Finding Your Place in Computer Science
How I went from sticking out to defining, for myself, what an engineer looks like.
The link between data and clothing was not immediately obvious to me.
There were two truths in my life at one time; two things I knew for sure: One, I was at university completing a degree in Computer Science. Two, in my free time, I enjoyed flipping through pages of Harper’s Bazaar.
These truths seemed independent from each other, and as if they stemmed from two, completely different corners of my likes and interests. After all, what does an ability to code recursive algorithms have to do with the colors in Prada’s new collection?
I soon learned: a lot.
It was my second year at Harvard that I decided to pursue computer science as a degree and, if I was good enough, a career. It was then that I knew — as I walked into a lecture hall of one hundred students, just a handful of which were women, feeling strongly juxtaposed against a sea of graphic tee-shirts in a summer dress and cardigan — that I did not fit in well.
I remember so vividly observing, in real-time, and unfolding right in front of me: clothing can mean something.
There are numbers to back this up, you know. 86% of software engineering professionals are men. And, though numbers are just numbers, it is often difficult to look beyond them; to remember that fields dominated by strong, male-oriented stereotypes don’t have to remain that way.
Since clothing is so closely tied to our identities; how we present ourselves to others; what others think about us upon first-glance, clothing was a big reason why I so strongly stood out.
While working one of my first software engineering jobs two summers ago, proud to show up in clothing that so strongly juxtaposed against the other engineers’ — summer dresses in blue satin; black, flowing skirts with kitten heels — I was told by a woman older than me who, at this point, I’d closely admired —
‘I used to dress like you, but it made me really uncomfortable.’
‘Oh.’
There was nothing else I thought to say. Maybe, I added —
‘Yeah, it makes me uncomfortable too,’ because it did. It doesn’t, anymore.
The words she said to me felt like they shouldn’t have been spoken; as if she had said to me the parts of myself that made me different were standing in my way or should, in time, be changed. I decided to keep dressing as I wanted.
I spent the rest of my internship learning about new, innovative technologies. I was particularly drawn to image recognition, because it seemed, to me, like the magical part of computer engineering. You can show a computer an image, and it can tell you what’s in it? I’ll believe it when I see it.
I liked looking at images — in fact, I spent a great deal of time flipping through Harper’s Bazaar editorials; Vogue Runway’s collections — so, maybe, I thought, I could teach a computer to detect things in them, too. Things that were important to detect: midi versus maxi length hemlines; monochromatic color palettes; pointed versus open toe shoes…
There is so much beautiful creativity, artistry, and subjectivity in fashion; in what, or who, inspires what we choose to wear. However, could there possibly be a way to make sense of all this artistry — to aggregate quantitative information about designs, in order to, in time, better understand them?
By learning to tie numbers to clothing — analyzing what percentages of a collection, or outfit, exhibited which trends — I began to better understand fashion; the staple silhouettes and designs used frequently across designers versus the intricate, creative, micro-trends particular to each collection.
I continued my fashion-trend-aggregation throughout my last year of university, and wanted to submit it for credit towards the completion of my degree. In order to do so, I needed the sponsorship and support of a professor in the Computer Science department. Some, when I asked, said no; that they didn’t understand the work I was doing, or why fashion was a space that could overlap well with technology. One, however, said yes.
One professor looked at my work, thought it had value, and decided to stand behind it. He was excited that I was excited, and wanted to see how much further I could go. Suddenly, a small corner for myself, hidden among a vast world from which I so starkly contrasted, began to form.
It was his support and guidance that fueled within me the desire to eventually publish my work. People don’t have to be in your life for very long to change it in extraordinary ways.
I’ve watched different stories, with alternate origins, characters, and lessons, become tangled and intertwined throughout my life like strings, eventually meeting at one, final point: my passion for fashion-tech. The data presented in my research, and my books, is a product of many things: holding different parts of myself and not knowing what to do with them; feelings of insecurity and not-good-enough; a sudden light leading me down a path I felt eager to keep uncovering.
When I aggregate data, the output appears as solely numbers. Though, I often feel that they are also so much more than that.
Computer science is a vast field, whose strict stereotypes often hide the myriad of opportunities it has to offer. If you are interested in the subject, I urge you to seek out the ways it can intersect with everything you love — whether it’s fashion or otherwise.
Continue searching for, or building, your place in Computer Science, even if it feels uncomfortable or if you become discouraged. I can promise you with full certainty: it exists, and it is waiting for you.
Ultimately, whether you’re a computer scientist or not, I hope you come across corners of the world in which you find yourself; feel confident in your differences; see happiness in your future.
*This personal essay was originally published in ‘The Little Book of Big Fashion Data: Edition III’. It has been modified here for clarity.
I’m a NYC-based software engineer, researching all the ways in which fashion and technology intersect. Read more of my stuff here, or check out my research, ‘The Little Book of Big Fashion Data’.
