Jia Hwee Wong (JH) is a data scientist working on new algorithms for non-intrusive load monitoring. As he finished his internship under SGInnovate’s Summation Program with us, we caught up to reflect on his experience at Resync.

First of all, can you share what motivated you to work in a startup?

JH: Startups are known for their vibrant culture and for pushing the boundaries of innovation. Every project in a startup has a high degree of impact to the growth of the company and towards its goals.

Right! So, what was your project about?

JH: I worked on NILM which uses machine learning to break down total energy consumption into appliance-level consumption.

And which 3 words would best describe what you worked on?

JH: Innovation, proactiveness and faith.

I like that! I know how inventive you are with memes. Can you summarise the biggest challenge you had to overcome in a meme?

Great! So, what did you learn during your internship? How did you grow professionally from it?

JH: I learnt to be more confident in my own work and in expressing my ideas and opinions. In the past, I was a lot more reserved, and was always afraid that my ideas would get rejected and make me look bad. At Resync, thanks to the support of my colleagues, I made it a point to be more confident about my work and ideas. Some became solutions, while others were rejected. In exchange, I received feedback to learn from and grow.

What do you think is the most exciting thing you did?

JH: NILM. If we can help people save money on utility bills and indirectly conserve the environment, we will be creating a very positive impact in this world.

I want to see that happen! What will you remember most fondly from the last few months?

JH: Mala Monday (and Toilet Tuesday). Terry and Abhinav’s F45 breaks. The determined pursuit of the NILM goal with all the experiments and exchange of ideas.

Hahaha. What were your favorite aspects of being part of the team then?

JH: My team accepted me for who I am – they welcome my quirks and memes. They are also very supportive, often giving valuable advice for the project.

We will certainly miss your memes! Looking back, what do you think are the important traits to succeed as a Data Scientist?

JH: One important trait would be the willingness to keep learning. Data science is a field that is really big. It may be fashionable to learn all the exciting, state of the art techniques, especially in the area of deep learning. However, at times, deep learning does not solve everything. The project or product may require one to quickly learn and apply classical machine learning techniques or even statistical techniques. In NILM, one commonly used model is the Hidden Markov Chains. We must keep learning to both keep up with the latest and to search for specific models applicable to the problem at hand.

Thanks for your time Jia Hwee! I am sure you will do great in your next challenge.

Date of Post
Friday, Jun 25
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