I am a PhD candidate in Computer Science at the University of Illinois at Urbana-Champaign, advised by Ravishankar K. Iyer. I am affiliated with the DEPEND research group at the Coordinated Science Laboratory. My research aims to improve the performance, resilience, and ease of management of large-scale heterogeneous computer systems.
I am particularly interested in applying ML to challenging problems within the design and management of computer systems. My dissertation research has demonstrated the application of domain-knowledge (i.e., knowledge about software and hardware architecture) as an inductive bias to ML techniques to solve a variety of systems problems, including heterogeneous resource management, secops, distributed failure detection and triaging, and testing and resilience assessment.
- May 31, 2020 Our paper on domain-knowledge guided reinforcement learning for scheduling tasks across CPUs, GPUs, and FPGAs has been accepted at ICML 2020.
- Mar 4, 2020 Our paper on intelligent malware targeting autonomous vehicle safety has been accepted at DSN 2020.
- Oct 29, 2019 Our DSN 2019 paper was featured on CSL News, Science Daily, Daily Illini, EurekAlert, Sina, and Guancha.cn.
- Apr 22, 2019 Our NSDI 2019 paper was featured on CSL News.
- Mar 4, 2019 Our papers on using Bayesian methods to perform targeted fault injection and model fault propagation in AI-driven systems have been accepted at DSN 2019.
Publications [Full List: Publications, Projects]
ASAP: Accelerated Short Read Alignment on Programmable Hardware.
IEEE Transactions on Computers.
- Best Paper Award
Efficient and Scalable Workflows for Genomic Analyses.
DIDC 2016 (Colocated with HPDC 2016).