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In Conversation with
A Techronicler interview with Rejoice Hu, Machine Learning Engineer
Techronicler: Thank you for joining us, Rejoice! Share with our audience a little bit about yourself, focusing on your experience in tech + what you currently do for work (and passion projects!)
Rejoice Hu:
I’m currently a Machine Learning Engineer at Morgan Stanley, where I work on machine learning and heuristic-based systems for fraud detection and risk. I graduated from Cornell University with a Bachelor’s and Master’s in Information Science, specializing in Data Science and Machine Learning. I have published research in deep learning for MRI imaging in ADPKD disease detection and reinforcement learning for human-robot interaction. Outside of work, I enjoy playing piano, baking, and running – a few of the ways I like to recharge and express creativity outside of engineering.
Techronicler: What is some advice you want to give to other young-in-their-industry AAPI women entering the tech space?
Rejoice Hu:
Advocate for yourself early and often. The gender disparity is still real, especially as you move upward, so it’s important not to underestimate your own voice, ideas, and ambitions. No one will care about your career as much as you do, which means being proactive, asking for opportunities, and not limiting yourself before others do.
Adopting this mentality of being bold was how I was able to create my own opportunities that didn’t even exist in the first place at my current company – you truly never know until you ask!
Network, network, network! Find mentors, build genuine relationships, and don’t be afraid to reach out to people you admire. Take advantage of your age – many people are more than willing to help you because they remember being in your shoes.
And most importantly: stick together. Having a strong community of women who support and uplift one another makes an enormous difference, especially in industries where representation is still growing.
Techronicler: How has Rewriting the Code helped you in your tech journey?
Rejoice Hu:
Rewriting the Code has been such a meaningful part of my early career journey in tech. When I first moved to NYC after graduating, RTC immediately gave me a sense of community — I was surrounded by other early-career women navigating the same transitions, challenges, and excitement that I was. It made a huge difference knowing I wasn’t alone, and I’ve met some incredibly ambitious and inspiring women through the organization who constantly motivate me to keep growing and aiming higher.
RTC has also helped me continue building my technical skills through opportunities like a sponsored DataCamp subscription, which allowed me to further upskill outside of work. Beyond the resources themselves, the encouragement, mentorship, and network have been invaluable in helping me grow both professionally and personally.
Techronicler: Everyone has an origin story! What was the first piece of technology you ever broke, built, or fell in love with?
Rejoice Hu:
My first real “I can actually build this” moment was my freshman CS project called Cure the Cancer, a tilemap game where I implemented the A* pathfinding algorithm. It was my first coding project ever in my very first computer science class, and I remember spending many late nights debugging and slowly watching things start to work. It was also the first time I dreamt about code haha.
That project ended up being a huge confidence boost for me, not because it was perfect, but because it showed me how much I could grow in a short amount of time when I stuck with something hard. It really shaped how I approach challenges in tech today. If there’s one piece of advice I’d give, it’s to take the hard class, try the intimidating project, and push yourself early — you grow exponentially more than you expect!
Rejoice Hu is a machine learning engineer at Morgan Stanley who has built models she struggles to publicly claim credit for. Her East Asian upbringing makes self-promotion feel like a transgression — a dynamic that’s costing talented women visibility they’ve earned.