The Systems & Networks Group (SysNet) is part of the Department of Computer Science at the University of Toronto. We work on projects that cover a diverse range of experimental and theoretical research across computer systems, networks, databases & data structures, security & privacy, machine learning & AI Systems and more. Below we summarize each category and our specialized focus in each.
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Focus on design and optimization of modern computer systems, from architecture to operating systems. We study large-scale and reliable computing infrastructures, memory systems, compilers, and runtime adaptation. Our work spans mobile and pervasive computing, stream processing, and performance-driven systems analysis to build efficient, scalable, and adaptive computing environments.
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Investigate the theory and practice of computer networking, focusing on data center networking, software-defined networks (SDNs), and congestion control. Our work also examines the structure and dynamics of large-scale social, economic, and computer networks, aiming to improve connectivity, scalability, and data flow in modern distributed systems.
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Our research addresses the full spectrum of data management, from the theoretical foundations of data structures to large-scale data processing systems. We design efficient, hardware-conscious data structures and explore new approaches for managing, querying, and analyzing massive datasets. We also focus on bridging cloud data processing & data center networks to address hyperscale data processing, and the intersection of databases and big data analytics.
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We focus on securing computing systems across the stack, from microarchitectural security to machine learning systems to interpersonal technology abuse, while also focusing on data privacy, applied cryptography and aiming to build secure and trustworthy computing environments.
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We also focus on the intersection of systems and artificial intelligence, where we develop efficient and secure infrastructures for large-scale machine learning, and visual computing. Our work targets performance, scalability, and reliability in ML systems, spanning topics like hardware acceleration, ML for systems optimization, robotics, and computer vision applications.
Highlights
Our Seminar Series
Check out the Systems @ UofT Seminar Series which is a monthly seminar series in computer systems, organized by our group.
Our Team
Our team is made up of faculty, postdoctoral researchers, graduate students, research assistants and staff.
Our News
A great way to learn about our work is to see how it’s making an impact. Browse or search our latest news and announcements.