Why did you start in the field of computer science?

I was very interested in the world of computers. During high school, I also did web development. I created simple websites and experimented with what I could make of them. I also delved deeper into 3D modelling. But after high school, I decided I wanted to work in computer science long-term. One of the attractions of the field was that many other disciplines connect to it: from medicine to bioinformatics to engineering. One inspiration was a book about Ada Lovelace. She and Charles Babbage practically invented the first mechanical computer almost two hundred years ago. Part of their story motivated me to pursue a degree in this field. I was accepted to the American University of Armenia, one of Armenia's top higher education institutions. There, I had the freedom to not only focus on my studies but also to figure out what I wanted to do with the knowledge I gained. Over time, I became increasingly interested in machine learning and artificial intelligence (AI) as it became a hot topic; OpenAI and Google research breakthroughs occurred during my university years.

You participated in the WorldQuant International Quant Championship, one of the most respected global contests in quantitative finance and data science. How did financial topics catch your interest?

I learned about the organisation and its international competition this year, and I saw that I could deepen my involvement in everything I love there. This includes mathematics and AI as well. I liked that you had to develop models used for prediction that would stand on their own in the world of finance. It was attractive because it required serious logical thinking.

How long did the project you worked on take? Was anything particularly challenging during the competition?

It required daily engagement, but I didn’t find it tiring at all because I didn’t approach it as an obligation. The task was directly related to my area of interest, and I was working on what I already wanted to do anyway. It was a little difficult to come up with several new ideas every day. This is a skill I developed during the competition.

After completing your studies in Armenia, how did you find Hungary? What made you choose Pázmány University?

During my teenage years, I participated in a project that involved scanning people and creating 3D models. Six of us took part, and we all became good friends. One of them continued his studies in Hungary. Four years later, when he wrote that he had earned his master’s degree in Hungary, I looked into local opportunities and found that Pázmány had a special programme focusing on machine learning. It was exactly the area that interested me, and there were scholarships available. That was important because during my undergraduate studies, my parents supported me financially. After that, I wanted to help them.

What might help students like math more?

It matters a lot how we present mathematics to children. If we connect math with everyday life, it’s easy to spark students’ curiosity. But if it only appears as another mandatory task with a lot of random symbols, students quickly get lost. Human examples can also help, so students see that even research mathematicians sometimes get stuck. That’s part of the journey to success. When you get stuck on a problem and try again, often you learn something valuable. For example, many Hungarian scientists have contributed to this field. You could mention Paul Erdős or John von Neumann, who laid the foundations for today’s computers.

Beyond the competition, what drives you? What is your main motivation?

My motivation partly comes from knowing that artificial intelligence can generally improve everyday life. I think it’s important to see the big picture in what you do every day. Whether it’s ecological problems or diseases, technology can produce solutions that bring meaningful, positive change. I hope to contribute to that throughout my career. It is also motivating when you manage to achieve something that was previously thought to be impossible, somewhat like Elon Musk’s motivation to reach Mars. It’s fascinating when a computer does something that resembles human thinking.

How do you see the future of AI? As AI solutions become smarter, how will people remain relevant alongside machines?

At the competition, it was visible that teams that relied on human creativity while also applying AI were more successful than those that left most tasks to machines. If we combine human expertise with AI, I think we can be much more effective than if we build a system that tries to solve everything for us. Human knowledge remains key. The human side cannot be excluded.

What are your plans for the future?

I don’t have final plans yet. I’m considering continuing my scientific and professional development in Hungary while staying in touch with my home country: for example, by creating initiatives that benefit Armenia as well. There are many opportunities in my field in Hungary. I also plan to continue collaborating with WorldQuant, which organised the competition.

Have you ever thought about teaching?

I’ve worked as a volunteer lab leader, and it was a good experience. But if I were to teach, I would first need to accomplish many things so I could have real experience to share with students. I am currently in a master’s programme, with about 1.5 years left until graduation. I am very happy about this competition because it gives me strength for my journey. I feel I am on the right path.

This interview article was adapted from an original interview published on Uniside.hu. Source: https://uniside.hu/egy-ormeny-diak-utja-nemzetkozi-sikerig-magyar-szinekben-gyozott/