But I realized during my sophomore year that I didn’t really have much of a focus. I was just thinking, “Oh, that class sounds cool,” and then doing it. That’s all fine and dandy for understanding what things you love to do – but how do you turn those loves into a future career?
In the process of figuring that out, I stumbled upon this really engaging paper, which was rare, because a lot of the stuff I was reading at the time was really dry or tough to understand for a sophomore undergrad. But this one grabbed me. It didn’t just present an interesting problem, a cool solution and some results. It introduced a problem – in this case, decision-making in self-driving cars – that took a lot of different perspectives to understand. It wasn’t just from an engineer’s point of view, but also from the point of view of the government, users and testers, and it laid out how to make a product that factored in the approach of all these different people. I just got really engrossed in it.
It turned out that paper came from professor Chris Gerdes’ lab at Stanford, where I’m now working on my PhD. He sort of became a mini academic superstar in my mind; this amazing person who’s guiding all this incredible work. When I was applying to graduate schools, his lab was my immediate first choice.
Today, I’m proud to be doing research that’s in the same vein as that paper that inspired me as an undergrad. In my lab, we work on motion and control for vehicles, and focus on vehicle dynamics at the limits of handling. We know self-driving cars will eventually be in situations where they’re at the edge of failing, whether that’s skidding off a road or just losing traction. So how can we prevent those failures and make them fail safer? To do that, you don’t just take into account the machine. It’s not just the driver. It’s the community, the government at all levels. It’s law enforcement. It’s anybody who would be interested in the decisions that car is going to make. I’m working every day on engineering challenges that take lots of different perspectives to solve, and that’s really satisfying to do.