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Dr. Zhenman Fang is an Associate Professor at the School of Engineering Science , Simon Fraser University (SFU) , where he founded and directs the HiAccel Lab . He also holds an associate membership in the School of Computing Science at SFU. His research focuses on customizable computing with software-defined hardware acceleration , addressing performance, energy-efficiency, and reliability in post-Moore’s law computing across domains like machine learning , big data analytics , quantum chemistry , and precision medicine . Education: Ph.D. in Computer Science from Fudan University (2014), with a visit to University of Minnesota during his studies. Postdoctoral Work: University of California, Los Angeles (UCLA) (2014-2017). Industry Experience: Staff Software Engineer at Xilinx (2017-2019). Dr. Fang’s research spans the entire computing stack , including application characterization , accelerator-rich architecture design , and programming/tool support . He has developed frameworks like HiSpMV , SyncNN , and SQL2FPGA , emphasizing FPGA acceleration for vision transformers , quantum chemistry , and spiking neural networks . His work has been recognized with 3 best paper awards (FPL 2024, TCAD 2019, MEMSYS 2017) and 3 best paper nominees (FCCM 2025, HPCA 2017, ISPASS 2018). Recent publications highlight trends in low-precision machine learning ( ShiftQuant , ESRU ), quantum chemistry acceleration ( SERI ), and vision transformer optimization ( Quasar-ViT ). His HiAccel Lab actively mentors PhD and MASc students , with notable graduates like Alec Lu (PhD 2024, now at Meta) and Philip Stachura (MASc, now with BC Graduate Scholarship). Scientific Awards: Inaugural SFU Research Excellence Award - Horizon Award (2025) FPL 2024 Stamatis Vassiliadis Best Paper NSERC Alliance Award (2020) CFI JELF Award (2019) Xilinx University Program Award (2019) IEEE Senior Member (2023) Grants: NSERC Discovery Grant (2019) CFI JELF Funding (2019) Huawei and Xilinx sponsorships Dr. Fang leads open-source initiatives like SyncNN , PASTA , and SQL2FPGA , and serves as General Chair for ASAP 2025 and Program Co-Chair for RAW 2025 . His lab collaborates globally with institutions such as UCLA , Northeastern University , and Xidian University .

• Customizable Computing
• Heterogeneous Computing
• FPGA Acceleration
• +8 more

Caroline Lemieux is an Assistant Professor at the Department of Computer Science, University of British Columbia (UBC), with research focused on advancing software correctness, security, and performance through innovative testing and synthesis techniques. Her work bridges Programming Languages and Software Engineering , particularly in fuzz testing, specification mining, and program synthesis. PhD from University of California, Berkeley (2021), advised by Koushik Sen Postdoctoral researcher at Microsoft Research, NYC (2021-2022) Key contributions: FuzzFactory , CodaMOSA , Arvada , and Gauss Her research integrates machine learning with traditional testing methods, exemplified by projects like RLCheck (reinforcement learning for test generation) and AutoPandas (neural synthesis for dataframes). Recent publications analyze generator-based fuzzing challenges and propose hybrid strategies combining coverage feedback with AI-driven insights. Scientific Awards : ACM/SIGSOFT Best Paper Award (ESEC/FSE 2019) ACM/SIGSOFT Tool Demonstration Award (ISSTA 2019) ACM/SIGSOFT Distinguished Artifact Award (ISSTA 2019) NSERC Postgraduate Scholarship-Doctoral (PGS D) UBC Governor General's Silver Medal (2016) Teaching roles include: 2025W2: CPSC 539L - Topics in Programming Languages 2024W2: CPSC 410 - Advanced Software Engineering 2023W2: CPSC 410 (with Alex Summers) She supervises graduate and undergraduate researchers working on projects like ExploTest (automated unit test generation) and GRIMOIRE (grammar extraction from pseudo-rules). Her research team collaborates with institutions including Microsoft Research, Google, and academic partners in systems security and AI-driven testing.

• Programming Languages
• Software Engineering
• Fuzz Testing
• +6 more

Jason Foster is an Assistant Professor at the Faculty of Engineering, University of Toronto, specializing in Engineering Education and Philosophy of Engineering . His work bridges rigorous academic inquiry with practical applications in engineering pedagogy. His research focuses on Research Through Design , aiming to redefine how design and education intersect. Key projects include analyzing the utility of design tools in small enterprises, developing coherent engineering requirements models, and creating open-source lab equipment for budget-constrained institutions. Recent publications highlight trends in engineering education, such as integrating multidisciplinary design, flexible project planning, and addressing intersubjective grading dynamics. His work emphasizes interdisciplinary collaboration, sustainable development, and systems thinking in curricula. He supervises graduate students through a junior colleague/collaborator model, prioritizing adaptability and critical engagement. No awards or formal honors are mentioned in the provided texts.

• Engineering Education
• Philosophy of Engineering
• Engineering Design
• +3 more

Mark Crowley is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo , with a cross-appointment in the Cheriton School of Computer Science . He is actively involved in the Waterloo Artificial Intelligence Institute (WAII) , the Waterloo Institute for Complexity and Innovation (WICI) , and serves as National Secretary for the Canadian Artificial Intelligence Association (CAIAC) , coordinating the Canadian Conference on AI . Research interests span the theoretical and applied aspects of Reinforcement Learning , Deep Learning , Manifold Learning , and Ensemble Methods . His work addresses challenges in domains with spatial dynamics, multi-agent systems, and uncertainty, particularly in Computational Sustainability (forest fire management, sustainable forestry), Autonomous Driving , Medical Imaging , and Material Design . Recent research focuses on integrating causal modeling with generative representation learning to improve out-of-distribution robustness in motion forecasting applications. Key publications include foundational work on ChemGymRL environments for safe chemical process reinforcement learning, Generative Causal Representation Learning for robust forecasting, and collaborative work on multi-advisor reinforcement learning in multi-agent settings. He co-authored a textbook Elements of Dimensionality Reduction and Manifold Learning (Springer, 2023) with Prof. Ali Ghodsi and Prof. Fakhri Karray. Teaching includes graduate and undergraduate courses in Algorithm Design , Computational Intelligence , Reinforcement Learning , and Data Modeling at the University of Waterloo since 2018. His research group has produced several notable graduates including Benyamin Ghojogh (2021), who continued as a postdoc until 2022.

• Reinforcement Learning
• Deep Learning
• Ensemble Methods
• +6 more

Dr. Mohamed Hassan is an Assistant Professor in the Department of Electrical & Computer Engineering at McMaster University. His research focuses on Cyber-Physical Systems-on-Chip (iCPSoCs) , emphasizing design, analysis, and deployment for critical domains like Unmanned Aerial Vehicles (UAVs), Autonomous Cars, and healthcare systems. Key research areas include hardware/software codesign, real-time systems, embedded systems, and security. He teaches courses such as COMPENG 4DM4 (Computer Architecture) and COMPENG 4DS4 (Embedded Systems) . His work bridges foundational theories (e.g., scheduling, AI) with infrastructure-level innovations (e.g., compilers, memory systems). The Fanos Research Lab he leads explores interdisciplinary solutions for efficient CPS-on-Chip, addressing challenges in multicore predictability, memory latency, and edge computing. Recent contributions include frameworks for explainable memory-centric workloads and techniques to accelerate TinyML inference. Dr. Hassan serves on Technical Program Committees for conferences like RTAS and OSPERT, highlighting his role in advancing real-time embedded systems research.

• Computer Architecture
• Embedded Systems
• Real-Time Systems
• +12 more

Kay C. Wiese is a Professor and Software Systems Chair at the School of Computing Science, Simon Fraser University. His research focuses on computational intelligence and bioinformatics, particularly RNA secondary structure prediction and visualization. He leads the Bioinformatics Research Lab and has contributed to RNA design and gene finding. Wiese holds a PhD in Computer Science from the University of Regina (1999) and degrees in Computer Science and Mathematics from the Universität des Saarlandes (Germany). He has extensive editorial roles, including Associate Editor for the IEEE/ACM Transactions on Computational Biology and Bioinformatics, and has organized major conferences like the IEEE Symposium on Computational Intelligence in Bioinformatics. His teaching interests include Bioinformatics, Computational Biology, and Discrete Mathematics. Wiese has supervised numerous graduate students, including Boris Shabash, Wenbo Jiang, and Andrew Hendriks. His research group developed tools like jViz.RNA for RNA visualization and SARNA-Predict for structure prediction. His work bridges computational methods with biological applications, emphasizing algorithmic innovation and practical software solutions.

• Bioinformatics
• Computational Biology
• Evolutionary Computation
• +4 more

Melanie Baljko is an Associate Professor in the Department of Electrical Engineering and Computer Science at York University's Lassonde School of Engineering. She directs the Practices in Enabling Technologies (PiET) Lab and participates in graduate programs in Science & Technology Studies, Critical Disability Studies, Digital Media, and Interdisciplinary Studies. Research Focus: Human-centered computing, participatory design, maker methods, assistive technology, augmentative communication, and computer-supported speech therapy Teaching: Graduate courses in critical technical practice and human-computer interaction; undergraduate courses in user interfaces, human-computer interaction, and computer science projects Publications highlight her work in accessible technology for Parkinson's patients, DIY assistive technologies in Kenya, and participatory design frameworks. She collaborates with the University Health Network – Toronto Rehabilitation Institute as an Affiliate Scientist. Key Themes: Accessibility, equity in technical design, and empowering marginalized communities through technology. Recent work examines transit app accessibility, disability inclusion in clinical education, and mixed reality teaching tools.

• Human-centered computing
• Participatory design
• Assistive technology
• +5 more

Professor Ahmed Karmouch is a faculty member at the University of Ottawa's School of Electrical Engineering and Computer Science. He holds a Ph.D. and specializes in advanced networking research, including Network Slicing, Software Defined Networks (SDN), Named Data Networking (NDN), and Cloud Computing. His IMAGINE Lab focuses on developing innovative solutions for autonomic and cognitive networks, emphasizing programmable data planes and in-network computing. Research Interests: Network Slicing Software Defined Networking Named Data Networking Programmable Data Plane Intelligence In-Network Computing Ambient Intelligence & IoT Publications reflect a focus on SDN, NDN, and cloud infrastructure optimization. His work often bridges theory and practical implementation, addressing challenges in network efficiency, reliability, and scalability. Supervised over 30 graduate students, contributing to advancements in edge computing, virtual networks, and autonomic systems. Labs/Teams: Leads the IMAGINE Lab, dedicated to research in mobile autonomic networks, context-aware systems, and future broadband infrastructure. Projects include WiMAX security, policy-based overlay networks, and semantic resource discovery.

• Network Slicing
• Software Defined Networking
• Named Data Networking
• +5 more

Dr. Joshua M. Pearce is a Professor at Western University, holding appointments in the Department of Electrical & Computer Engineering and the Ivey Business School. He is the John M. Thompson Chair in Information Technology and Innovation at the Thompson Centre for Engineering Leadership & Innovation and a Fellow of the Canadian Academy of Engineering. His research focuses on open-source appropriate technology for sustainability and poverty reduction, spanning solar photovoltaics, 3D printing, distributed recycling, and policy analysis. Ph.D. in Materials Engineering from Pennsylvania State University Former Richard Witte Professor at Michigan Tech Editor-in-Chief of HardwareX Author of multiple open-source sustainability books His work integrates engineering, economics, and policy to solve global sustainability challenges. Recent projects include agrivoltaic systems, open-source medical devices, and climate-resilient food production frameworks. He leads the Free Appropriate Sustainability Technology (FAST) research group, which has produced over 200 open-access publications cited in top-tier journals like Renewable and Sustainable Energy Reviews (IF=16.3) and HardwareX (IF=2). Dr. Pearce's scientific contributions include: Fulbright-Aalto University Distinguished Chair Top 0.06% most cited scientist (Elsevier metrics) Leading open-source hardware certification frameworks Developing low-cost scientific instruments His research team includes cross-disciplinary collaborators from Mechanical Engineering, Environmental Science, and Policy Studies. The FAST group emphasizes practical open-source solutions for energy, water, and food security in both developed and low-resource contexts.

• Renewable Energy
• Open Source Hardware
• 3D Printing
• +3 more

Jagath Samarabandu is a Professor in the Department of Electrical and Computer Engineering at Western University. He holds a Ph.D. and M.S. in Electrical Engineering from SUNY Buffalo, and a B.Sc. in Electronics and Telecommunication Engineering from the University of Moratuwa, Sri Lanka. His academic career spans since joining Western University in 2000, with prior post-doctoral experience at SUNY Buffalo and industry work at Life Imaging Systems Inc. Education: Ph.D. Electrical Engineering, SUNY Buffalo M.S. Electrical Engineering, SUNY Buffalo B.Sc (Eng) Electronics and Telecommunication, University of Moratuwa His research focuses on Artificial Intelligence, Machine Learning, Image Analysis, and Cyber Security , with applications in biomedical imaging, network intrusion detection, and civil infrastructure monitoring. He has supervised numerous graduate students working on topics ranging from chromosome analysis to smart grid security. Recent publications highlight his work in medical AI applications (auditory processing disorder diagnosis), industrial time-series analysis (using contrastive predictive coding), and network security frameworks (INSecS system development). He has contributed to 3D ultrasound segmentation, prostate motion compensation algorithms, and synthetic aperture radar systems. Key projects include NSERC-funded intelligent home monitoring systems for elderly care and low-cost synthetic aperture radar development for search-and-rescue applications.

• Artificial Intelligence
• Explainable AI
• Machine Learning
• +5 more

Alexander Tuzhilin is a prominent academic researcher in the fields of recommender systems, personalization, and data mining. His work spans over two decades, focusing on theoretical foundations and practical applications of context-aware recommendations, optimization in data validation, and temporal database systems. He has collaborated extensively with scholars like Gediminas Adomavicius, Konstantin Bauman, and Balaji Padmanabhan. Research Interests: Recommender systems, context-aware computing, temporal database design, and optimization techniques in data mining. Publications: 10+ peer-reviewed articles in journals such as Information Systems Research , Management Science , and INFORMS Journal on Computing , with a focus on algorithmic innovation and business impact. Collaborations: Worked with leading researchers in information systems and operations research, contributing to interdisciplinary advancements in eCRM and data-driven decision-making.

• Recommender Systems
• Personalization
• Data Mining
• +6 more

Rebecca Feldman is an Assistant Professor in Medical Physics and Physics at the Irving K. Barber Faculty of Science, University of British Columbia Okanagan. Her research integrates MR physics, engineering, and medical research to advance MRI pulse sequences and hardware for clinical translation, particularly in neurological disorders. University: University of British Columbia Okanagan Academic Rank: Assistant Professor PhD: University of Western Ontario Research Interests: Dr. Feldman specializes in technical innovation in MRI (accelerated imaging, spectroscopic imaging, non-proton imaging) and translational research applying MRI to neurological disease detection, characterization, and treatment. Her work leverages ultra-high-field (7T) MRI for enhanced resolution of brain structures like hippocampal subfields and perivascular spaces. Publications: Recent work includes advancements in self-supervised medical imaging backbones (MedMAE), segmentation of venous structures in epilepsy, automated MRI pulse design via neural networks, and clinical applications of 7T MRI in neurosurgical planning and psychiatric disorders like major depressive disorder. Teaching: Currently teaches courses in physics, including physics of waves.

• Medical Imaging
• Magnetic Resonance Imaging (MRI)
• Pulse Sequence Design
• +4 more

Dr. Nancy Samaan is an Associate Professor at the School of Electrical Engineering and Computer Science, University of Ottawa. She holds a Ph.D. in Computer Science from the University of Ottawa (2007), along with B.Sc. and M.Sc. degrees in Computer Science from Alexandria University, Egypt (1998 and 2001). Her research focuses on wireless communication, QoS in networks, autonomic networks, and policy-based management, with over 20 publications in refereed journals and conferences. Key achievements include the 2008 NSERC University Faculty Award and recognition for her 2006 paper highlighted in IEEE Wireless Communication magazine. She is an active IEEE member and contributes to advancing network management through innovative solutions like programmable data-plane architectures and machine learning integration. Her recent work emphasizes machine learning applications in networking, programmable data planes, and QoS optimization, reflecting a trend toward intelligent and adaptive network systems. Despite no explicitly listed grants or labs, her publications indicate significant contributions to network autonomy and resource management in dynamic environments.

• Wireless Communication and Mobile Networking
• QoS in Wired and Wireless Networks
• Network Management
• +3 more

Professor Kenneth B. Kent is a full-time academic at the Faculty of Computer Science , University of New Brunswick, holding the Barrett Chair in Entrepreneurship for Digital Transformation and directing the IBM Centre for Advanced Studies - Atlantic. His research focuses on Hardware/Software Co-Design , Virtual Machines , Reconfigurable Computing , and Embedded Systems , with collaborations at the Institute for Visual Computing, Hochschule Bonn-Rhein-Sieg. Ph.D. & M.Sc. - University of Victoria B.Sc. - Memorial University of Newfoundland Kent's work bridges FPGA architecture optimization, cloud computing resource management, and Java virtual machine enhancements. He supervises numerous graduate students including Alireza Azadi (PhD) and Scott Young (MCS), while mentoring alumni like Maria Patrou (PhD) and Konstantin Nasartchuk (PhD). His recent publications (2020-2014) span FPGA modeling ( VTR 8.0 ), garbage collection interference, and workflow-aware storage systems. He teaches advanced topics including Virtual Machines and FPGA CAD , while maintaining technical expertise in runtime optimization and reconfigurable architectures. Outside academia, Kent is known for his 1968 Mustang restoration and extensive cycling adventures across the Greek Islands , Newfoundland, and the Canadian Maritimes.

• Hardware/Software Co-Design
• Virtual Machines
• Reconfigurable Computing
• +7 more

Dr. Eugene Syriani is a Professor at the Department of Computer Science and Operations Research , Faculty of Arts and Sciences , University of Montreal . He leads the GEODES research group and teaches software engineering at undergraduate, Master's, and PhD levels. His work combines Model-Driven Engineering (MDE) and Simulation to improve software engineer productivity and cross-disciplinary system design. Research interests span two axes: (1) Software Engineering focusing on Domain-Specific Languages (DSLs) , Model Transformations , Code Generation , Collaborative Modeling , and Customizable Modeling Environments ; (2) Simulation addressing Digital Twins , Discrete-Event Simulation , and Co-Simulation for applications in agriculture, automotive, and smart systems. His recent work explores AI-assisted modeling and prompt engineering . Key projects include Digital Twins for Vertical Farming (funded by NSERC, MITACS, and industry partners) and Domain-Specific Environments (NSERC Discovery Grant). He has received multiple best paper awards at international MDE and modeling conferences. Scientific contributions include: Best Paper, ACM/IEEE International Conference on Model Driven Engineering Languages & Systems (2023, 2018) NSERC Discovery Grant (2020-2027) Visiting Professor Fellowships (University of L'Aquila, TU Wien, University Cote d'Azur) Guest Editor for Software & Systems Modeling and JOT He supervises 13 graduate students and postdocs, with expertise in DSL development , collaborative modeling , digital twin frameworks , and model consistency . His tools include Gentleman (projectional editor), ReLiS (systematic review tool), and AToMPM (cloud-based modeling environment).

• Software Engineering
• Model-Driven Engineering
• Digital Twins
• +5 more