From quantum mechanics to wind turbines, Mykolas' career path has been anything but conventional. A former PhD student at FU Berlin, Mykolas now applies his analytical skills to the field of renewable energy as a data scientist at Turbit since May. We recently had the opportunity to chat with him about his unique journey and the work he is currently doing, and our conversation revealed how diverse backgrounds can contribute to innovation in unexpected ways. Join us as we explore Mykolas' trajectory and get a glimpse of the projects he has been working on.
Patricia: Could you share a bit about your background and the journey that brought you to Turbit?
Mykolas: I studied physics at university. What I really liked about my studies wasn't so much the physics itself, but the programming and problem-solving aspects. I enjoyed taking real-life problems that physicists face and simplifying them enough to solve on paper or with a computer. This led me to machine learning, which seemed like a nice way to combine mathematics, programming, and problem-solving.
I’ve also explored quantum computing, working on a project about doing machine learning on quantum computers during my masters. I started a PhD in quantum computing in Berlin, but realized it wasn't for me. I wanted to work more with other people and on something less abstract, where I could see the tangible effects of my work.
That's when I remembered how much I enjoyed machine learning, so I started looking for data science jobs. That's how I ended up at Turbit. I like that we do applied work, work closely as a team, and you can really tangibly say that we're helping the world by making renewable energy more accessible.
Patricia: Could you tell us more about the project you're currently working on?
Mykolas: We're developing a chatbot designed to help wind turbine operators deal with the massive amount of documents they handle. Different technicians perform various inspections on wind turbines and write reports. Operators are overwhelmed with these documents and often can't utilize all the insights.
Our job is to take in all these documents, store them, and parse them appropriately. This allows operators to ask questions like, "Are there any abnormalities with turbines in wind park X or Y?" We can then provide specific answers, like "This turbine had gearbox oil faults two months ago," and provide the sources.
In the future, we envision the chatbot suggesting actions, not just summarizing issues. It could provide a to-do list, suggest causes for problems, or even generate emails to relevant personnel.
Patricia: How does your expertise contribute to Turbit's mission in the renewable energy sector?
Mykolas: This field is super novel, with a lot of new developments in the past two or three years. There's no established way to do it, so it almost becomes a research job to figure out how to best apply these new tools in wind energy.
My research experience helps me navigate through all this new stuff without losing focus, while staying open-minded and trying things out. My background in machine learning research gives me a good foundation for approaching this systematically.
Patricia: What does a typical day of work look like for you?
Mykolas: Being a startup, we all share each other's traditional roles. As a data scientist, I do a lot of what a software engineer might do, and vice versa. About 60% of my time is spent developing code. Then 20% is meetings and brainstorming with people, which is great because we spend a big chunk of time bouncing ideas off each other. The remaining 20% is researching about large language models, or just staring at a wall and thinking about how to solve something. Sometimes you need that too.
Patricia: What inspires you the most in your daily work?
Mykolas: I still like to imagine I'm a physics student solving a problem on a blackboard. I look at it like a game. I really enjoy taking a messy problem filled with real-life complications and simplifying it as much as possible. Figuring out what's really the key to solving this or what makes it different from other problems. I really like when I'm able to make a nice abstraction of a real problem, finding ways to simplify it to its core essence.
Patricia: What are your passions and hobbies outside of work?
Mykolas: I really like to cook. I enjoy cuisines from all over the world. I'm really good at this Japanese dish called katsu curry. I also really like playing football. I try to do it every week, but sometimes it doesn't work out or it's too hot outside. I like playing pool too.
Patricia: Do you find time to do all this with your work?
Mykolas: Yes, I would say there's a good work-life balance here.
Patricia: What are some areas at Turbit where you see potential for improvement?
Mykolas: We have so many ideas and so much to do, but not enough people to do everything. So we just need more people. But I really appreciate that in this company, we take hiring very seriously and make sure people are the right fit before they join. It takes time, and we're still growing, so we don't have all the resources to hire everyone yet. But yeah, we just need more manpower and womanpower.
Patricia: Thank you so much for your time, Mykolas.
Mykolas: Yeah, no worries. My pleasure.
After our conversation with Mykolas, we were left with a clear sense of the innovative work happening in wind energy. His journey from physics to data science highlights the value of diverse perspectives in tackling complex challenges. As Mykolas and the whole Turbit’s team continue their work, we are reminded that progress often comes from unexpected places. The future of renewable energy looks promising, thanks to the creativity and dedication of professionals like Mykolas.
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