Robert Teather is an Associate Professor and Director at the School of Information Technology , Carleton University . With a PhD in Computer Science from York University (2013) and postdoctoral experience at McMaster University (2015), Dr. Teather specializes in Human-Computer Interaction with focus on 3D user interfaces, virtual reality systems, and game interface design. PhD: Computer Science, York University (2013) Postdoc: McMaster University (2015) His research explores Virtual Reality interaction fundamentals including input device comparison , cybersickness mitigation , and haptic feedback systems. He has developed 3D interface evaluation frameworks for comparing mouse vs 3D tracker inputs, and investigates mobile game control schemes and diegetic display design in gaming contexts. Dr. Teather's recent publications demonstrate focus on VR interaction techniques (58% of recent work), input device evaluation (33%), and mobile XR systems (9%). NSERC Postgraduate Scholarship Ontario Graduate Scholarship Best Demo Award - ACM Symposium on Spatial User Interaction (SUI 2017) Best Paper Honourable Mention - ACM Symposium on Applied Perception 2020 He supervises graduate students in Human-Computer Interaction and Digital Media programs, and leads research in CFI-supported labs exploring shape-changing haptic interfaces and VR scalability frameworks .
John Kildea is an Assistant Professor in the Department of Oncology at McGill University and a Medical Physicist at the McGill University Health Centre (MUHC) Cedars Cancer Centre. He is an associate member of the Medical Physics Unit, Department of Physics, and Department of Biomedical Engineering at McGill University. His work bridges clinical practice, translational research, and education in medical physics. Academic Background: Physics (Queen's University Belfast), Astrophysics (University College Dublin), Postdoctoral Fellowships in Gamma-Ray Astronomy (McGill University, Harvard-Smithsonian Center for Astrophysics) Research Programs: Patient-Centered Health Informatics (Opal patient portal, data donation, mHealth) ROKS (Radiation Oncology Knowledge Sharing: AI in treatment planning, incident learning systems) NICE (Neutron-Induced Carcinogenic Effects: neutron dosimetry, Monte Carlo modeling, DNA damage studies) His research involves collaborations with the School of Computer Science at McGill, Canadian Nuclear Laboratories, the Canadian Nuclear Safety Commission, and Detec Inc. He has supervised 1 postdoc, 4 PhD candidates, 14 M.Sc. students, and 33 undergraduates. Key software projects include Opal (Quebec eHealth award), Depdocs, SaILS, and AEHRA. Funding sources include NSERC, Canadian Space Agency, and Canadian Nuclear Laboratories. Scientific Awards Quebec eHealth solution of 2019 Prix d'excellence–ministers' choice award (highest Quebec healthcare accolade) Trottier-Webster Innovation award (RI-MUHC)
Biography Dr. Kami Vaniea is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, where she leads the Technology Usability Lab in Privacy and Security (TULiPS). Her research focuses on making security and privacy technologies accessible to end-users, developers, and system administrators. Prior to this role, she held positions at the University of Edinburgh (2015–2023) as Reader (Associate Professor) and Indiana University (2014–2015). Education PhD in Computer Science, Carnegie Mellon University, 2012 BSc in Computer Science, Oregon State University, 2005 Research Interests Her work spans cybersecurity, privacy, human-computer interaction, and phishing mitigation. Key areas include: Developer-centered privacy and security practices Phishing detection and user education Smart speaker privacy in multi-user environments Patch management challenges for system administrators Virtual reality applications in authentication systems Affiliations Technology Usability Lab in Privacy and Security (TULiPS) Cybersecurity and Privacy Institute at Waterloo Games Institute and Design Informatics at University of Edinburgh Teaching She teaches courses such as ECE 458 (Computer Security) and ECE 750 (Special Topics in Computer Software), emphasizing practical cybersecurity principles and emerging threats. Grants and Projects Her projects include funded research on phishing mitigation strategies, smart speaker privacy, and developer education in privacy-by-design. She collaborates internationally on initiatives like the REPHRAIN Center for Privacy and Online Influence.
Adam Fourney is a Senior Principal Researcher at Microsoft Research's Human-AI eXperiences (HAX) group in Redmond. He holds a Ph.D. and M.Math. from the University of Waterloo and a B.Sc. from the University of Ottawa. His work focuses on AI agents collaborating with humans to complete complex tasks, including projects like AutoGen and Magentic-One. He previously studied web search, intelligent assistants, and information systems at the University of Waterloo. Education: Ph.D. (Computer Science), University of Waterloo M.Math. (Computer Science), University of Waterloo B.Sc. (Computer Science), University of Ottawa His research interests span Human-AI collaboration, multi-agent systems, AI ethics, and AI-assisted programming. He explores how AI systems can support human tasks while addressing challenges like uncertainty, communication breakdowns, and alignment with human goals. His work bridges technical innovation with user-centered evaluation, emphasizing real-world usability and societal impact. His recent articles highlight advancements in interactive AI debugging, alignment of AI tools with human needs, and leveraging search data for public health insights. Notably, he received a Best paper honorable mention at CHI 2024 for work on AI-assisted programming costs. Adam has collaborated extensively with researchers across Microsoft and academia, contributing to open-source tools like AutoGen Studio and foundational studies in human-LLM interactions. His interdisciplinary approach combines technical rigor with insights from user behavior and social dynamics.
Dr. Ryan Grant is an Assistant Professor in the Department of Electrical and Computer Engineering at Queen’s University, Canada. He leads the Computing at Extreme Scale Advanced Research (CAESAR) lab and is affiliated with the Ingenuity Labs Research Institute. His expertise spans cloud computing, high-performance networks, low-level hardware-software interfaces, and energy-efficient supercomputing systems. Dr. Grant holds a PhD from Queen’s University (2012) and previously worked at Sandia National Laboratories (2012–2021), where he contributed to critical supercomputer communication protocols now deployed globally. He has authored over 80 peer-reviewed articles and received prestigious awards including the R&D100 Award and Queen’s University’s 125th Engineering Alumni Award. His research emphasizes advancing Canada’s supercomputing infrastructure to support AI, climate science, and national security applications. Education: PhD in Computer Engineering, Queen’s University (2012) MSc in Computer Engineering, Queen’s University (2005) BSc in Computer Engineering, Queen’s University (2004) Research Interests: Dr. Grant’s work focuses on optimizing supercomputing architectures for extreme-scale systems, with an emphasis on: High-performance networking and MPI communication protocols Power/energy management in HPC systems AI-driven network traffic prediction and resource disaggregation GPU-accelerated computing and cloud infrastructure integration National sovereignty in supercomputing for sensitive applications (e.g., defense, healthcare) Awards & Recognition: R&D100 Award (Oscars of Research) U.S. Defense Programs Awards Public Good Innovator Award Queen’s University 125th Engineering Alumni Award Grants & Labs: Dr. Grant directs the CAESAR lab, one of the world’s leading supercomputing architecture research groups. His work is supported by grants from Canadian and international agencies, focusing on sovereign supercomputing and HPC-AI convergence. Labs/Teams: CAESAR Lab (Queen’s University) Ingenuity Labs Research Institute
Sudhir Mudur is Professor in Computer Science and Software Engineering at Concordia University. His research spans computer graphics, vision, augmented/virtual reality, and deep learning with applications in geometric modeling and 3D interaction. Recent work develops neural cloth deformation techniques, personalized visual dubbing systems, and differentiable subdivision surfaces. Mudur has held positions internationally including at INRIA France and Michigan State University, and chaired Concordia's department since 2007. He contributes to graphics standards and has managed R&D projects across academic and industry settings.
Amir H. Chinaei is an Associate Professor and Department Chair at the Department of Electrical Engineering & Computer Science at York University . He holds a Ph.D. in Computer Science from the University of Waterloo (2007), an MSc in Software Engineering from Amirkabir University of Technology, and a BSc in Software Engineering from Isfahan University. Ph.D. in Computer Science (University of Waterloo, 2007) MSc in Software Engineering (Amirkabir University of Technology) BSc in Software Engineering (Isfahan University) His research focuses on Computer Science Education , Access Control Models , Data Security , and Information Visualization . His publications emphasize security frameworks, privacy preservation in social media/health systems, and access control transitions to modern paradigms. He received the Teaching Excellence in Computer Science award at the University of Toronto and has coached over 100 students in developing information systems. His recent publications span topics from WordPress security to biometric authentication in healthcare. Teaching Excellence in Computer Science (University of Toronto) Additional contributions include curriculum development for software engineering programs, work-integrated learning initiatives, and projects like Decentralized Privacy Preservation in Social Networks and Biometric Access Control for e-Health Records .
Dr. Alvine Boaye Belle is an Assistant Professor in the Department of Electrical Engineering & Computer Science at Lassonde School of Engineering, York University. She leads the DARE! research group and serves on multiple international committees, including ICSE and RE conferences. Her work bridges software engineering with equity, diversity, and inclusion (EDI) initiatives. PhD in Software Engineering (École de Technologie Supérieure, University of Quebec) 2-year Industrial Postdoctoral (University of Ottawa) Graduate Diploma in Public Administration & Governance (McGill University) Dr. Belle's research focuses on system assurance for autonomous systems, generative AI applications in software engineering, and EDI in computing . She applies machine learning to safety case automation and vulnerability detection, as shown in her publications with high-impact journals. Her recent work explores deep learning and SVM models for Android malware detection with 99% accuracy. She mentors a diverse group of students across Bachelor's, Master's, and PhD levels, emphasizing accessibility and social impact in technology. Keynote speaker at Black History Month events Moderator of EDI-focused panels at ICSE conferences Editorial board member for journals like IEEE Software and Information and Software Technology
Gias Uddin is an Associate Professor in the Electrical Engineering and Computer Science department at York University's Lassonde School of Engineering. He also holds an Adjunct Professor position at the University of Calgary. Previously, he served as an Assistant Professor at the University of Calgary from 2020 to 2023. Dr. Uddin's research lies at the intersection of software engineering (SE) and artificial intelligence (AI), with specific focus areas including the assessment of AI trustworthiness using SE (SE4AI) and improving the productivity of software and knowledge professionals using AI-enabled software assistants. His work spans three key domains: Democratized Data Science (HCI → AI4DS, SE4DS), Modernized Software Issue Management (HCI → AI4SE), and Usable Cybersecurity Engineering (HCI → AI4CE). He is particularly interested in how AI can democratize the adoption of machine learning techniques across stakeholders during ML systems development. His recent publications demonstrate a strong focus on practical applications of AI in software engineering, with particular emphasis on detecting hallucinations in LLMs, improving API documentation, and developing AI-assisted tools for software issue management. His research has resulted in numerous publications at top-tier software engineering conferences including ICSE, ASE, and FSE. Distinguished paper award at FSE 2025 for work on hallucination detection in LLMs York University Research Award (2025) IBM Champion recognition for 2024 and 2025 CAS Project of the Year Award at IBM TechXChange 2024 Multiple NSERC-funded research grants Dr. Uddin has successfully secured multiple research grants including an NSERC Discovery Grant, NSERC Alliance International Catalyst Grant on 'Hallucination Detection in LLMs using Metamorphic Testing,' and several industry-funded projects with IBM. He has supervised numerous graduate students who have gone on to successful careers in both academia and industry, with many receiving prestigious scholarships and awards. As the founding director of the Data Intensive Software Analytics (DISA) Lab, he leads a team focused on developing innovative AI-assisted tools for software developers and data scientists.
Dr. Marzieh Ahmadzadeh is an Associate Professor (Teaching Stream) at the Department of Electrical Engineering & Computer Science, York University. She holds a Ph.D. and MSc in Information Technology (Software Engineering) from the University of Nottingham, UK, and a BSc in Computer Engineering from Isfahan University. A certified Professional Engineer (P.Eng.) in Ontario, she has held academic positions at Shiraz University of Technology, University of Toronto, and University of Georgia, USA before shifting her focus to education research in 2015. Education: Ph.D., Information Technology (Software Engineering), University of Nottingham (2006) MSc, Information Technology (Software Engineering), University of Nottingham (2002) BSc, Computer Engineering, Isfahan University Her research intersects Computer Science Education and Human-Computer Interaction , with a focus on Applied Data Mining for educational analytics and security applications. She has published in prestigious venues like ACM SIGCSE, IEEE Transactions, and Future Generation Computer Systems. Recent publications demonstrate expertise in: Exam design and cognitive load optimization Ransomware detection in fog computing environments Breast cancer survivability modeling with imbalanced data Gender preferences in e-commerce UX design Academic integrity analysis in programming education
Song Wang is an Associate Professor in the Department of Electrical Engineering and Computer Science at York University's Lassonde School of Engineering. He joined York University as an Assistant Professor in July 2019 and was promoted to Associate Professor in May 2024. He serves as an Associate Editor of ACM Transactions on Software Engineering and Methodology (TOSEM) and has established himself as a prominent researcher at the intersection of Software Engineering and Artificial Intelligence. Dr. Wang earned his Ph.D. in Computer Engineering from the University of Waterloo in December 2018 under Prof. Lin Tan. He received his MS degree from the Chinese Academy of Sciences in June 2014 under the supervision of Prof. Ye Yang, Prof. Wen Zhang, and Prof. Qing Wang. His undergraduate education includes a BE in Software Engineering and a BHRM in Human Resource Management from Sichuan University in June 2011. Prior to academia, he gained industry experience through internships at Microsoft Research, Morgan Stanley Capital International, Yahoo, and Baidu, and co-founded a startup named QualDivine. Dr. Wang's research focuses on two main directions: (1) leveraging AI technologies to address software reliability challenges (AI for SE), and (2) developing software reliability assurance techniques for AI systems (SE for AI). His recent work has particularly focused on how Large Language Models can optimize and reshape software testing practices. His research has practical impact, with tools and techniques that have detected hundreds of true bugs in real-world software systems. His work spans multiple application areas including mobile testing, fuzz testing, and functional testing. His recent publications (2024-2025) demonstrate a strong focus on the intersection of AI and software engineering, with significant contributions in automated vulnerability detection, API recommendation, bias analysis in generated code, and mobile application testing. His research combines empirical studies with innovative technical approaches, often involving benchmarking and systematic literature reviews to establish foundations for future work. He has published over 60 papers in prestigious IEEE/ACM Software Engineering journals and flagship conferences, with over 2,600 citations. Dr. Wang has received four best paper awards: a Distinguished Paper Award at APSEC'23, an ACM Distinguished Paper Award at ICPC'22, an ACM Distinguished Paper Award at ICSE'20, and a Best Paper Award at PROMISE'19. He was recognized as one of the top-10 most impactful early-career researchers in Software Engineering by the Journal of Systems and Software in 2020 and received the TOSEM Distinguished Reviewer Award in 2023. Dr. Wang currently supervises multiple PhD and Master's students including Mohammad Abdollahi, Haoran Xue, Jiho Shin, Nima Shiri Harzevili, and Moshi Wei. He has successfully guided several students to complete their theses, including Reem Al Eithan (Master's thesis defense in April 2025), Moshi Wei (PhD thesis defense in April 2025), and Nima Shiri Harzevili (PhD thesis defense in February 2025). His research group has received funding from various sources to support their work on software engineering and AI. Dr. Wang leads an active research group focused on AI and software engineering at York University. His team includes PhD students, Master's students, and research assistants working on various projects related to software testing, reliability, and AI applications in software engineering. The group has developed tools that have detected hundreds of true bugs in real-world software systems, with some findings documented in Jira issues and GitHub repositories across numerous open-source projects.
Dr. Ellen Balka is a Professor in the School of Communication at Simon Fraser University (SFU) and Associate Dean in the Faculty of Communication, Arts and Technology. Her work focuses on the design and implementation of health information technologies, emphasizing equity, patient safety, and participatory design. She leads the Assessment of Technology in Context Design Lab (ATIC Lab), which explores the human dimensions of technological systems. Her research has secured over $7 million in grants, including major funding from CIHR and MSFHR. Key projects include the ActionADE initiative, which aims to reduce preventable adverse drug events (ADEs) through improved cross-setting communication. Education Ph.D. (Interdisciplinary: Communications, Computer Science, Women’s Studies), Simon Fraser University (1991) M.A. (Women’s Studies), Simon Fraser University (1987) B.A. (Geography and Environmental Studies), University of Washington (1981) Research Interests Health Information Technologies and Policy Participatory Design and Social Informatics Gender and Technology Studies Patient Safety and Adverse Drug Events Awards & Grants Paz Buttedahl Career Achievement Award (2025) CIHR Partnership in Health System Improvement Grant ($1.2M+) MSFHR and BC College of Pharmacists Funding Labs & Projects ATIC Lab : Investigates human-technology interactions and participatory design. ActionADE : Develops software to prevent repeat ADEs through PharmaNet integration.
Georgiy Krylov is an Assistant Professor at the Faculty of Computer Science, University of New Brunswick. He holds a PhD from UNB (2024), and master's and bachelor's degrees from Nazarbayev University (2018 and 2016). His research focuses on high-performance computing, compilers/runtime environments, FPGA CAD, and quantum/reversible computing. Education: PhD in Computer Science, University of New Brunswick (2024) MSc in Computer Science, Nazarbayev University (2018) BSc in Computer Science, Nazarbayev University (2016) Research Interests: His work spans compiler optimization, quantum circuit design, FPGA applications, and ahead-of-time (AOT) compilation techniques. He explores geometric refactoring for quantum circuits, heterogeneous logic implementations, and GPU acceleration in genetic algorithms. Publications Trends: Recent work emphasizes AOT compilation frameworks (e.g., Eclipse OMR), quantum computing optimizations, and FPGA-based CAD tools. Earlier studies focused on GPU-accelerated algorithms for quantum circuit synthesis. Grants/Advising: No specific grants or advisees listed. Active in open-source compiler toolchains and hardware-software co-design projects.
Dr. Waqar Haque is a Full Professor at the University of Northern British Columbia (UNBC), cross-appointed between the Department of Computer Science (Faculty of Science and Engineering) and the School of Business (Faculty of Business and Economics). He has been a key academic figure at UNBC since 1995. PhD in Computer Science from Iowa State University MSc in Computer Science from Iowa State University MSc in Mechanical Engineering from the University of Alberta Dr. Haque’s research focuses on advanced data analytics , business intelligence , parallel and distributed computing , and visual analytics , with applications in healthcare. His work bridges theoretical exploration and industrial collaboration, leading to software commercialization. He has received the Industrial Collaborative Research award BC Top Innovation award and secured grants from NSERC and SSHRC. Dr. Haque leads the Business Intelligence Research Group (BIRG) and contributes to UNBC’s Research Computing Management Board and Health Research Institute (HRI) Leadership Council. He supervises graduate students in MSc Computer Science , MSc Business Administration , and Health Sciences programs but is currently not accepting new graduate students.
Jonathan Anderson is an Associate Professor at Memorial University of Newfoundland's Faculty of Engineering and Applied Science. He holds a B.Eng. and M.Eng. from Memorial University (2006, 2008) and a PhD from the University of Cambridge (2012). His research focuses on computer security, privacy, operating systems, and the hardware/software interface. He is a contributor to the FreeBSD operating system, particularly its Capsicum sandboxing framework, and maintains securityconferences.net . Anderson's work includes the development of the CHERI capability model and the TESLA security logic assertions framework. He has held postdoctoral roles at Cambridge before returning to Memorial in 2014. His honors include the IEEE Canada–Telus Innovation Award and the Rothermere Fellowship. His research spans secure operating systems, cryptographic protocols, and distributed systems. Key contributions include advancements in sandboxing technologies, secure storage systems, and blockchain applications for data integrity. Anderson actively participates in academic workshops and conferences, contributing to the field of security protocols and system design.
