My first year in robotics academia/industry
Several conversations I had this week prompted me to share about things I learned in my first year working in robotics in academia and industry.
Academia - Lessons learned in my first few years
I recently had a conversation with a co-op at the office about this topic. He asked, “What was it like in your first year of the PhD program?” As this isn't the first time I've been asked this question, I'd like to share my thoughts here.
Here's a summary:
Be prepared: Our level of preparation should be measured based on the future environment, not the current one.
Adjust expectations based on reality: Our experience in a new environment may be far from our original expectations. Be open to reality and accept that expectations need to be adjusted based on actual circumstances.
Everyone has a different experience in their first year. In my case, it took me longer than I wished to get my head around how to live a balanced PhD life. My biggest challenge was that I was not prepared. This was a shock to me. I came with the highest GPA in my year in mechanical engineering from one of the best universities in Taiwan. I thought scoring high academic records and having several research experiences would automatically prepare me to become a thriving PhD student. But this wasn't true.
I was gauging myself against my current environment in Taiwan, without attempting to understand how prepared I was for the new environment. I thought excelling in my current environment would make me better prepared, and I'd figure out the rest when I actually started my PhD. Little did I know that "the rest" was actually the main thing I needed to know to be truly prepared.
To be more specific, using myself as an example, I had very good coverage in mechanical engineering (manufacturing, materials, statics, dynamics, fluid dynamics, controls, heat transfer, mechanical design, etc.). However, what a robotics PhD in controls needs are: linear algebra and probability (I had only spent half a semester learning either subject, and at the time, I was a bit rusty too), robotics fundamentals (I had some knowledge but not enough; I didn't really know how to compute inverse kinematics), optimization (I didn't know what linear programming was), coding (I had only done limited C# and MATLAB, and had never used Python), and platforms (I had never used Linux). I hope my case shows that we can prepare as much as we think possible, but if we don't cover the core subjects we actually need in sufficient depth, it's just not enough.
So what happens if we find out we're not prepared? This is the second thing I wish I had done better in my first several years. After the first few weeks into my PhD program, I quickly realized my lack of preparation had put me on the back foot. My first reaction was to try to push hard and play catch-up. This mentality had worked when I was in my first year of high school, but this time it didn't. The reason was simple: my labmates were pushing just as hard as I was.
I set myself an expectation that I should be performing at the same level as my peers, taking the same number of classes while producing the same amount of research results. Looking back now, that expectation was simply unrealistic. What's worse, without adjusting that expectation, I put a lot of unnecessary pressure on myself. At that time, I felt scared to change expectations. It felt like I was giving up. It took me three years to gradually realize it was better for me to adjust based on reality. In the last two years, I was finally able to study and do research at my own pace. It turns out I was far more productive compared to my first three years. Of course, this made my PhD genuinely enjoyable for me as well.
I hope these lessons I learned don't scare people away from considering a PhD. At the end of the day, we learn things as we go through different unexpected events. Whether it's smooth sailing or bumpy air, it's all part of the journey.
Industry - Lessons learned in my first year
My transition from academia to industry has been much smoother than expected. This is partially due to my personality and interests. I generally like interacting with people, and industry is a place where understanding and communicating with others is crucial. Therefore, I'm naturally more prepared. Still, there are new things I've learned since joining the industry:
Industry is about business. The stakes are high, and therefore, business has to be concrete. (Check out my previous articles for a comparison between academia and industry [part 1][part 2])
When there's a problem, focusing on individuals can fix it once, but focusing on the system can prevent the problem from recurring. (Check out my previous article on Mechanism)
Another question I often get is, “What's your advice for new graduates starting a new job?” (Disclaimer: I have just over 2.5 years of work experience.) My advice is to focus on developing “ownership” (one of Amazon leadership principles). It's beneficial for people to have a sense of ownership towards their work in both academia and industry. However, this can be more challenging in industry because we often think we're just working for our bosses. We don't technically “own” the company (despite having some shares).
Nevertheless, an ownership mentality is valuable when I treat my work as if it's my own project. I tend to care not just about the assignment but also about the broader scope of things related to it. This approach helps me think about how to maximize the impact of the assignment and even develop my own proposals after better understanding the broader context. A sense of ownership also helps me think long-term and better understand many leadership decisions. Companies in industry are large organizations, and this is where understanding the broader scope, taking initiative, and planning for the long-term helps me grow quickly and deliver more at work. For me, this all starts with having an ownership attitude towards my day-to-day work.