As a graduate student at UBC, Keyi Tang conducted work on a biomechanical model of the human head and neck, where he modelled important functions such as speech and swallowing.
Today, Tang is a research engineer at Borealis AI, which focuses on developing AI products for the financial industry. He shares the importance of networking in career planning and how research keeps you humble.
Can you describe the journey to your current position?
After my Master’s of Applied Science in Electrical and Computer Engineering, I first joined a survey analysis company building text analaytics products data for a year and a half. After that, I moved on to working at Amazon as an Applied Scientist on Alexa technology for a few months.
At that point, I started to look for other opportunities to sharpen my skills. I was looking for an environment with a faster pace and diverse challenges, so I reached out to my network. One of my previous colleagues worked at Borealis AI, which is a research company under Royal Bank of Canada (RBC). He told me a bit about their long-term projects, including one on semantic parsing that their Natural Language Processing (NLP) team was working on. I found their direction really interesting, so I moved to AI Borealis, and I’ve been working there since.
Can you describe your current work?
I’m working in a team that’s doing research on semantic parsing, which is an active research area. Specifically, we’re working on text-to-Structured Query Language (SQL), which is basically trying to map free-form questions that users provide to SQL, a formal computing language.
With this technology, users will be able to ask the machine questions, and the machine will provide them with the useful data that they need.
So, we also spend some of our time trying to productize this technology.
I really enjoy this job and the challenges, because I get to tackle business problems with the most updated technologies. There’s lots of discussions happening in the team, and I get to hear lots of different ways to approach the different problems – all of which will help me in my long-term career.
How did training and time at graduate school help your career?
First, doing research helps keep me humble – it highlights to me that I don’t know everything, and that I need to do research to make claims.
If I want to propose a new feature to the company, I need to do research to prove that it’s helpful to the company. Having research skills allows me to do quantitative analyses so that I can convince the decision makers to add that new feature.
Second, my time at graduate school helped me with problem solving. Before graduate school, if I came across a problem, I would just try out a random idea to try and solve that problem – but I’ve learned that’s not always the best approach. I need to do some research, which will then help me decide the best direction to take.
Do you have any advice for someone who is interested in following your path?
Reach out to your network – whether you’ve worked with them before, or even if you’ve taken courses with them.
If they’re working in a certain company or field, ask them about the position and the work culture, and see if you can get a referral. Others have reached out to me through LinkedIn, and I have given referrals to them. These internal referrals can be very helpful to an application, since certain companies can be buried with tons of resumes.
Interested to learn more about what Keyi Tang is working on? Click here to learn more about his latest product, or email him at keyit92@gmail.com.