Matura 2025

Dr. Wacharamanotham forscht am Institut für Informatik UZH an der Schnittstelle zwischen Mensch und Maschine und wurde 2019 mit dem Award for Best Teaching der UZH ausgezeichnet. Hier seine Rede, die er in der vollen Aula für die maturi und maturae 2025 hielt.

Last month, I found myself in Paris working on a study of how we can let a surgeon call into a hospital and help their colleague operate on a patient through an augmented reality on their mobile phone. If I could turn back time to tell the young Chat about this future when I was about to graduate from high school, my past self would have said, "No way!" (Because, back then, young Chat thought):

- The telephone has only voices.

- Before you could connect to the internet, the patient would have died already!

- When you see blood, you faint!

Oh, little Chat, you are so wrong.

I would like to share a story about the choices I made and what I learned along the way.

Twenty-four years ago, I was about to graduate from high school. I want to be a programmer, to write code and make computers do whatever I say. I had a clear three-step plan: 1. Get a bachelor's degree, 2. Get a job in a big company, and 3. Get a good salary.

In my third year of undergrad, I did an internship in the IT department of a big company. It went well. At the end of the internship, I received a job offer. However, after that experience, I had learned that system administration jobs weren't for me.

During my undergraduate studies, I took several biology courses and became fascinated by how cells work. It's fascinating to learn how the codes in the DNA are transcribed into RNA, which is then synthesized into proteins that are exported as neurotransmitters. Around that time, the Human Genome Project aimed to sequence all human DNA, which was then understood as a "source code of life". It was advertised that if we knew the code of life, we could fix diseases or even allow us to live forever. Well, we are in 2025, and we haven't fixed the diseases yet, and no one can live forever. From this situation, we learn that our collective horizon into the future is quite limited. Nevertheless, the young Chat doesn't know that yet. He thought that. Oh! DNA, RNA, and protein are like source code. We can program living things! And there's a combination of computer and biology called bioinformatics! The catch was that bioinformatics was so new that it could not be studied in Thailand, so I needed to study abroad.

After sending out several applications, I had two choices: A bioinformatics program at a university in the U.S. or coming to Europe and studying informatics. If I had chosen based on my interest alone, I'd have gone to the U.S. My parents were open about these choices and insisted they could support me. But I can see that it will be a burden for them. If I go to Europe, I'll receive a scholarship. Although the European program does not specialize in bioinformatics, there are several courses in this area that I could take. It is not ideal, but not so bad either.

I was in an Erasmus Mundus program. It was a two-year program at two universities. My first year was at the University of Edinburgh in the UK, and my second year was at RWTH Aachen University in Germany. Bioinformatics courses are only available in Edinburgh, so I maxed out my credit for these courses. I even had to audit some courses because they are outside of my program of study. One of the courses I audited was a course on machine learning. I became fascinated with how mathematical models can effectively explain and predict real-world phenomena. On the other hand, the bioinformatics courses were taught by biologists. And they were fascinated by how they could search genome databases or create a computer simulation of proteins. But in my eyes, with my background in computer science, I see this kind of work as boring. It is like being a system admin for biologists.

In the second year of my study in Germany, I learned about Human–Computer Interaction or HCI. It opened my eyes to the other side of computing: the people who use the computer. I learned how scientific knowledge about human perception, cognition, and social interaction can explain and predict how people learn how to use computer software, gain mastery over these tools, or have their behavior changed by computers.

In Germany, many master's students also work as research assistants. Because I had already taken a lot of courses in my first year, I had a lot of free time, so I took two student assistant jobs. Although I was somewhat disillusioned in bioinformatics, I still want to learn more about this field, so I got to work in a medical image processing lab. That was the opportunity nearest to bioinformatics that I could find. In the meantime, I also worked as a second job in the HCI lab. I took both jobs because I wanted to know more about what researchers do in these fields before I make my move.

At the image processing lab, I was assigned to code image processing algorithms into a big medical image system that they were building. At the HCI lab, I was assigned to implement a program that recognizes the movement of conductors' batons. That was
ten times more exciting! At the HCI lab, I also had great senior colleagues who allowed me to sit next to them while they worked and explained their thought processes. With my increased interest in HCI and the great work environment, I decided to pursue my PhD in HCI at RWTH Aachen University.

During my PhD study, it happened that people in the lab focused on designing and building tech, but we lacked knowledge on evaluation: how to design a study that validates the technologies, and how to choose the right statistics. So, I took it upon myself to read up about these methods besides my work. If my undergrad self knew about this, he would find it very strange. In fact, I hated statistics when I was an undergrad. I didn't appreciate how it works and why it is useful. It was only because of my knowledge about machine learning that I saw the big picture. I also organized a study group with students who were working in the lab at the time.

It turned out that one student from that study group went on to become a researcher in a robotics lab in Paris, and he needed help with study design, so he brought me into this cool project. So, have I overcome my fear of blood? No. But I don't need to because in this project, I work in a team with surgeons and other experts who take care of those bloody parts.

To draw the lessons from my story, I would like to point out some choices I’ve made. I'll call them "big choices" and "small choices". The big choices in my life were:

- Choosing to study abroad instead of getting a well-paid job in Thailand

- Choosing to come to Europe instead of the US

- Choosing to do a doctoral degree in human-computer interaction instead of image processing

I ended up making these "big choices" based on constraints and opportunities at the time. And I couldn't have foreseen how impactful this situation would be in governing these big choices.

What's more interesting are the small choices. These were when I

- chose to audit a machine learning class

- chose to take up two student assistant jobs

- chose to become a self-taught statistician and organize a reading group

These small choices ended up either opening doors to new opportunities that I couldn't have known of in the past.

Graduates, big choices are hard to anticipate because you will have a limited horizon into the future, and situational factors will greatly influence your decision.

The recent advancements in artificial intelligence add uncertainty to your future. There will be some jobs that will become obsolete, but there will also be new opportunities showing up. How can we navigate this uncertain time? Graduates, pay attention to small choices. Making them well could open doors to opportunities that you couldn't know. But if you made the wrong small choice, don't sweat it. You get to make a better choice again very soon.

I want to suggest three heuristics to think about when you make these small choices. I call them the three Cs: Capability, Capacity, and Coverage.

- Capability: Choose what will make you more capable of solving important problems in the world

- Capacity: Choose what will increase your capacity to influence the world directly by yourself or indirectly via your colleagues and team

- Coverage: Choose what increases coverage of your knowledge for the big choices you will face.

Graduates, the choices are yours. Make them wisely.