Su Ann Chong
About Su Ann Chong
Su Ann Chong is a Graduate Research Assistant currently working at Oak Ridge National Laboratory. She has a background in Physics and Computer Engineering, with experience in developing advanced detector technology and conducting data analysis.
Current Role at Oak Ridge National Laboratory
Su Ann Chong currently serves as a Graduate Research Assistant at Oak Ridge National Laboratory, a position she has held since 2017. In this role, she focuses on advanced research in nuclear engineering. Her responsibilities include conducting experiments and simulations that contribute to the development of innovative detector technologies.
Previous Experience at Lawrence Livermore National Laboratory
Chong worked at Lawrence Livermore National Laboratory as a NIF & Photon Science Summer Graduate Scholar in 2021. This three-month internship provided her with hands-on experience in photon science, enhancing her practical skills in a leading research environment.
Educational Background in Physics and Engineering
Chong earned her Bachelor of Arts in Physics from the University of California, Berkeley, where she studied from 2012 to 2016. She later pursued a Master of Science in Computer Engineering at the University of Tennessee, completing her studies from 2019 to 2021. Additionally, she obtained her Doctor of Philosophy in Nuclear Engineering from the University of Tennessee, Knoxville, between 2017 and 2022.
Research and Development Projects
Chong has contributed to significant research projects, including the development of a high data-rate pixelated neutron detector designed to improve neutron reflectometry instruments at the Spallation Neutron Source. Her expertise includes utilizing digital signal processing techniques for real-time data acquisition and visualization.
Technical Skills and Specializations
Chong is skilled in printed circuit board layout using KiCAD and specializes in the characterization of glass scintillators and photodetectors. She is proficient in data analysis with Python libraries such as numpy, pandas, seaborn, scipy, and sklearn, and conducts Monte Carlo simulations to model particle transport in glass scintillators.