Research Assistant, Explainable AI; Technical Fellow, BU Spark!
MS in Computer Information Systems, concentration in Data Analytics (MET’22)
What compelled you to return to school and pursue a graduate education? What is your long-term objective?
Many industries nowadays are exploring digital and data evolution. I used to have a first-hand feeling for such needs, working in the commodity trading industry for 10 years. I served in various roles from the front desk to the back office, and the momentum in digital and data applied to every role I filled.
Comparing “traditional” industries like commodity trading to “modern” industries such as tech and finance, there is a clear distinction between how each has adapted to innovative advances. The tech industry has developed digital platforms that automatically gather and process user data, as has finance—because such infrastructure has been mandatory. Whereas traditional industries do not necessarily have such a capability, and hence face more difficulties. Without a base dataset, none of the advanced data science technologies are useful.
I wanted to be able to provide both the infrastructure that provides a foundation for industry to innovate, and the data science technology. That is how I decided to pursue a practical graduate program that covers both computer science and data science.
In the long run, I would like to return to the industry and leverage the computer science and data science knowledge I acquired through the MET program. It could be in a scientist role, someone who invents new technology/framework, or in a commercial role that identifies client problems and delivers solutions. I am keeping it open at the moment.
Why did you choose BU MET for your graduate studies? What set BU MET apart from other programs you were considering?
I found MET’s MS in Computer Information Systems, Data Analytics Concentration both comprehensive and intense enough to enable my quick career change. It offers data science components in its computer science program, and I was interested in applying machine learning technology to whatever I do in the future.
One of the key distinctions from other CS graduate programs is that MET doesn’t necessarily require an undergrad degree in CS. To meet today’s industry needs, it is important to have both domain expertise and technical skills. When I spoke to a recruiter from MET’s CS program, I got the impression that the BU MET CS department understands real-world needs and is committed to training people like me from scratch to become industry-ready.
Is there a particular faculty member from your courses who has enhanced your experience at BU MET? Who and why?
Prof. Eric Braude enhanced my experience significantly as a lecturer and a researcher. I took two of his courses, Foundations of Machine Learning (MET CS 555) and Analysis of Algorithms (MET CS 566), in summer 2021. Though the classes were virtual, they were highly engaging and offered a lot of interaction with the professor and other students. I found the assignments distinctive because students got to choose their own projects, while Dr. Braude provided frameworks so students did not get lost. It emphasized the hands-on aspect. The frameworks did not always tell us what to do or ask for one single answer, but they made us think thoroughly, do our own research and, most importantly, implement algorithms we had just learned using concrete examples. He gave me feedback on my project every week during office hours, so I was able to guide myself in the right direction throughout the project.
This research/project framework has been instilled in me and has become my formula whenever I do any research or project.
I’m currently working for Dr. Braude as his research assistant at Explainable AI. This hands-on research experience is establishing a solid scaffolding for my career.
I am also a technical fellow for BU Spark! (an on-campus incubator).
How do you apply concepts you are learning in your courses at BU MET in your current job or internship?
I am currently working on a web-app development project called AutoPCB. In this project, I apply my software engineering skills as well as an understanding of algorithmic efficiency. The project aims to automate manual processes that electrical engineering students go through when they build printed circuit boards. Since it entails computationally expensive optimization problems, an understanding of the algorithm and the capability to model it play a central role in this project. Also, seeing the potential of our app, I continuously re-factor codes to make the app scalable, maintainable, and readable. Those are principles I learned in the Software Engineering (MET CS 673) course.
On the soft skills front, I am leveraging tech-communication skills. Communicating code and questions about code is challenging. When we collaborate as a team in a distributed environment, it’s important that we update each other frequently, so we can make appropriate changes to the working code and merge when necessary. Explaining my code enhanced my tech-communication skills every time, and I would like to carry on using this skill for my current and future jobs.
What is currently, in your opinion, the most valuable thing that BU MET provides you?
BU MET’s streamlined program is the most valuable component, in my view. The CS program gave me comprehensive knowledge to get on board in my new career path. Also, modules included in the data analytics concentration covered statistics theory, tools, and applications for real-world use.
Some people may claim that such knowledge is available on YouTube and other online courses. It is true that those online materials exist. However, at BU MET the lectures, assignments, and professors make you come up with your own ways to apply newly-acquired knowledge to a unique problem. I believe that you can immediately transfer those new skills to the industry.
This comprehensive style of education is the most important component of BU MET for me, and the experience I gained will be an asset in my future career.