Machine Learning at Loyola

Machine Learning at Loyola

CTSDH Graduate Fellow Aman Meghrajani recently caught up with Dmitriy Dligach, Assistant Professor of Computer Science, to learn more about his work on the topic of machine learning, an important field in the Digital Humanities. Prof. Dligach received his PhD in computer science from the University of Colorado Boulder, his MS in computer science from the State University of New York at Buffalo, and his BS in computer science from Loyola University Chicago. Prior to joining the faculty in computer science here at Loyola this year, Dr. Dligach was a researcher at Boston Children's Hospital and Harvard Medical School. 

What made you feel so passionate and motivated to study computer science in depth?

My interest was initially ignited when I realized that computer science gives its practitioners a power to build things. I decided to study computer science in-depth when I learned about artificial intelligence (AI) that focuses on building *intelligent* things.

For a novice student, machine learning might sound like a very broad and vague term. How would you define the term? What are some of the resources that can give a broader perspective on machine learning for new students in the field? Why might machine learning matter to students outside of computer science?

Machine learning is our best bet right now at building intelligent systems. Students interested in machine learning should consider enrolling a free online course such as the one offered by Coursera. Machine learning is likely to be of help to researchers in data-driven disciplines who are interested in deriving insights from large quantities of data automatically.

Where do you see machine learning going? How is it going to change our day-to-day activities? How is it going to impact human interactions and knowledge?

I like to say that machine learning is about predicting the future (you are typically given some historic data and the task is to predict what will happen when the computer is presented with future data). The more I work in this field the more I realize how hard this task is. Therefore, I will refrain from making predictions.

You've performed extensive research at Boston Children's Hospital & Harvard Medical School in deep semantic analysis and data mining. Data mining is well known in the software industry to help gain insights out of daily-generated raw data. What skill sets in data mining particularly helped you perform your research and what suggestions would you like to provide to Loyola students (business, computer science, biology, etc) who might be potentially interested in data mining careers?

To work in machine learning in general and data mining specifically, one needs training in calculus, linear algebra, statistics, and programming, although it is possible to succeed with a subset of these disciplines.

In the Spring 2017 semester, Dr. Dligach is teaching COMP 170: Introduction to Object-Oriented Programming and COMP 398: Independent Study.