Dr. Eric Braude
Faculty Spotlight.
Meet Dr. Eric Braude, Associate Professor of Computer Science and Coordinator of the Master of Science in Software Development program. Dr. Braude holds a PhD from Columbia University, MS from University of Miami, MS from University of Illinois and a BSc from University of Natal.
What is your area of expertise?
Machine learning and software engineering.
Tell us about your work—can you share any current research or recent publications?
A paper, “Generalizing Morley’s and Other Theorems with Automated Realization,” by my student (and recent MSCS graduate) Satbek Abdyldayev and myself, appeared in April’s issue of the Journal of Automated Reasoning. Morley’s Theorem is a statement about triangle trisectors that came to my attention years ago via the writing of computer scientist Edsgar Dijkstra, and in this 23-page paper we describe the theory as well as our GEOPAR program, which checks the validity of various proposed theorems in plane geometry.
MSSD graduate Jason Van Schooneveld and I recently completed work on “Incremental UML for Agile Development with PREXEL,” which was introduced at the International Conference on Software Engineering last month in Gothenburg, Sweden.
How does your work in apply in practice? What is its application?
The most common form of software development, agile, does not readily accommodate the use of design tools. That’s the issue PREXEL addresses, and master’s graduates Chih-Chieh Liang and Nitish Gaddam are now working with me on the next generation of PREXEL.
The work that student Andy O’Connell and I are doing applies machine learning to recovery from failures in the Internet of Things—which is now quite pervasive.
What course(s) do you teach at MET?
Most recently, Machine Learning (MET CS 767), Advanced Programming Techniques (MET CS 622), and Analysis of Algorithms (MET CS 566).
From your previous work in the industry, what “real-life” exercises do you bring to class? And how does that inform your classroom?
Before coming to BU, I worked in applying AI to complex systems and was also involved in software reliability. The resulting perspectives influence my research and teaching. In advanced classes, I emphasize the development of individual projects, so students have the opportunity to apply concepts as they learn them.