantum-Safe Cryptography
• Distributed Ledger System Security
• +3 more

Rei Safavi-Naeini is a Professor in the Department of Computer Science at the University of Calgary. She is a Fellow of the International Association for Cryptologic Research (IACR) and held former leadership roles as Co-Founder and Director of the Institute for Security, Privacy and Information Assurance (ISPIA) until December 2018. Previously, she served as a Professor and Director of the Telecommunication and Information Technology Research Institute at the University of Wollongong, Australia. Educational Background: PhD in Electrical Engineering from the University of Waterloo, Canada. Her research focuses on information-theoretic security, quantum-safe cryptography, distributed ledger systems, cloud security, and IoT security. She has over 400 peer-reviewed publications and has held editorial roles at IEEE Transactions on Information Theory, ACM Transactions on Information and System Security, and others. She has chaired major conferences such as Crypto 2012 and ACNS 2013. Awards include prestigious chairs in information security and recognition as an IACR Fellow. She has contributed to academic leadership through roles in research institutes and editorial boards.

• Data Privacy
• Computer Science Education
• Academic Integrity in STEM
• +3 more

Leanne Wu is an Associate Professor (Teaching) in the Department of Computer Science at the University of Calgary. She holds a PhD (2020), MSc (2010), and BSc (2003) from the same institution. Her work bridges technical computer science with pedagogical innovation and societal impact. Research focuses on three pillars: 1) Data Privacy (with emphasis on contextual integrity and interdisciplinary definitions), 2) Computer Science Education (designing curricula to enhance metacognition, project-based learning, and academic integrity), and 3) Data Science applications supporting experiential learning. Notable projects include a Teaching & Learning Grant-funded study on academic integrity attitudes in CS, and a nuclear energy news analysis capstone with Jason Donev. Publications span 20 years, reflecting early work in database performance (2002-2009) to recent innovations in education technology (2019+) and nuclear science communication (2024). Recent articles emphasize ethical AI use and learning analytics. Awards: Anita Borg Scholarship (2012), Grace Hopper Faculty Scholarship (2021) Advising includes supervising Hannah Ku's privacy & aging tech project and capstone collaborations. She does not currently supervise thesis-based graduate students. Labs/Teams: Active in university strategic initiatives around Energy Innovation and Human Dynamics. Collaborates on interdisciplinary projects linking CS education with nuclear science and humanities.

Arvind MagesanView profile

Professor

• Econometrics
• Political Economy
• Industrial Organization
• +3 more

Arvind Magesan is a Professor of Economics at the University of Calgary's Faculty of Arts, Department of Economics. He holds a PhD from the University of Toronto (2011) and has been at the University of Calgary since 2010, advancing through academic ranks including Associate Professor (2015–2021) and Graduate Director (2017–2019). His research focuses on econometrics, political economy, and industrial organization, with a particular emphasis on electoral dynamics, political violence, and structural modeling. Education includes a B.A. (Honours) in Economics from the University of Calgary (2004), an M.A. in Economics from the University of Western Ontario (2005), and a PhD in Economics from the University of Toronto (2011). His work has been published in top journals such as the Review of Economic Studies , American Political Science Review , and American Economic Journal: Policy . He has received SSHRC grants totaling over $160,000 for research on topics like non-state armed groups and electoral barriers. Research interests span econometric methodologies applied to political economy problems, including the link between electoral politics and violence in developing countries. His recent work examines candidate selection by political parties and the impacts of social security reforms on retirement decisions. He has advised numerous graduate students and teaches advanced courses in econometrics and structural modeling. Awards: SSHRC Grants, University of Calgary GREAT Supervisor Award, Superior Teaching Awards Grants: SSHRC Insight Grants (2019–2028), SSHRC IDG Enhancement Award Dr. Magesan has presented at major international conferences, including the American Political Science Association and European Economic Association meetings. His research bridges theoretical econometrics with applied problems in political and industrial organization.