NJIT Alumnus Lands Verizon Engineering Role, While Staying Enrolled for M.S.
Most people finish college and then look for full-time employment or enroll in graduate school, but Don Bonifacio did both and is constantly challenging himself to learn new things.
Bonifacio graduated in May from New Jersey Institute of Technology with a B.S. in computer engineering and was a member of Albert Dorman Honors College. He now works at Verizon planning behind-the-scenes engineering for their fiber optic network and is simultaneously continuing in the NJIT computer engineering department this fall for a master’s degree in his field.
While an undergraduate, Bonifacio also found time to work on research projects related to electronic imaging with Associate Engineering Professor Xuan Liu, and even helped with the data science for a study of corporate earnings manipulation with Assistant Professor Ming Taylor in NJIT’s Martin Tuchman School of Management.
It’s the optical imaging front where his work shined brightest, earning Bonifacio first-author honors among Liu and other students, including engineering classmate Laterriean Minaya on Phase-augmented deep learning for cell segmentation in wrapped quantitative phase images in the journal Biomedical Optics Express. Xuemei Chen and Yuanwei Zhang, both from the Department of Chemistry and Environmental Science, also contributed. Funding was provided in part by a grant from the National Institute of General Medical Sciences, Monitor single-cell dynamics using optically computed phase microscopy in correlation with fluorescence characterization of intracellular properties.
The research proposes a data science solution to a measurement problem when viewing cells under a microscope. Complex measurements cause what’s called phase-wrapping artifacts, essentially blurriness between and among cells. The research taught a neural network to know the difference between cells and the image artifacts, and then remove the latter. It is faster and more accurate than prior methods.
“Don played a critical role in designing, training and validating the deep learning neural network. He showed remarkable engineering talent along with strong motivation and leadership,” Liu stated.
Bonifacio said his interest in applying data science to the natural sciences is rooted in his youth. He grew up in Ocean County and attended MATES — Marine Academy of Technology and Environmental Science — so he has a strong natural sciences background. But he also took a data science course there, enjoying the mathematics and technology that made it work.
“Once I started off at NJIT, I spent the first couple years trying to get comfortable there. I had to learn a lot. Coming from a high school where the focus is more on biology, there was a lot to learn especially on the electrical engineering side of things. I didn't know what a resistor was, I didn't know what a transistor was. … I could learn how to code, I was pretty good at it, but computer science is layers of abstraction. Computer engineering goes all the way down to the physical layer. I still do care about the higher-level stuff, but what interested me a lot was the base of everything.”
A lesson learned, he said, is that it’s okay to not know exactly what you want to do or to change majors when something else is a better fit. Bonifacio still loves hardware and said that someday he’d like to be in position to design the full range of backend systems. Meanwhile, data science has him enamored.
“Data by itself is not useful. You use it to tell stories. Use it to draw conclusions. And with this kind of data, we are able to track the progress of certain projects that are going on — what's being held up, why, license agreements, points of contact … The ultimate goal is, yes, we want to tell a story, but at the same time, we want it to be understandable by those who see it.”