Emily Fortuna entered Rice University with a lot of interests. The Computer Science alumna chose Rice because it offered a great selection of majors for a university with a student enrollment about the same size as her high school.
“CS was appealing to me because it applies to so many different fields,” she said, “Majoring in CS was a way to kick the can down the road and keep my options open. Chemistry? Chemists use computer modeling. There are also applications in psychology and biology, just to name a few. I took organic chemistry, materials science, music and social science classes, and ultimately felt CS could be applied to any of them.
“But CS also taught me a style of thinking. In contrast, my organic chemistry classes required a lot of memorization. While memorization is important to be able to work at a deeper level in any discipline, I loved the problem-solving, engineering-based thinking the instructors incorporated in my CS classes.”
Fortuna felt particularly drawn to artificial intelligence (AI), given its intersection between computing and psychology. She double majored in both Computer Science and Linguistics, in hopes of combining what she learned in the two disciplines to study Natural Language Processing.
“Some upperclassmen recommended I talk to Devika Subramanian as a resource for learning more about AI, even before I took any of her courses. She gave me a fresh perspective that was instrumental in my decision to major in CS and I even ended up doing a small AI research project with her.”
She also found herself thriving in COMP 314. The applied algorithms and databases course was taught as a projects-based class, and consisted of only three assignments. Each assignment was roughly three weeks long and included room for creativity.
“There was always the opportunity to make it your own,” said Fortuna. “Most of the projects were designed to be open-ended, with space for taking it further if you were so inspired.” She enjoyed the class so much she became one of Dan Wallach’s teaching assistants the next time the course was offered.
The next discipline of CS Fortuna discovered an interest in was the world of compilers. “I didn’t anticipate loving compilers when I signed up for COMP 412, but Keith Cooper and Tim Harvey taught it in such a fun way, and I loved finding ways to squeeze as much performance out of a program as possible.
“After the class, I worked on a research project with Keith and Tim the summer between graduating from Rice and heading to the University of Washington for grad school. I had such a great experience that when I got to UW, I knew I wanted to focus on either Natural Language Processing/AI, compliers, or some combination thereof. I ended up working more on compilers and computer languages rather than natural languages, which led to my current role at Google. Keith’s approach to compilers has had a strong influence on my career.”
Fortuna originally applied to graduate school with the intention of becoming a teaching professor. But after observing her adviser, she witnessed what a small portion of a faculty member’s time is devoted to teaching.
“I realized teaching was a much smaller part of professor’s job than I had anticipated,” said Fortuna, “and for me personally, I decided the time investment of getting a Ph.D. was not worthwhile if I didn’t want to become a professor.”
Her undergraduate internships with NIST, National Instruments, and Microsoft, and her graduate school internship at Google all helped solidify the shift in her career interest. Fortuna found she preferred working in collaborative environments with teams larger than those she found in university departments.
“Academia has its benefits, but industry was a much more collaborative and social atmosphere that I preferred. And you still get to solve interesting problems in industry. For me, the ideal work environment is a combination of writing code that solves tricky problems and having a good time with my co-workers,” she said.
Now a software engineer at Google’s Seattle campus, Fortuna appreciates the advantages of working on a relatively small team that’s part of a global corporation.
“I am part of the Dart team, which is an open source programming language that Google created for developing web and mobile applications. I am part of a smaller sub-team within the larger group, but we all sit together. The space is set up so that I can overhear conversations with other teams, which makes it easy to stay in the loop. And anyone can interject if they know something helpful. But the team is also a close-knit group of people having good times and sharing stories and jokes.”
Fortuna has worked on several Google teams and stays in touch with former co-workers. Previously she played a key role in developing the artificial intelligence system used in Google Clips, an intelligent camera that takes photos and short video clips.
She encourages students interested in applying to Google to not get discouraged by the company’s popularity: “Don’t give up if you don’t hear back from Google right away, or are even turned away. It’s a big and popular company with lots of applicants. Apply again. Once you get in, there are so many different things you can work on.
“You can completely change directions or the types of projects you work on. Change teams instead of changing companies. It’s much easier to move teams, and Google gives you a lot of flexibility as well as a wide variety of projects from which to choose.”