Ahmed Alquraan wins 2026 Cheriton Distinguished Dissertation Award

Rising distributed systems researcher Ahmed Alquraan has received the 2026 Cheriton Distinguished Dissertation Award.

Since 2019, this annual award recognizes outstanding doctoral research at the Cheriton School of Computer Science and includes a $1,000 prize.

“Ahmed is a superstar,” says his supervisor, Professor Samer Al-Kiswany. “His research represents an exceptional combination of intellectual novelty, technical depth, and real-world impact. It has redefined core assumptions in distributed systems, influenced industry-scale production platforms, and advanced the state of the art in fault tolerance, consensus, and cloud infrastructure.”

Ahmed was recognized for his thesis, Leveraging Emerging Data Center Technologies to Build High-Performance Data Stores, which also earned him second place in the 2026 Faculty of Mathematics Doctoral Prize. He is also the recipient of various national and international awards, including the 2019 Huawei Prize for Best Research Paper, an IBM PhD Fellowship, a Fields Postdoctoral Fellowship, and a Canada Postdoctoral Research Award.

Under the mentorship of his supervisor, Professor Samer Al-Kiswany (left), Ahmed Alquraan (right) conducted research that has influenced both academia and industry, including production systems at Microsoft and Oracle.

“I am deeply honoured to receive the Cheriton Distinguished Dissertation Award,” says Ahmed, who graduated in 2025. “My PhD research explored the systems that power modern cloud computing, including the protocols that keep services available during network failures, the consensus algorithms behind replicated databases, and the resource-management techniques used by large cloud providers.”

“It has been especially meaningful to see my research extend beyond the dissertation, influencing production systems and being taught in graduate-level courses. I am grateful to my advisor, Samer Al-Kiswany, for his guidance and support throughout this journey, and to my collaborators at UWaterloo, Microsoft, and Oracle.”

At the start of his PhD, Ahmed led an in-depth study of 136 network-partitioning failures across 25 widely used distributed systems, including file systems, messaging systems, and in-memory data structures. Notably, this work challenged key assumptions about network failures. For example, he found that 88% of failures can occur when a single node is isolated, urging network practitioners to prioritize top-of-rack switch failures, which were overlooked. Moreover, many practitioners assumed that eliminating client access would lower failures. However, his team found that most failures involved minimal to no client access. The team concluded their paper by introducing the Network Partitioning Testing (NEAT) framework, an open-source testing system.

This research, published at the USENIX Symposium on Operating Systems Design and Implementation, was widely praised for its industrial impact. For example, his team found flaws in the design of five common techniques, including scheduling, discovery service, and replication. They also identified a vulnerability to catastrophic failure in a common Zookeeper deployment approach and malpractice in Microsoft’s network maintenance procedures that aggravates the impact of network faults. Beyond the industry, this research was taught at several top-tier universities, among them Harvard University, the University of Michigan, and Johns Hopkins University. 

Ahmed also identified major bottlenecks in state-of-the-art replicated storage systems, which store copies of data across multiple machines to keep services available even when some machines fail. He and his co-researchers found that state-of-the-art designs struggle to fully leverage multicore machines. A key limitation is their reliance on a log of operations to coordinate replicas and track and order every operation in the system. This log becomes a major scalability bottleneck, limiting throughput and increasing latency.

This research culminated in LoLKV, the first logless and linearizable storage system. Instead of logs, LoLKV relies on per-key operation tracing to achieve linearizability. Ahmed and his collaborators have found that LoLKV has almost ten times higher throughput and up to 92% lower tail latency than other state-of-the-art storage systems. These findings were published at the 2024 USENIX Symposium on Networked Systems Design and Implementation.

Ahmed capped off his doctoral research by building efficient and reliable cloud computing systems. For example, he developed DROPS, a resource management system for serverless functions. DROPS uses a novel statistical analysis of historical execution traces to allocate resources efficiently while meeting performance requirements. Tech giant Microsoft Azure has adopted and deployed DROPS in their production, serving thousands of clients across the globe and handling millions of requests per day. It has even reduced Azure’s infrastructure costs by tens of millions of dollars. This research was published at the 21st European Conference on Computer Systems.

Next is Slogger, a new disaster recovery system that leverages modern data centre time synchronization hardware and protocols. It can reduce the data loss window by 50% compared with the traditional approach, incremental snapshotting, which only captures and stores data changes since the last backup. Ahmed created Slogger in collaboration with Oracle, who patented it.

Overall, Ahmed’s research helped advance and transform cloud computing systems, one of the major cornerstones of modern-day technology. From preventing network failures, including system crashes, to enhancing data recovery systems like phone back-ups, Ahmed’s lifelong work can help millions of users, right at their fingertips.