About Me
I am currently a senior majoring in Nuclear Engineering and Radiological Sciences and pursuing a minor in Material Science and Engineering and an International Minor in Engineering at the University of Michigan. I hail from Hong Kong and I speak both Cantonese and Mandarin. I am passionate about utilising the gift of knowledge to satisfy the needs of the future. I am currently involved in undergraduate research and student design teams. Outside of engineering, I am avid chorister and I served as the librarian of the University of Michigan Men’s Glee Club.
My Works
Ongoing
Real-time Defect Identifier
Nuclear Orientated Materials and Examination (NOME) Laboratory
University of Michigan
I am currently an undergraduate research assistant working for Dr. Kevin Field at the Nuclear Orientated Materials and Examination (NOME) Laboratory at the University of Michigan. My current project is to create a deep neural network (DNN) model to identify dislocation loops in transmission electron microscopy (TEM) images of steel samples in collaboration with Dr. Dane Morgan and Mingren Shen at the University of Wisconsin. The DNN model will be applied on in-situ identification of dislocation loops as they are formed during irradiation. I am also involved in setting up a DNN workstation at the NOME Lab.
Past Works
TEM DNN-based Cavity Identifier
Center for Nanophase Materials Science
Oak Ridge National Laboratory
As part of the Nuclear Engineering Science Laboratory Synthesis internship program at ORNL, I worked under the direction of Dr. Maxim Ziatdinov and Dr. Sergei Kalinin and created a DNN-based framework using TensorFlow in Python on the Google Colab cloud computing platform to locate and size helium cavities in a large number of TEM images of irradiated high entropy iron-nickel alloys with an accuracy of 96%. I also used the same framework to create a program to de-noise scanning tunneling microscopy images.
Customised OSL Dosimeter Reader
Radiation Health Laboratory
University of Michigan
Under the direction of Dr. Kimberlee Kearfott, I participated in the construction of an optically stimulated luminescence (OSL) dosimeter reader that operated on a broad spectrum of wavelengths (as opposed to current commercial OSL readers which operate on a specific wavelength) to explore novel scintillator materials. I also calibrated a custom built gamma-ray spectrometer and used it to conduct gamma-ray spectroscopy on volumetric sources and foodstuff. I also used Ortec Maestro and GammaVision to analyze the gamma-ray spectra generated from the spectroscopy and identify possible radioactive contaminants in foodstuff.
PsA Development Prediction using DNN
Department of Dermatology
University of Michigan
As part of the Biomedical and Life Sciences Summer Fellowship, I worked under the direction of Dr. Alex Tsoi and Dr. Matthew Patrick to use a DNN to predict the development of psoriatic arthritis (PsA) among psoriatic patients based on the genetic signatures of 7000 samples to facilitate advanced diagnosis and individualized treatment of patients likely to develop PsA. For that I created a deep neural network in the R programming environment using the MXNet deep learning package with a prediction accuracy of 69%.
My Experiences
Professional & Educational
International Engineering Summer School
Institute of Energy Engineering
Technical University of Berlin (Technische Universität Berlin)
In the summer of 2018, I participated in the International Engineering Summer School in which I designed a wood gasification system to generate both heat and electricity for a sawmill. I also took classes in German which furthered my interest in the German language.
Tommy Wong 