Q&A FOR PROPSPECTIVE STUDENTS

The goal of the COOL Autonomy Lab is to foster a supportive and engaging research environment where students can learn, explore, and develop the skills essential for their future careers. We are always excited to collaborate with highly motivated students who have a strong mathematical foundation. If you are passionate about advancing the next generation of control, optimization, and learning algorithms for autonomous systems, I encourage you to reach out. Below are some guidelines and expectations outlining what you can expect from me and what I expect from you.

PhD Students

1. What is my goal for PhD students?

I strongly believe in the importance of a solid foundation. In our lab, students will have opportunities to build and strengthen their understanding of the fundamentals needed to address complex research problems. By the time they graduate, they should not only possess a strong foundational knowledge but also have developed deep expertise and tangible research results in a specific area of their choice. These early achievements will prepare them to thrive and succeed in whichever career path they pursue.

2. What type of research do I focus on: Theoretical vs applied?

Our research lies at the intersection of theory and application. We focus on developing new, efficient methods with strong theoretical guarantees, validating them through simulations, and ultimately testing them on real hardware, such as robotic platforms. Our goal is to maintain a healthy balance between rigorous theoretical development and practical implementation.

3. What do I expect from incoming PhD students?

Students joining my group should feel comfortable taking theory courses in control, optimization, and probability offered by the AE, ECE, and Math departments. During the first year, I encourage students to explore different research areas and reflect on the types of problems they are most excited to solve. Once you have completed most of your coursework (typically by the second year), your focus should shift toward tackling challenging research questions in your chosen area. I expect students to be self-motivated and independent in their research—after all, this is your degree. I already finished mine!

4. How often will I interact with PhD students?

I consider myself a very hands-on advisor—or at least I try to be. I’m always eager to learn new things, and one of the best ways to do that is through my students. I like to meet with each student at least once a week to hear about their progress, discuss challenges, and see how I can help. I believe that successful advising depends on open and consistent communication between students and their advisor.

Here are a few examples of what I don’t want to see:

1) Ghosting is extremely bad. It can mean you’re not working, have nothing to discuss, or that our communication has broken down. If we schedule a meeting, I will definitely not ghost you—and I expect the same courtesy in return.

2) Disappearing without notice. If you disappear for several weeks and only reappear with results, even impressive ones, that’s not ideal. If you can work entirely on your own, then you don’t really need an advisor! Collaboration and regular feedback are key to your growth and success.

5. How many papers do I expect from PhD students per year?

I don’t have a strict rule when it comes to publications. However, I think students should aim to publish one or two conference papers per year starting from their second year. This provides opportunities to present their work and network with peers in the research community. That said, I personally value journal publications more, as they require a deeper and more thorough investigation of the research problem to produce results of sufficient quality for acceptance.

6. What venues do I submit my papers?

I always strive to submit my work to well-known and highly regarded conferences and journals. There are two main reasons for this: (1) the likelihood of receiving high-quality reviews from knowledgeable experts (although this is not always guaranteed, especially in some machine learning conferences); and (2) the opportunity to network with and learn from top researchers in the field. Examples of such venues include CDC, ACC, COLT, IEEE TAC, and SIAM journals. I encourage my students to do the same, with the understanding that they will take the lead in preparing and submitting their work.

7. How do I decice when a student can graduate?

I do not decide when a student can graduate—that decision is ultimately made by the departmental committee. My role as your advisor is to provide honest feedback and guidance on your progress. In the end, you are the one who must decide when you feel ready to graduate. That said, you should plan your studies so that your PhD does not extend beyond seven years, which is uncommon in engineering.

8. How I finacially support PhD students?

Students joining my lab will be supported as Graduate Research Assistants (GRAs), funded through my research projects. In general, I can guarantee GRA support for approximately two years. While funding availability can be unpredictable, I always do my best to ensure my students are supported throughout their studies. I also encourage PhD students to spend at least one semester serving as a Teaching Assistant (TA), as this experience helps strengthen communication and teaching skills.

9. How to apply to our lab?

The best way to join our group is to apply to the PhD program in our department and list me as your potential advisor. I encourage you to review our recent publications and consider whether our research interests and lab culture align with your goals—specifically, how we can support your professional development and what you can contribute to our lab. If you have any questions or comments about our research, feel free to reach out via email.

MS Students

To be updated.

Undergraduates

To be updated.