I am a Ph.D. candidate in the Electrical Engineering Department at University of Southern California. I am lucky to work with my advisor, Prof. Michael J. Neely. The curiosity of communication network theory, where mathematics is used as tools to design and analyze communication networks, was the reason that I joined the program in 2010.
I completed my M.Eng. in Telecommunications from Asian Institute of Technology in 2008 and my B.Eng. in Computer Engineering from Kasetsart University in 2006. Both institutes are in Thailand.
My research expands in two directions:
- Convergence analysis of stochastic network optimization
- Practical implementation of stochastic network optimization
Recently, a practical load-balancing algorithm has been developed from the insight of a theoretical throughput-optimal algorithm. The algorithm works gracefully with TCP flows in datacenter networks and outperforms the commonly used ECMP algorithm. This demonstrates the practicality of the theory and reduces the gap between theory and practice, which is the goal of my Ph.D. study.
I am expected to graduate in December 2017. My plan is to work on "practical theory" network optimization where theoretically optimal algorithms with realistic (possibly non-analyzable) considerations are elevated by software-defined networking and network function virtualization. I strongly believe that "practical theory" network optimization will bring both theoretical and practical network communities together to create beautiful network systems.
My research interests include:
Practical network optimization,
Distributed algorithms, Convex optimization,
Software-defined networking, Network function virtualization
Datacenters, Cloud computing, Machine learning