Hello, my name is Edward. Prior to my post-doc, I studied for a PhD at The University of Warwick, UK for 3.5 years (my former PhD supervisor is Dr. Arshad Jhumka). I successfully defended my thesis on 28 May 2020 and received the PhD degree in Computer Science on 7 July 2020. My post-doctoral supervisor is Prof. Neeraj Suri.
My current interests lie at the intersection of systems security, fault tolerance, distributed systems and data analytics. I also have a general interest in anomaly detection, causal inference and networking. I have been working on the topic of failure diagnosis since 2010 and it is an area that I enjoy immensely.
Selected peer-reviewed publications:
- E. Chuah, A. Jhumka, S. Alt, J.J. Villalobos, J. Fryman, W. Barth, M. Parashar, “Using Resource Use Data and System Logs for HPC System Error Propagation and Recovery Diagnosis” , in Proceedings of 17th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA), December 2019.
- E. Chuah, A. Jhumka, S. Alt, D.Balouek-Thomert, J.C. Browne, M. Parashar, “Towards Comprehensive Dependability-Driven Resource Use and Message Log-Analysis for HPC Systems Diagnosis”, Journal of Parallel and Distributed Computing, vol. 132c, pp. 95-112, October 2019.
- E. Chuah, A. Jhumka, S. Narasimhamurthy, J. Hammond, J.C. Browne, B. Barth, “Linking Resource Usage Anomalies with System Failures from Cluster Log Data”, in Proceedings of 32nd IEEE International Symposium on Reliable Distributed Systems (SRDS), October 2013.
Software tools developed:
- CORRMEXT – A dependability-driven resource use and message logs analysis tool
- EXERMEST – A tool for diagnosing rare error cases using resource use data and system logs
Services to the community:
- 2020: Invited reviewer for IEEE Access, 2nd International Conference on Machine Learning and Intelligent Systems (MLIS 2020), 6th International Conference on Fuzzy Systems and Data Mining (FSDM 2020), PC member (ICI2ST 2021).
- 2018: Invited reviewer for Software: Practice and Experience, ACM Computing Surveys.