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Dr. Abdelkader Ouda is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Western Ontario, with over three decades of experience in academia and the software industry. He holds a Ph.D. in Computer Science from Western University (2005), an M.Sc. in Computer Science and Pure Mathematics from Ain Shams University (1993), and a B.Sc. (Hons) in the same disciplines from Ain Shams University (1986), graduating with the highest honor (96.80%). His research spans information security, cryptography, network security, big data security and privacy, and data analytics . He leads the Information and Computer Networks Security (iCNS) Research Laboratory, focusing on innovative solutions for IoT, fog–cloud computing, and behavioral biometrics. His recent work includes developing the ADG Engine for synthetic data generation and HSM4SSL for intra-domain security. Dr. Ouda’s publications highlight advancements in authentication protocols, lightweight IoT security frameworks, database benchmarking, and machine translation . His industry experience includes 14 years in software development, project management, and system analysis, which he integrates into his teaching of courses like Software Design, Algorithms & Data Structures, and Information Security. He also contributes to engineering accreditation through the CEAMS application. Key trends in his articles include secure communication in hybrid architectures, energy-efficient IoT protocols, and reinforcement learning for continuous authentication . His work bridges academic theory with practical applications, emphasizing efficiency and scalability in modern computing environments.

• Information Security
• Cryptography
• Network Security
• +9 more

Dr. Swati Mishra is an Assistant Professor at McMaster University's Faculty of Engineering, Department of Computing and Software, specializing in Human-Computer Interaction , Machine Learning , and Explainable AI . With 9 years of industry experience and a PhD in Information Science from Cornell University, she focuses on designing interactive AI systems for healthcare, computational journalism, and museum engagement. PhD: Cornell University (Bloomberg Data Science Fellowship) MSc: Computer Science (Cornell), Human-Computer Interaction (Indiana University) Her research explores Machine Teaching , Concept-Based Explanations , and Human-Centered AI , with publications in ACM SIGCHI, CSCW, UMAP, and IEEE VIS. Her lab develops tools to bridge human cognitive models with AI systems, emphasizing transparency and usability. Recent projects include: Risk Analysis Dashboard for FDA clinical trial documentation Gestural interaction systems for museums Interactive Transfer Learning tools She has received a Best Paper Award at ACM SIGCHI and held industry roles in AI product development. Contact: mishrs23@mcmaster.ca | Personal Website | Office: ABB C-531

• Human-Computer Interaction
• Artificial Intelligence
• Machine Learning
• +5 more

Matthew Brehmer (he/him) is an Assistant Professor in the School of Computer Science at the University of Waterloo, where he joined in Fall 2024. He leads the Ubiquitous Information Experiences (UBIX) research group, focusing on human-computer interaction and data visualization. Prior to Waterloo, Brehmer was a lead researcher at Tableau and a member of the EPIC HCI research group at Microsoft Research. Brehmer's research spans data visualization, human-computer interaction, and ubiquitous information experiences , with particular emphasis on spatial computing, multimodal interaction, and data storytelling. His work explores innovative ways to communicate and collaborate around data through techniques like gesture recognition, augmented reality video presentations, and novel timeline visualization approaches. He has pioneered techniques such as Diatoms for generative design inspiration and TimeSplines for flexible timeline authoring. His recent publications reveal a growing focus on spatial computing interfaces and multimodal data communication , particularly through projects like Tableau for visionOS and Tableau Gestures. His research increasingly bridges the gap between physical and digital spaces for data interaction, with applications in remote collaboration, presentation techniques, and expressive data storytelling. Scientific Awards: IEEE VIS Test of Time Award (2023) for 'A Multi-Level Typology of Abstract Visualization Tasks' IEEE VIS Best Paper Award (2023) for TimeSplines ACM UIST Best Paper Honorable Mention (2022) IEEE VIS Best Paper Honorable Mention (2018) for Charticulator Brehmer actively contributes to the visualization community through service roles including the IEEE VIS Executive Committee (2022-2026), Maryland Institute College of Art Data Analytics and Visualization MPS Advisory Panel (2023-2026), and as Publications Chair for the IEEE Computer Society Visualization and Graphics Technical Community Executive Committee (2022-2025). He has served on program committees for IEEE VIS, ACM CHI, Computation + Journalism, and Information+ conferences. Brehmer directs the UBIX research group (ubixgroup.ca), which focuses on ubiquitous information experiences through projects exploring spatial computing, gesture recognition, and novel interaction techniques for data visualization. The group recently developed Tableau for visionOS and RemixTape, a presentation authoring tool for narratives about metrics/KPIs.

• Human-Computer Interaction
• Data Visualization
• Ubiquitous Information Experiences
• +3 more

Stéphane Bedwani is an Associate Professor in the Department of Physics and an Assistant Professor-Researcher in the Department of Radiology, Radiation Oncology and Nuclear Medicine at the University of Montreal. He also serves as a Medical Physicist in the Department of Radiation Oncology at CHUM (Centre Hospitalier de l'Université de Montréal). His interdisciplinary work bridges physics, engineering, and clinical medicine with a focus on advancing radiation therapy techniques. Dr. Bedwani's educational background includes a Master of Science (M.Sc.) and Doctor of Philosophy (Ph.D.), though specific institutions and years are not mentioned in the provided text. His academic career demonstrates strong integration between theoretical physics, biomedical engineering, and clinical applications in radiation oncology. Dr. Bedwani's research interests focus on several key areas in medical physics and radiation oncology. His primary research focuses on dual-energy computed tomography (DECT) applications for quantitative imaging and radiation therapy planning, particularly in assessing pulmonary function. He has developed innovative approaches using 3D printing technology to create patient-specific radiation therapy devices, including the "Montreal split ring applicator" for gynecological brachytherapy. His work also explores real-time monitoring techniques for mobile tumors and methods to improve cardiac sparing in left breast cancer radiation therapy . Dr. Bedwani's research bridges the gap between advanced imaging techniques and practical clinical applications to improve patient outcomes in radiation oncology. Analysis of Dr. Bedwani's publication record reveals a strong emphasis on translating engineering solutions to clinical radiation oncology problems. His research demonstrates a clear progression from fundamental imaging physics to practical clinical applications, with particular focus on dual-energy CT techniques, 3D printing applications in radiation therapy, and functional lung imaging. His work often involves interdisciplinary collaboration between physicists, engineers, radiation oncologists, and other medical specialists. Dr. Bedwani leads research initiatives focused on the Imaging and Engineering axis at CRCHUM (Centre de recherche du Centre hospitalier de l'Université de Montréal). His laboratory work emphasizes the development and validation of novel imaging techniques and medical devices for radiation therapy. He collaborates with a multidisciplinary team including medical physicists, radiation oncologists, engineers, and computer scientists to advance precision radiation therapy techniques. His current projects include optimizing 3D-printed patient-specific devices for brachytherapy, developing quantitative imaging biomarkers for radiation-induced lung injury, and improving functional imaging techniques for treatment planning.

• Medical Imaging
• Radiation Oncology
• Biomedical Engineering
• +6 more

Philippe Doyon-Poulin is an Associate Professor in the Department of Mathematics and Industrial Engineering at Polytechnique Montréal, specializing in human factors engineering and user experience design for complex systems. With extensive industry experience from Bombardier Aerospace (2013-2019), he contributed to the design and certification of flight decks for the CSeries (now A220) and Global 7500 aircraft, conducting over 500 hours of usability testing with pilots in flight simulators. His educational background includes a Doctorate in Industrial Engineering from Polytechnique Montréal (2014), a Master's in Applied Sciences in Industrial Engineering from the same institution, and a Baccalaureate in Physics with specialization in numerical computing from Sherbrooke University. Doyon-Poulin's research centers on cognitive engineering of man-machine systems, with particular focus on user interface design for aviation, healthcare, and industrial applications. His work bridges theoretical human factors principles with practical implementations in real-world contexts, especially in the evolving landscape of Industry 4.0 and digital transformation. He investigates how visual clutter affects performance, how to design effective touch interfaces under vibration conditions, and how to optimize human-system interaction for safety-critical environments. His recent publications demonstrate a strong trajectory across multiple domains including aviation human factors (touchscreen interfaces under vibration), healthcare systems (pediatric ICU decision support), and industrial applications (predictive maintenance systems). The research shows increasing interdisciplinary collaboration, particularly in healthcare applications and human-centered AI development for Industry 5.0 contexts. Doyon-Poulin actively supervises graduate students, with seven Master's theses and two PhD dissertations completed in 2022-2023 alone. His students' work spans aviation interfaces, mining equipment maintenance systems, medical decision support tools, and virtual reality applications for human factors evaluation. His research has attracted media attention, particularly regarding cockpit design for future aircraft and applications of his work in healthcare during the pandemic. He leads research projects that often involve building test environments for human performance evaluation, such as the customizable touchscreen testing bench developed by his Master's student Adam Schachner, which simulates cockpit vibration conditions. His laboratory work bridges theoretical human factors research with practical applications in industry settings.

• User-centered design
• Usability
• User experience (UX)
• +4 more

Nicholas Rhinehart is an Assistant Professor at the University of Toronto, holding primary appointments in the Institute for Aerospace Studies and cross-appointments in the Department of Computer Science and Robotics Institute. He leads the Learning, Embodied Autonomy, and Forecasting (LEAF) Lab, focused on developing autonomous systems that operate safely in complex environments through advancements in reinforcement learning, imitation learning, and deep learning. His research bridges robotics, computer vision, and AI to create efficient algorithms for autonomous decision-making. Education: Ph.D. in Robotics from Carnegie Mellon University (2014–2019), M.S. in Robotics (2013–2014), and B.S. in Engineering and B.A. in Computer Science from Swarthmore College (2008–2012). Prior to academia, he was a Senior Research Scientist at Waymo Research (2022–2024), a Postdoctoral Scholar at UC Berkeley’s RAIL Lab (2019–2022), and held research internships at NEC Labs, Uber Advanced Technologies Group, and Berkeley. Research Interests: His work emphasizes autonomous systems, reinforcement learning, imitation learning, and generative models for 3D scene forecasting. Recent publications explore diverse topics like residual reward models, traffic prediction, and social navigation using deep learning techniques. Labs/Teams: PI of the LEAF Lab, which develops foundational algorithms for embodied autonomy and forecasting in robotics and AI.

• Robotics
• Artificial Intelligence
• Machine Learning
• +3 more

Steven Enns serves as a Lecturer at East Carolina University, listed under the faculty directory with the title "Cs Instructor" despite his documented work centering on industrial and product design rather than computer science. His professional profile emphasizes creative projects including furniture and functional object design. His research and creative interests focus on Product Design , Industrial Design , Craft Design , 3D Printing Applications , and Leatherwork . These are evidenced through projects like the Flux Stool (2013) which creates visual tension through "organized chaos" while maintaining structural integrity, the 3D Printed Lamp (2013) that reimagines mass-produced lighting through customizable open-source models, and Hand and Sew Leather Goods (2012) involving handmade wallets and accessories developed from personal experimentation into small-scale production. No scientific awards or honors are documented in his profile. There is no information regarding student advising, research grants, or laboratory and team affiliations, with the directory explicitly noting "No courses currently associated with this person" and "No interests have yet been listed".

• Product Design
• Industrial Design
• Craft Design
• +2 more