Tell me about yourself / What did you do after graduation?
I am a researcher working out of the Leidos AI/ML Accelerator. Most of my work right now is within the field of Computer Vision, but I’ve also spent a good bit of time thinking about everything from RLWE homomorphic encryption to AI operationalization.
Why did you choose Georgetown?
I was an undergraduate mathematics major at Georgetown University. Upon graduation, I realized (very quickly) that if I was serious about practicing mathematics as a professional career, I would need at least a master’s degree (or many years of experience). The masters seemed like a quicker path to career happiness, and I had ties to the Georgetown community.
During undergrad, I had taken an advanced linear algebra class with Professor Ken Shaw. I went to see him three months after I graduated with my undergraduate degree to express my discontent working as an analyst at a fintech startup, which I’d very quickly realized was certainly not the direction I wanted to take my career. I knew, at that point, that as part of my professional life, I wanted to develop new mathematics and work closer to the cutting edge of AI/ML. However, I was lacking some of the necessary programming and applied mathematics skill sets – particularly around deep learning frameworks, modeling, and paper-reading/writing. Professor Shaw told me that participating in the MAST program would help me get closer to my goals, and I trusted him, both as a mentor and a friend. So, I only applied to Georgetown MAST, was accepted, and will forever be grateful to Professor Ken Shaw for helping me begin my professional career.
How did the MAST program prepare you for your career?
The program taught me the programming, applied mathematics, research, and theoretical backing necessary to successfully enter the workforce and meaningfully contribute towards my team’s research objectives. Most of my professors were also working professionals with excellent advice and years of experience in the field. Every class I took during my masters either provided a great deal of personal edification or professional wisdom.
What’s your advice for alums?
Your masters degree is only the beginning. Continue to both grow your deep understanding of mathematics/programming post-masters and your personal network – both will help you have a successful, fulfilling career (of which I am still only just starting).
Also, a lot of AI/ML modeling relies upon underlying hardware, sometimes a vacation does result in better model performance.