I am generally interested in Systems, in particular, Distributed System and Operating Systems. My current research focuses on improving the reliability of cloud control planes such as Kubernetes.
I received my B.S. Computer Science from University of Wisconsin-Madison. During my undergraduate time, I was an undergrad Research Assitant in Paradyn Tools Project group at UW-Madison, advised by Prof. Barton Miller. I also worked with Prof. Earlence Fernandes on an adversarial ML project.
Improving the reliability of cloud control planes by developing automatic testing techniques for controllers/operators in cluster management systems (e.g. Kubernetes/Openshift).
Understanding challenges of migrating applications from VMs to containers. Improving the reliability of applications deployed on Kubernetes.
Develop Self-Propelled Instrumentation engine which is capable of instrumenting before and after function calls. Design trace generation using Self-Propelled Instrumentation engine. Develop visualization method for program traces in order to support recent Vulnerability Assessment.
Explore physical robust Adversarial Machine Learning attacks on real-world commercial ADAS (Advanced Driver-Assistance Systems). Further than the previous Robust Physical Perturbations attack, properties of control systems such as Kalman Filter are considered.
Undergraduate TA position. Hold Office Hours to help students on concepts in Operating System. Help students who are stuck on their course projects.