177 Huntington Avenue
Boston, MA 02115
Jay DeYoung is a PhD student at Northeastern University’s College of Computer and Information Science, advised by Professor Byron Wallace. He earned his BS in Computer Science, Applied Mathematics, and Statistics, and a MS in Engineering in Computer Science from Johns Hopkins University. He then worked in industry, but decided to come to the PhD program at Northeastern to pursue a more academic career path. Jay is interested in developing novel approaches with a large impact across multiple CS disciplines; his areas of research include AI, Data Science, Machine Learning, and Natural Language Processing, and he is interested in working on subjects ranging from deep learning to question answering systems to optimal dataset collection.
- Master of Science and Engineering in Computer Science, Johns Hopkins University
- BS in Computer Science and Applied Mathematics and Statistics, Johns Hopkins University
- Field of Study: Deep Learning
- PhD Advisor: Byron Wallace
What are the specifics of your graduate education (thus far)?
I am returning from being a working professional to pursue a more academic track.
What are your research interests in a bit more detail? Is your current academic/research path what you always had in mind for yourself, or has it evolved somewhat? If so, how/why?
I am interested in developing and building novel techniques and approaches for problems in computer science that can have a big impact. My areas of interest extend from optimal dataset collection to question answering systems to deep learning applications.
Where did you study for your undergraduate degree? Any reason in particular behind your choice (a program you were excited about, a city you love, a researcher you wanted to work with)?
I did an undergraduate in Computer Science, concurrent with a second major in Applied Mathematics and Statistics, and a Master’s Degree in Computer Science, at Johns Hopkins University.