Stephanie Wang
The last time I was in Seattle was eight years ago, right at the tail end of winter, in early March. I stayed in Capitol Hill, and therefore my memories, for the most part, are of a wet and gloomy city: grungy, quirky, and alive with an undercurrent of something moody. The kind of place where you’d walk past the Chihuly Garden and Glass, its neon colors glowing like embers against the backdrop of hazy, gray mountains in the distance. Or where you’d spot metalheads, already drunk by early afternoon, stumbling down the streets, heading to some concert. I absolutely loved Seattle back then, but it didn’t imprint itself on me as a particularly green city. It felt gritty, urban, and, perhaps, a little wild. Certainly not the Emerald City moniker I kept reading about.
But here I am now, eight years later, in the heart of spring, in early May, and Seattle couldn’t be more different. This time, I’m staying in Wallingford with my friend Stephanie and her soon-to-be husband, Tyler. It’s a completely opposite setting: lush and residential, a far cry from the downtown grit I’d experienced before. The rain had fallen yesterday, soaked everything, and now the whole neighborhood feels like it’s been drenched in nature's own paint.
Colors are everywhere, vivid and almost surreal. The grass and trees glow with vibrant shades of green, as if every leaf had absorbed the rain and reflected it back in technicolor. Deep-red rose trees in full bloom; pink, purple, and red tulips stand wide open, likely coaxed out by the rare abundance of spring sunlight. Light pink flowers, open and confident, with striking dark red blotches on their petals—Furnivall’s Daughter, says Visual Look Up on my iPhone—dot the landscape. Pots overflow with purple petunias, and tall delphiniums sway gently, their lavender spikes reaching toward the sky. The neighborhood is putting on its most vibrant, opulent show, but with a relaxed, almost hippie twist. Like an English garden that’s let its hair down and gotten a bit wild, in the best possible way.
In that spirit, in the early afternoon on Saturday, Stephanie wants to take me to the Volunteer Park Conservatory, a beautifully restored Victorian greenhouse showcasing a world of exotic plants. When we get there, we find ourselves in the middle of another riot of colors and textures. One section bursts with tropical beauty: there’s the jade vine, its flowers an almost surreal turquoise, next to a spiky pineapple plant and clusters of red flamingo-lilies. In another room, we’re surrounded by desert plants: towering saguaro cacti, barrel cacti, and other rugged succulents.
I make a comment that Stephanie's outfit couldn’t have blended in more perfectly. She’s wearing a burgundy-purple mélange knit sweater over a turquoise shirt, echoing the colors all around us.
“Oh, Denis!” Stephanie exclaims.
She has spotted a cluster of delicate white and soft-red petal flowers.
“Do you know what these are called? Maybe these are the ones I could get for my wedding.”
There are no names posted anywhere, and no one around to ask. So, naturally, I do what I’ve been doing all along—pull out my phone and use Visual Look Up.
“Well,” I say, somewhat inconclusively, “according to my phone, it’s either a Clubed Begonia or Flaming Kathy.”
We stand there for a few seconds, comparing online images of both species. Stephanie narrows her eyes at the flowers, lips pouting like she’s about to solve a mystery, but neither of us looks any closer to figuring it out.
“Oh, well,” I shrug.
Before Seattle, Stephanie and I had lived in pretty much the same place for almost a decade. I met her on my first night in the US, back when we were both just starting college. We spent several years in Boston, and later, while I was in San Francisco, she was just across the Bay in Berkeley, doing her PhD. It wasn’t until October 2023 that she and Tyler made the move to Seattle. The reason for the move? Tyler got a postdoctoral position in computer science at University of Washington (UW), and Stephanie landed a job as an assistant professor at UW, also in computer science. She will not only teach but also head her own research group at the university.
“I’m slightly stressed out,” she tells me when I ask her how things are going, with that typical we-will-figure-it-out-somehow attitude that is a trademark trait of hers. “I guess there is a lot that I need to do.”
Steph’s primary research interest is distributed systems. The simplest explanation of distributed systems is that they are collections of computers working together to provide better performance and reliability than a single computer could on its own. Steph focuses on building intermediate abstractions—tools, really—that make it easier to build high-performance, fault-tolerant, and domain-specific systems. Right now, she sees the biggest need for this in the domain of machine learning (ML) applications, which is an umbrella term for all the “behind-the-scenes” applications that fuel much of the world presented to us today through technology, whether that’s movie recommendations on Netflix or credit card fraud detection alerts.
During her PhD, to be precise, Steph worked on distributed systems in the context of data processing, which includes all sorts of fancy stuff, like data cleaning, data aggregation, and data transformations. What she wanted to figure out was how to build a middle-layer system that could provide the computational infrastructure to handle the heavy lifting of data processing at scale, making it easier to build new techniques or systems for data processing. That’s because machine learning applications, despite being data processing applications, are not great at consuming lots of data efficiently.
Steph did figure out how to solve this problem, but the solution was generalized—not deeply tied to the nuances of machine learning itself. That was always her focus: distributed systems, not necessarily machine learning.
“I was happy that I got the project done,” she tells me, “but I effectively built the distributed systems around the black box of ML applications themselves. And not knowing what was happening in that black box felt unsatisfying.”
And that’s how her interest in machine learning developed over the past few years. It’s important to note, however, that this isn’t really about the use of machine learning techniques to solve problems, which is what’s presented to us when we get movies recommended on Netflix or when a bank alerts us of a credit card fraud. Steph is talking about the abstraction of these machine learning applications to scale their functionality across many computer systems.
“Okay, so what does that mean—abstraction?”
“Think of Apple’s macOS, for example,” she says. “When you’re using your Apple laptop, you don’t really think about what happens when you’re dragging an icon or double-clicking. It’s because all the stuff that happens behind the interface has been abstracted for you as the end user. If it hadn’t been, you’d actually have to think, ‘How do I move this icon from point A to point B? What do I click? What will happen?’”
Essentially, what Steph is talking about is the idea that I, as the user, don’t have to worry about the complex layers of operations happening underneath. Pre-abstraction, it’s all about the hardware-level processes: what all the wires are doing and how they form logic gates, which handle basic operations like AND or OR. These gates come together to create logic units, which then form larger units that can do arithmetic and decision-making—essentially the processor or CPU. That processor, in turn, forms the core of an operating system, which can manage many simultaneously-executing pieces of code. Because each layer exposes a higher level of abstraction—wires, gates, CPU instructions, programs—a user can click on their laptop and the action will translate into progressively lower-level operations, all without the user knowing it.
“Oh, got it,” I say, “so abstraction is a little bit like when you learn to use letters in math to write equations so that you can show a generalized formula, instead of actual numbers?”
“Yes, exactly,” Stephs smiles. “But, with math, abstraction isn’t physical. You can’t really make something with it. In computer science, you can use abstraction to create something. That’s what I find really cool.”
“Ha,” I nod. “Can you give me an example of that?”
“Through my research in PhD,” she explains, “what I realized was that these ML applications have been built on really inflexible systems. They are built on GPUs, graphics processing units, which accelerate execution, but are also less flexible in what they can execute compared to the CPU processors that we’re used to. So, we don’t yet have the equivalent of an operating system for distributed GPUs. People have gotten around that by building relatively simple distributed ML applications. But that becomes a problem when we have more and more complicated applications that we want to build. Say you want to have different chatbots, imagine many Chat GPTs that need to talk to each other, across different computers. Doing that efficiently and reliably right now would require so much engineering effort, so it would be a very expensive task.”
To that extent, Steph hopes her research group will figure out what common abstractions machine learning applications need. Finding these will allow her group to easily scale the functionality of a single application, therefore making it easier to handle the coordination between multiple machines. She is looking to build the next set of tools to make large-scale machine learning more efficient and flexible in the future.
“What is it about this that’s so appealing to you?” I ask her as we make our way out of the conservatory.
“I think it’s because,” she lights up, “when you find a way to abstract something, previously complex problems suddenly become very understandable.”
Well, it’s no wonder Steph handles things with a we-will-figure-it-out-somehow attitude—she always abstracts away the unnecessary details. Meanwhile, I tend to jump into problem-solving mode, assuming any problem might be the unsolvable, crisis-inducing one. Steph, on the other hand, operates from the principle that there’s likely a solution in there somewhere, so why stress? Our friendship has always been a bit hilarious as a result of this juxtaposition. Like the time in 2015 when we stayed in Vienna during our summer travels and when a bird flew into the room early in the morning, slamming into the walls. I freaked out. Steph woke up briefly, listened to my incoherent freakout, and casually replied, “Oh, okay,” and went back to sleep.
She cracks up as I retell this anecdote, while we’re making our way from the conservatory to the Seattle Asian Art Museum. At the museum, we spend most of our time looking at photographs of Anida Yoeu Ali’s performances, and both of us are struck by her orange worm-like suit from the The Buddhist Bug project. It’s a surreal, almost comical image—a long, segmented tube that Ali wore to appear like a human bug, popping up in the most unexpected places. Then there is the stunning Red Chador photo series, a collection of sparkling chadors that Ali wore in public, highlighting both the invisibility and hyper-visibility of the Muslim identity. Neither Steph nor I discuss any of this but I can tell that we both know what the other person is doing: absorbing and thinking.
What I’ve always found special about Steph—and probably one of the reasons why we became friends—is that, in addition to being deeply analytical, she is strongly drawn to the arts and prone to disappear in her own world of imagination. Steph paints, she draws, she’s into music (we’ve seen so many concerts together: Yeah Yeah Yeahs, Austra, Tokimonsta), and she’s always been into films and books.
This isn’t too surprising once you know her full story. Steph was born in Philly but grew up in Croton-on-Hudson, a village in New York’s Westchester County. I remember visiting her there several years ago, just around the winter holidays, and thinking that the place reminded me of Stars Hollow from Gilmore Girls. Quirky, cozy, creative.
“Oh, yes, definitely,” Steph says when I mention how artsy Croton-on-Hudson felt. “I grew up around a lot of writers and theater people. I think that definitely influenced my interests as a kid. I read so much when I was younger.”
By the way, Steph’s favorite books, in ascending order of publication year, are:
A Tree Grows in Brooklyn (1943), by Betty Smith
All the King’s Men (1946), by Robert Penn Warren
To Kill A Mockingbird (1960), by Harper Lee
The Earthsea Cycle series (1968-2001), by Ursula K. Le Guin
The Remains of the Day (1989), by Kazuo Ishiguro
Jonathan Strange & Mr. Norrell (2004), by Susanna Clarke
The Idea Factory (2012), by Jon Gertner
The Broken Earth series (2015-2017), by N.K. Jemisin
Circe (2018), by Madeline Miller
A Deadly Education (2020), by Naomi Novik
Steph and I bonded over music and movies in college, and we both embraced the indie sleaze era with open arms. We wore sweaters, boots, long coats—I distinctly remember Steph wearing a great thrift-store find, a navy-blue coat with red cuffs and baroque-style buttons—and we aired our opinions on arts and culture freely.
To close the loop, Steph’s favorite movies, in ascending order of their release year, are:
Fargo (1996), directed by Joel Coen and Ethan Coen
Princess Mononoke (1997), directed by Hayao Miyazaki
The Iron Giant (1999), directed by Brad Bird
Crouching Tiger, Hidden Dragon (2000), directed by Ang Lee
Spirited Away (2001), directed by Hayao Miyazaki
Pan’s Labyrinth (2006), directed by Guillermo del Toro
The Lives of Others (2006), directed by Florian Henckel von Donnersmarck
The Handmaiden (2016), directed by Park Chan-wook
Spider-Man: Into the Spiderverse (2018), directed by Bob Persichetti, Peter Ramsey, and Rodney Rothman
Parasite (2019), directed by Bong Joon-ho
Nomadland (2020), directed by Chloé Zhao
Everything Everywhere All at Once (2022), directed by Daniel Kwan and Daniel Scheinert
There is one film she keeps going back and forth on, unsure if it belongs on her favorites list: Synecdoche, New York (2008), directed by Charlie Kaufman.
“I guess it’s a very important movie in my story arc,” she says, “because I really loved it in college, but I rewatched it lately, and I wasn’t into it anymore.”
“How so?”
“It’s a very existential movie that addresses life from the perspective of extreme commitment to work, to your vision in what you do. I think I was super into that when I was in college, but as I grew older, my perspective shifted. Probably because I met Tyler.”
“You experienced love,” I say with a smile.
“Yeah,” she smiles back, “I did. And I honestly didn’t ever think that a relationship could change my life so much, which is funny, because the change was really that I realized I felt most like myself when I was with Tyler.”
Outside, it’s starting to drizzle. We leave the Seattle Asian Art Museum and drive through the damp streets in Steph’s car, heading to Espresso Vivace in Capitol Hill, a place that feels like the Seattle I know from my first visit. When we get there, the rain outside has become steady, and the cold has seeped into the coffee shop. I order a warm apple cider and a slice of banana bread, and Steph goes for a matcha latte. We settle in, and the conversation drifts back to relationships, as it tends to when things slow down over coffee.
Steph and Tyler met in grad school at Berkeley and had been dating for most of their PhD experience. It’s been a pivotal relationship for both of them, for many reasons; for Steph specifically, one reason was that the relationship helped reveal a new side of her. Through Tyler, who grew up in the Pacific Northwest, she became more outdoorsy, and now spends a lot of her free time in the mountains and in the woods. On the surface, it seemed like an unexpected twist—Steph, the artsy New Yorker, suddenly spending weekends in the wilderness. But when I think about it, it actually fits her no-nonsense, risk-tolerant personality perfectly.
This has, of course, become a running point of amusement between Steph, Tyler, and myself, because unlike the two of them, I’ve stayed a consummate city boy, with no desire to camp or hike. It’s even funnier because in three months, Steph and Tyler are getting married, and after the wedding, we’re all heading to Camp Saturna in Washington for a weekend of nature with a bunch of their friends, including our college crew.
"Okay, so just for calibration, how outdoorsy is everyone?" I ask, trying to get a sense of what I’m in for.
"Don’t worry, Denis,” she laughs, “there will be people who you can be bougie with."
Fast forward three months from our coffee shop conversation: the wedding weekend at Camp Saturna has just wrapped up, and everyone—myself included—is mildly impressed I survived the experience. Tyler, now officially Steph’s husband, had joked before we left, "We're going to the woods, Denis, not Mordor,” to which I replied with a GIF of Mariah Carey saying “I don’t know about that.”
But, I survived, and now, we’re driving back to Seattle from the camp. Bennett is behind the wheel of Steph’s car, Steph is in the passenger seat, and Jaime and I are crammed in the back. The car is packed with our luggage, bags, and the leftover food from the weekend. We’re driving through the peaceful roads of Washington, and I can’t keep my eyes off the magical scenery, the green fields and the quiet farms, the mountains rising in the distance, and the trees stretching out on both sides of the road.
I am thinking how, despite spending the entire weekend in serenity, many of us have been … well, unchill. Our friend Neha officiated Steph and Tyler’s wedding, and she had been stressing (just like I would have, mind you) over whether she had filled out the paperwork correctly and used the right pen color. Meanwhile, I’ve been preoccupied with a text from Alaska Airlines warning of delays due to a cyberattack at Sea-Tac airport, worried my luggage will be lost forever. And in the front, Bennett, as if he knew what I am ruminating on, has cranked up "You Think I Ain't Worth a Dollar, But I Feel Like a Millionaire" by Queens of the Stone Age, speeding up on the highway to get to Chick-fil-A, our pit stop.
I smile because, amid all this collective mental chaos, the only person completely unbothered by these irrelevant musings, fast asleep in the passenger seat, as calm as ever, is Stephanie. Abstracted away from all the worries.
