Niv Dayan

Niv Dayan is an Assistant Professor in the Department of Computer Science at the University of Toronto, holding this position since 2023. His research focuses on designing efficient data structures and algorithms for modern hardware, with applications in databases, cryptography, machine learning, and virtual reality. He collaborates closely with industry partners to bridge theoretical advancements to real-world systems.

Education: PhD in Computer Science (IT University of Copenhagen, 2015), MSc in Software Development (IT University of Copenhagen, 2012), BSc in Computing and Economics (University of Dundee, 2010). Prior to his faculty position, he held roles as a Research Scientist at Pliops (2019–2022) and postdoctoral researcher positions at Harvard (2015–2019) and Copenhagen University (2022).

Research Interests: Data structures for modern hardware, LSM-trees, key-value stores, probabilistic filters (e.g., Bloom, Cuckoo), and adaptive storage systems. His work emphasizes practical implementations and rigorous experimentation, addressing challenges in scalability, efficiency, and robustness.

Teaching: Instructors for courses CSC443/CSC2234 (Database System Technology) and CSC2525 (Research Topics in Database Management), emphasizing hands-on projects, paper presentations, and research-oriented learning. Courses require strong programming skills in C/C++, Rust, or Java.

Awards: Received the Best of SIGMOD 2017 award for the paper Monkey: Optimal Navigable Key-Value Store. His work has been cited as one of the best four papers at conferences, reflecting its impact on database systems research.

Lab and Collaborations: Leads a research lab focused on advancing database system fundamentals. Collaborates with industry on projects like Pliops' storage solutions and startup partnerships to ensure practical relevance of his research.