Kyi Thar
Background
For my academic journey, after graduating with a Bachelor of Computer Technology degree from the University of Computer Studies Yangon, Myanmar in 2007, I joined as an IT executive and part-time lecturer in Myanmar Egress. Myanmar Egress is a non-profit organization and was founded to promote Myanmar's educational sector, especially for the young generation. As a young enthusiastic learner, I was always looking for opportunities for further studies. Eventually, I was selected for a fully funded president scholarship to the MS leading to Ph.D. program in Computer Engineering at the Networking Intelligence Lab, Kyung Hee University and I graduated in February 2020.
After Ph.D. graduation, I worked as a Postdoctoral Researcher in the Intelligent Networking Lab, Department of Computer Science and Engineering at Kyung Hee University, South Korea. I have collaborated with other organizations in various projects, including the “Institute for Information and Communications Technology Promotion (IITP)” (Korea) and “Electronics and Telecommunications Research Institute (ETRI)” (Korea). I was also collaborating with Trinity Healthcare Enterprise to build an integrated one-stop healthcare solution to improve Myanmar’s healthcare sector. Moreover, I am working with PIT Technology to develop the Agricultural Platform to improve Myanmar’s agricultural sector. The objective is to establish a traceable unified agricultural platform to address information asymmetry, linkage in the value chain system, inconsistency in the quality of produce, impacts of climate change and access to the market of increased income for farmers and stronger sectoral growth in Myanmar.
Area of interest
My research area was content-centric networking and I developed various named-based routing and intelligent caching solutions. I also applied deep learning in intelligent wireless network virtualization and management. The title of my Ph.D. dissertation was “An autonomous deep learning model generation framework for edge computing”, which aims to develop an autonomous system capable of generating the most appropriate domain-specific deep learning model for the edge computing environment. I am also interested in Internet-of-things (IoT), industrial IoT (IIoT), network intelligence, information security, and explainable distributed/federated machine learning research areas.