Summary
Htet Naing is a data scientist with 9 years of engineering and research experience, specializing in applying AI/ML to complex physical systems such as weather nowcasting, rainfall sensing networks, and traffic simulation. He blends deep learning, reinforcement learning, gradient-free optimization, and physics-informed ML to build production-ready, real-time spatiotemporal pipelines and generative models. At NEA he led an award-winning effort to deploy a radar-based nowcasting pipeline on HPC with strict latency and accuracy targets, and developed an in-house GAN variant leveraging 3D reflectivity and wind fields. His PhD work with Alibaba-NTU produced novel physics-guided calibration methods and multiple top-tier publications, including a Best Paper award. Comfortable bridging research and operations, he mentors cross-functional teams and has a track record of turning cutting-edge models into operational systems in Singapore’s high-stakes environmental and transportation domains.
9 years of coding experience
4 years of employment as a software developer
Basic Education High School (BEHS) qualification (O-level equivalent) High School, Basic Education High School (BEHS) qualification (O-level equivalent) High School at No. (1) Basic Education High School, South Okkalapa, Yangon, Myanmar
Diploma Electronics Computer and Communications Engineering with Specialty in Wafer Fabrication, Diploma Electronics Computer and Communications Engineering with Specialty in Wafer Fabrication at Nanyang Polytechnic
Doctor of Philosophy - PhD Computer Science with Specialty in Machine Learning & Simulation, Doctor of Philosophy - PhD Computer Science with Specialty in Machine Learning & Simulation at Nanyang Technological University Singapore
English, Myanmar