Join Us



We are always looking to grow our team! We are looking for students across all levels of experience: from undergraduates, to Masters students, to PhD candidates, to Postdoctoral researchers. No background in robotics, parallel programming, or machine learning is required. That said, we are generally conducting research that requires mathematical maturity and programming and so we will expect some CS / EE / Math background. For CU and BC undergraduates considering taking COMS BC3159: Parallel Optimization for Robotics as it is perfect preperation for much of the lab’s research (and the course project is a perfect way to start to explore our research)! Other useful courses include: COMS W3157 Advanced Programming, CSEE 3827: Fundamentals of Computer Systems, or any courses in optimization, numerical methods, or robotics!

In general, we are looking for students who demonstrate commitment, creativity, communication skills, and courage to learn something new. We also particularly encourage students from any of the underrepresented groups in CS and Engineering to reach out about potential projects.

For Undergraduate and Masters part-time researchers during the academic semester, in order to ensure that you can have a meaningful research experience as a member of the lab we expect you to:

There are also additional opportunites for full-time summer research experiences. For Barnard students, consider applying for the Summer Research Institute (SRI).

If you have any questions, comments, or concerns, please reach out to us at: barnard.a2r.lab@gmail.com.

FAQs:

What kinds of research is the lab doing right now?

You can find descriptions of some of our current research directions on our projects page as well as our recent publications on our publications page. In general we tend to explore one of two things. First, how to combine algorithmic and computer hardware insights to accelerate robotics problems. You can find a talk exploring these concepts at this link. Second, how to increase the accessibility of cutting-edge computer science topics globally. This is best exemplified by our work with TinyMLedu.

Is the position paid?

If you are doing research through a funded research program you will be funded (e.g., PhD program, SRI summer program). For Barnard and Columbia students there are lists of possible term-time and summer funded research programs at the following links: [1], [2], [3], [4], [5], [6]. There is also a large list of national research fellowships at this link. If you do not have a research fellowship we will be constantly applying for grants to support additional student researchers, however, depending on timing, we may only be able to offer research as an independent study for credit. However, do note that you can receive elective credit towards the CS major for research done through independent studies! Note: We do not expect you to be funded to join the lab! We can work to help you get funded AFTER you join! Also if you reach out ahead of time we can work together to get you funded BEFORE you start doing research.

Does research happen all the time?

Yes, in fact, the summer is often the busiest time of the year for research! So whether you have interest and time in the sping, summer, or fall, there will always be opportunities for research!

Why should I consider doing research?

Research is a great way to learn more about a field of interest and develop both your technical and communication skills. Also, whether you are considering graduate school or industry positions, spending a few semesters doing research and publishing a peer-reviewed paper and/or presenting at regional and national conferences looks great on your resume!

Do you have any resources for getting started?

While most research projects will dive deep into specific areas of robotics and so there aren’t truly general resources that are applicale to all projects, as most (current) projects do explore hardware acceleration and optimal control to some degree, there are a few things you could do to prepare for research in the lab. First, as mentioned above, for CU and BC undergraduates considering taking my course, COMS BC 3159: Parallel Optimization for Robotics, and for CU masters students and PhDs consider TAing the course! Second, also as mentioned above, my talk at Barnard and PhD Dissertation Defense provide nice overviews of some projects I have done in the past (note that the Barnard talk is aimed at a more introductory audience). If you want to go deeper into the algorithms and math, Russ Tedrake’s Underactuated Robotics course on edX covers many of those topics. If you want to learn more about GPU programming, this online course provides a nice introduction.