TA Spotlight: Victor Legros

Every other week we spotlight an OMSCS TA, so you can get to know who's behind the screen. Here are four questions for Victor Legros who TAs CS 6291: Embedded Systems Optimization.


Victor Legros

What do you do professionally?
I am exclusively focusing on the OMSCS by taking two classes and being a teaching assistant right now. I had previously worked as a product manager at Microsoft and Electronic Arts, juggling full-time work while doing this degree. Before Covid-19 put an end to it, I left my job to travel internationally while also continuing my studies! (My photo is of Angkor Wat in Cambodia.)

Why do you TA for OMSCS?
I have really enjoyed exploring subjects that are new for me and reconnecting with my technical roots as part of OMSCS. Being a TA seemed like a good opportunity to go deeper in the material that particularly resonated with me. I have found that being able to explain a topic to another really solidifies my own understanding by prompting me to consider it from different angles and to aggressively simplify.

What’s your advice for future students in OMSCS?
Take a moment to tally the things you value and spend time on in your life now. Next, think about what your goals are for your studies, assess how you learn best, and gather up tools and resources. Pursuing a graduate degree is demanding, and it is easy to over-commit yourself or be caught out by multiple things coming due. To finish strong, you may need to make trade-offs or lean on support from others, so knowing for yourself and preparing will help you persist and get through it when things get messy. It takes measures of adaptability and time, but it can be very rewarding, too!

What’s your preferred programming language, and why?
I love religious debates! I really like working in Python since it is a very clean language that gives you a lot of useful data structures and programming idioms out of the box. There are many instances I have worked in C++ and wished I had access to Lists and Dictionaries! I understand why existing codebases or strong performance requirements are good reasons to use different languages, but if I am starting from a clean sheet I’ll at least try to use Python.

Plus, there are lots of powerful libraries. Using NumPy for data manipulation or OpenCV for image processing is a way to get most of the performance from compiled C++ code, and there is a whole lot more out there on the artificial intelligence and machine learning front that builds on Python.