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I build and study intelligent systems at the intersection of language, vision, and reasoning — with a particular focus on low-resource and under-represented languages in NLP.
About
I'm a graduate student in Artificial Intelligence at Georgia Institute of Technology, one of the world's leading programs in computing and AI. My academic journey began with a Bachelor of Science in Computer Science from the University of the People (USA), where I graduated with distinction.
My work sits at the crossroads of machine learning theory and real-world systems — from building computer vision pipelines to exploring how large language models can be adapted for low-resource languages like Burmese.
Beyond coursework and research, I founded the Burmese NLP Research Group an independent collective dedicated to advancing natural language processing for the Burmese language — one of the most linguistically rich yet underserved languages in the NLP community.
Technical Skills
Education Timeline
Research
Exploring the theoretical foundations of AI — knowledge representation, reasoning under uncertainty, multi-agent systems, and the frontier of artificial general intelligence.
Deep learning architectures, self-supervised learning, transfer learning, and novel training paradigms that enable models to generalize across tasks and domains.
Image understanding, object detection and segmentation, vision-language models, and scene comprehension using both CNNs and modern transformer architectures.
Large language models, low-resource language processing, tokenization for morphologically rich languages (Burmese), machine translation, and multilingual NLP.
Intelligent control systems, motion planning, reinforcement learning for robotics, dynamic modeling, and the design of autonomous agents that perceive, reason, and act reliably in unstructured real-world environments.
Research Group
The Burmese NLP Research Group is an independent, community-driven research collective focused on advancing natural language processing technologies for the Burmese language. We work to close the resource gap for one of Southeast Asia's most widely spoken yet computationally under-resourced languages — creating datasets, benchmarks, and open-source models for the global research community.
Contact
I'm always open to research collaborations, speaking invitations, mentorship discussions, and conversations about AI for under-resourced languages. Reach out — let's build something meaningful.