12 Questions with Aleksandra Faust on Finding the Right Career and Being Resilient in AI


The Machine Learning Center at Georgia Tech’s Seminar Series draws leading researchers from across academia and industry each semester to present on current topics in machine learning and artificial intelligence, applications for the technologies, and related insights and experiences. The popular series averages more than 100 attendees for each talk. This fall, five experts give talks across a variety of topics.

Aleksandra Faust, a senior staff research scientist at Robotics at Google, gave a talk to a packed room on using deep learning for task and motion planning.

While Faust was on campus, ML@GT had the opportunity to talk with her about her unique journey to Google, misconceptions in artificial intelligence, and advice for students entering the job market.

Tell us about what you do at Robotics at Google.

I work on deep learning, motion planning, robotics research. We’re trying to find ways to make machine learning, robotics, and navigation more accessible and scalable for many different types of robots in a lot of different environments.

We’re really motivated by ideas like the fact that there are 11 million people in India who can’t leave their homes without some sort of device (can’t, won’t, or don’t? It makes it sound like they are bound by some regulation). That’s the total population of New York City and Los Angeles, and 3.5 million of those people never leave their homes.

We’re working on creating robots that can help these populations by bringing them medicine or providing other services for them. It’s a huge research problem and challenge though because it’s extremely difficult to create robots that can function well in structured and unstructured environments and help everyday people.

What is your favorite part, and the most challenging part of your job?

I love working with amazing people and seeing all of them grow and learn new things. I like that at the same time I get to learn and make things work. A lot of my research is open-ended so it can be hard to see the light at the end of the tunnel, especially when I work on something for a long time and it’s not working. You can’t beat the feeling when it finally works though.


What has been your favorite project to work on?

I was previously with Waymo (Google’s self-driving car group) and that was definitely a highlight. I enjoyed that work because it’s technology that can directly help many people and make their lives better.

My current work is exciting because we’re trying to introduce fundamental new methods that will enable robotics in everyday life which also has the potential to help a lot of people. There’s a lot of hope at work every day.

How did you become interested in artificial intelligence (AI) and robotics?

I originally went to school to get a Ph.D. in machine learning and I was very interested in perception and vision. On my first day of grad school, professors came to present their research and Dr. Lydia Tapia came and said, “I teach robots on how to help with behaviors,” and I was like that’s what I want to do.

It’s been interesting work because teaching robots good behaviors allows me to work with the whole system and figure out how something will make long-term decisions.


What is some advice you would give to students (particularly women) going into this field?

Love what you do. It’s really that simple!

What do you think is a misconception that people have about AI and what would you say is actually true about it?

That AI is math. I think that’s one of the biggest misconceptions. Every behavior an agent learns, how it’s trained, and what data is used comes from humans, but at the end of the day it’s getting all of that information from an algorithm.

What is it about machine learning that excites you?

I like that it’s a process of discovery. There is so much potential to make a positive impact on a lot of people. A lot of the classical machine learning methods generally do not scale up, but there is this promise and possibility of improving them and making these systems available to more people.

Why do you think it’s important for people to come and give talks like the one you gave today?

Robotics is hard. It’s really hard. It’s not something that one person or one group is going to solve. It’s about the entire community and the exchange of ideas to get to the point. So bridging different institutions or ideas is extremely important to getting these algorithms right for maximum positive impact.

What is your proudest accomplishment?

Oh gosh, I’m actually proud of a lot of things so far. Professionally, I would say that my work with Waymo is something that I am very proud of. I’m also very proud of my children. They’re teenagers now and it’s been exciting and fulfilling to see them become young adults.

What is something that you wish you knew at the beginning of your career that you know now?

I did my undergraduate degree in Serbia before moving to the United States. I wanted to go to graduate school but couldn’t because of family constraints and some other reasons. I worked for a couple of years and ended up getting my master’s in computer science. I knew I ultimately wanted to get a Ph.D. and started my degree when my first child was three years old.

One thing that I didn’t know before all of this was about scholarships for master’s students. After completing my degrees, I was at a series of workshops where somebody said, “If you do your masters at our university, we have a lot of scholarships,” which completely caught me off guard. I didn’t know that those existed and affordability nearly prevented me from pursuing my degree!

In summary, I wish I had known that it was okay to make a lot of mistakes at the beginning, and if you’re not getting an answer or finding the right answer, keep going until you figure it out. Don’t just accept no. Resiliency is key, especially in academia.


As students are looking to enter the workforce, either in academia or industry, what are some things that you would tell them to look for in an institution?

I think it’s important that they ask themselves “What excites you?” and “What end result do you want?” Some people get really excited about putting a product out, so that might lead them more to the industry side. Or they might be more excited about teaching and growing another generation of researchers, scientists, and professors. There’s also an amazing segment of people who just love research and thrive in an industry lab.

I think it’s important to find your true passions and look for jobs that align the most with them and their values. What excites you will define your career.

Tell us about something that brings you joy.

Learning something new always brings me an immense amount of joy. I love being challenged and learning new things, whether that’s in my career or in my personal life. The “aha” moment never gets old.

For more information on ML@GT seminars, visit our website.


Press Contact:

Allie McFadden

Communications Officer


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