Ngoc Pham is a research-focused data scientist and master's student in Data Analytics for Science at Carnegie Mellon University with 14 years of technical experience spanning academia and industry. She has applied machine learning and deep learning to scientific and engineering problems, from data-driven reduced-order modeling for time-dependent PDEs to 3D point-cloud object detection using PV-RCNN and Point-RCNN on KITTI. Her background in mathematics (BS from The Chinese University of Hong Kong) and hands-on internships in NLP and semi-supervised learning give her a strong foundation in both theory and experimental validation. Based in Pittsburgh, she currently contributes to research at CMU while bridging numerical analysis and modern ML approaches—an uncommon mix that helps translate mathematical models into deployable data-driven solutions.
14 years of coding experience
1 year of employment as a software developer
A Level (Maths, Further Maths, Physics, Computer Science, Geography), A Level (Maths, Further Maths, Physics, Computer Science, Geography) at British Vietnamese International School
APRU Virtual Exchange Program, APRU Virtual Exchange Program at Osaka University
The Chinese University of Hong Kong (CUHK)
Master of Science - MS, Data Analytics for Science, Master of Science - MS, Data Analytics for Science at Carnegie Mellon University
Exchange Program, Exchange Program at University of Pittsburgh
International Graduate Summer School 2020, International Graduate Summer School 2020 at Vietnam Academy of Science and Technology - Institute of Mathematics
Contributions:30 pushes, 1 branch in 5 years 1 month
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Ngoc Pham - Research Assistant at Carnegie Mellon University