Dr. Eugene Pinsky
Dr. Eugene Pinsky Sees Positive Growth in World of Data Science
Eugene Pinsky
Associate Professor of the Practice, Computer Science; Coordinator, Software Development
PhD, Columbia University; BA, Harvard University
What is your area of expertise?
My research area is in performance analysis, data science, and machine learning. I completed my PhD in computer science at Columbia University, and in the years since I have taught both within academia (Boston University, MIT) and industry. For almost twenty years, I worked in the areas of data science and machine learning, developing applications that utilize machine learning to solve real-life practical problems—primarily in computational finance and computational advertising.
Data science and machine learning require an understanding of many interdisciplinary concepts. The practice involves mining large amounts of data and applying machine-learning methods to design new algorithms that are able to solve important practical problems. As more and more tasks become automated, the role of machine learning in our lives has grown in importance. This makes it vital that students become familiar with the practical elements of data science and machine learning.
What have been some of the main developments at BU MET in the area of data science in the past year?
The past year has seen a lot of positive developments within data science at MET. We continue to see a strong increase in the number of graduate students interested in pursuing data analytics. Moreover, we see many more students, from other MET departments and the greater University, registering for our classes, which reflects its interdisciplinary nature.
BU MET recently launched a new MS in Applied Data Analytics. How will students benefit from this new program?
This huge success for our college is the result of a large collaborative effort by faculty and staff, and a major step in Boston University’s recently launched, major initiative in data science. Our Applied Data Analytics graduate program will allow and encourage students to acquire practical skills that are in demand worldwide.
What are some of the objectives for the new program?
We must continue offering new courses that get students involved in the kinds of projects that teach them the necessary skills of the field. We currently offer a number of new courses, both online and on campus. To name a few, these include Big Data Analytics (MET CS 777), Machine Learning (MET CS 767), and Data Science with Python (MET CS 677). We plan to offer additional relevant and innovative courses in the near future as well. We also hope to see an increased number of students working on collaborative projects with faculty throughout the University.
Can you give us an example of such a project?
Last year I supervised a project by two students from France, Etienne Meunier and Pierre Moreau. Both had worked for French electric distribution companies and were interested in a practical problem—developing algorithms that could predict future power consumption. We were able to design methods that were simpler than the current proposals while remaining amenable to simple intuitive explanations. Our solution’s accuracy was comparable to the complex existing methods, and because of its viability we plan to submit the paper to a journal for peer review.
What are your goals for the upcoming year at BU MET?
Personally, my goals are to continue active collaboration with my colleagues so that we might engage students in as many projects as possible, while we continue developing and updating new courses.