
I am a Ph.D. candidate in Computer Science Department at Columbia University, advised by Prof. Kostis Kaffes. focusing on systems performance and low-latency computing.
My work spans networking, operating systems, and machine learning systems. I have built high-performance software such as Machnet, a kernel-bypass networking framework, and interned at Microsoft Research, where I worked on large-scale infrastructure for data and networking.
I have expertise in C/C++, Rust, CUDA, DPDK, RDMA, eBPF and Linux kernel programming, and my interests lie at high-frequency trading systems and large-scale AI platforms, where reliability and nano/microsecond-scale performance are critical.
Before starting my Ph.D., I built Replicant, a MultiPaxos-based key-value store for strongly consistent cloud replication during a research internship at Penn State, and also gained experience at EPFL, where I worked on distributed systems reliability and failure analysis.
Education
Columbia University, United States
Sep. 2023 - Present (Expected 2027)Ph.D. in Computer Science
Advised by Prof. Kostis Kaffes

Columbia University, United States
Sep. 2023 - 2025M.Sc. in Computer Science

Middle East Technical University, Turkey
2019 - 2023B.Sc. in Computer Engineering
