Deniz Altınbüken
I’m a Research Engineer at Google DeepMind. My work is focused on advancing the state-of-the-art in systems using AI and ML.
Prior to joining Google I received a Ph.D. in Computer Science from Cornell University. During my Ph.D. I focused on building distributed systems that rely on strong foundations in distributed systems Theory. My primary research interests are in machine learning for systems, distributed systems, database systems, and operating systems.
Authored Publications
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Google
Snowcat: Efficient Kernel Concurrency Testing using a Learned Coverage Predictor
Sishuai Gong
Dinglan Peng
Pedro Fonseca
Symposium on Operating Systems Principles (SOSP) (2023)
HALP: Heuristic Aided Learned Preference Eviction Policy for YouTube Content Delivery Network
Zhenyu Song
Kevin Chen
Νikhil Sarda
Eugene Brevdo
Jimmy Coleman
Xiao Ju
Pawel Jurczyk
Richard Schooler
20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23), USENIX Association, Boston, MA (2023), pp. 1149-1163
Snowboard: Finding Kernel Concurrency Bugs through Systematic Inter-thread Communication Analysis
Sishuai Gong
Pedro Fonseca
Proceedings of the 28th ACM Symposium on Operating Systems Principles (2021) (to appear)
Learned Indexes for a Google-scale Disk-based Database
Hussam Abu-Libdeh
Alex Beutel
Lyric Pankaj Doshi
Tim Klas Kraska
Chris Olston
(2020)
