CSE Colloquium: Building Fast and Robust Data and Storage Systems in Milli-/Micro-second Era

Abstract: As the need for real-time data surges, storage systems, the home of data, are facing a significant challenge of maintaining performance sustainability and offering low and stable response times. With intricate structure and emerging storage hardware, our systems become more vulnerable to tail latencies, which can cause bad user experience and severe revenue loss, highlighting the necessity for new technologies. In this talk, I will introduce my view on how to redesign our hardware-software co-stack to tackle this challenge from multiple angles, and eventually make our data and storage systems “tail-free”. 

Biography: Mingzhe Hao is a Ph.D. candidate in the Department of Computer Science at the University of Chicago. His research interests are in combining heuristics methods and machine learning techniques to build solutions for various systems, such as storage systems, operating systems, and cloud/distributed systems. Specifically, he builds fast and robust systems that achieve rapid responses even in the most turmoil scenarios. 

He publishes his work in conferences such as ASPLOS, FAST, OSDI, SOSP, and SoCC. Some publications he is involved in are nominated for the best paper awards for their potential impacts. Meanwhile, his expertise has allowed him to serve as a reviewer/external reviewer for conferences and journals including FAST, JPDC, TC, and TOS. Also, as a recognition of his academic merit, he has received multiple honors/awards including Siebel Scholar (class 2020), William Rainey Harper Dissertation Fellowship, Elastos Fellowship, and Facebook Fellowship Finalist. 

 

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Event Contact: Bhuvan Urgaonkar

 
 

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The School of Electrical Engineering and Computer Science was created in the spring of 2015 to allow greater access to courses offered by both departments for undergraduate and graduate students in exciting collaborative research fields.

We offer B.S. degrees in electrical engineering, computer science, computer engineering and data science and graduate degrees (master's degrees and Ph.D.'s) in electrical engineering and computer science and engineering. EECS focuses on the convergence of technologies and disciplines to meet today’s industrial demands.

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