Research During Masters

The visions I had for grad school have not quite been realized during my time at UPenn.

The Statement of Purpose I used for my Masters’ admissions was filled with the experiences I had when working on projects on during undergrad. I emphasized that if I was selected, my goal was to advance the state of art in robotics through research. To be clear, the feelings were genuine and based on whatever experiences I had in undergrad, I was ready to take a lighter course during my masters if it would mean more time at research. I had pretty much made up my mind to take the thesis option at Penn - granting one with the chance to do original research for two full semesters with a 20% reduction in course load to boot!

However, as I mentioned in my previous posts, my plans changed during my first year. I ended up taking time-consuming courses in my first and second semester which left little time to do research. That’s not to say it was for a lack of trying - for I did reach out to a couple of labs located at Pennovation Works, a business incubator and massive robotics research facility under one roof.

I had some good introductory conversations with the passionate PhDs and postdocs at these labs. One of the more notable discussions I had was when a postdoc at one of these labs asked me how I would solve one of the open research problems she was working on. Perplexed by the question, I said that I wouldn’t be able to answer without reading some papers and doing some background reading. After all, I had only just started approaching labs to pursue research and I wasn’t even sure where to begin till I got warmed up with the problem.

Ignoring my response, she repeated the question and asked me to try harder. When I was stumped for the second time, she said that I should try to pursue solving the problem with whatever experiences I had in my previous projects. It was a epiphanic moment for me, because till then I had always thought research would require substantial background and theory before building off existing work. Just thinking that solving a difficult problem with whatever I knew was a valid research direction in itself was a new way of thinking. I left that meeting feeling a lot more certain that I had come to the right place. Unfortunately, a couple of weeks after that meeting, COVID-19 caused the college and all research facilities to close for good. With the burden of courses and new lifestyle changes due to COVID, research was no longer at the to of my priority list and it looked like it would have to wait indefinitely.

It didn’t have to wait for long though. My summer internship ended up getting cancelled a few weeks before it was going to start, so to stay busy during the summer, I ended up taking a remote research project at a different lab from the ones I had approached earlier in the year. At first glance, the project looked like a good fit. It was about creating a autonomous system for UAVs to avoid midair collisions (think of a virtual air traffic control for quadcopters). I felt like I could leverage some of my previous work for new ideas. However, soon after I started, the cracks in my what I knew started to become apparent. The project involved using Model Predictive Control (MPC) and convex optimization for planning trajectories. I only knew about MPC in passing and convex optimization was not a topic I could hope to cover in time for doing anything new in a 12 week project. I would end up spending weeks on what I felt was a novel approach, only to find that the team of PhDs and tried it out without much luck long before. I began rethinking the existing work and it troubled me that the current research direction would only work for a very specific configuration of robots, which as anyone working in robotics knows, is rarely something which can be applied to the real world. At some point, it was clear that the project wasn’t a good fit for me, so I dropped out of the lab soon after.

So what is the message in this cautionary tale? I feel that it is much harder to get satisfactory results in short-term research projects which are heavily based on core concepts which one is unfamiliar with. It is imperative to know the background which a particular research project requires, unless your idea is to solve the problem with what you already know. I also suggest prodding an existing research approach for weaknesses, as it’s possible that new insight can patch the holes in a current direction of the research project. It’s also best not to commit early to working on a project, at least not until you have a plan of work which is both realistic, yet challenging.

My experience with research was less than ideal, but I would be curious to find out if others have been able to overcome the hurdles which come with trying out a project out of one’s depth. Do let me know about your experiences in the comments!