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NEWS

23 November 2022

Is it worth seeking out authorities in the world of science? Is it possible to find the perfect research problem – one equally interesting and connected with the actual challenge? Answers to these and many other questions may be found in interview with Professor Piotr Sankowski, the President of IDEAS NCBR. Enjoy the reading!

  1. A good research problem – what does it mean exactly? How can it be described?

PS: To give a satisfactory answer to these questions, we also have to decide what defines good research. For me, the crucial part is thinking about what the results may be applied for. We need to stress, that I do not mean applied “here and now”. The verification of usefulness of the results of fundamental research may take many years, but it is certainly much easier to publish research that is related to real challenges. And in my opinion, they are simply more interesting. At the universities, particularly in Poland, we are often unable to effectively combine these two parts, that are, in fact, parts of the same story. On one hand I know researchers, who strongly believe, that “the real science” should not have use. On the other hand, many persons concentrate on the work on applications with no research aspect. I think a nice illustration of this is a quote by Louis Pasteur: “There are no such things as applied sciences, only applications of science.”

This matter is an important part of the answer to the question of a good research problem, but it is not all. When choosing the research problem you should be guided by certain pragmatism, i.e. assess your chance for success. The severity of the problem is usually inversely proportional to the difficulty of solving it. That is why we need to find this perfect point for us, where we solve the most interesting problem that we have a chance to solve yet. This compromise, as it usually is with compromises, is not simple at all. Few researchers can do it instinctively, many come to it over the years, along with the growing experience.

  1. What are young researchers’ most common mistakes when looking for a research idea?

PS: In recent years, I have been meeting more and more young researchers whose research interests are fully formed before their master’s degree. To my surprise, at that point they already know what subjects they want to explore and in fact they do not want to discuss what is worth doing or listen to the older colleagues’ suggestions. As I previously mentioned, the choice of research problem is difficult and both experience and intuition increase the researcher’s chance for success. To certain point such approach is understandable – it results from major science authority crisis in Poland. Few scientists are in world’s big league. Why would these young scientists draw inspiration from them or consult them? Even though I can understand such approach, in my opinion it may be a mistake. It is worth taking some time and look for a mentor at the world level. Luckily, there are more and more fantastic scientists who decide to work in Poland. Experience in effective research is crucial in science, where problems often take years to solve.

OTHER ARTICLES

4 October 2022

Centrum Wiskunde & Informatica (CWI), the national research center for mathematics and computer science in The Netherlands and IDEAS NCBR, the Polish centre of innovation in the field of Artificial Intelligence (AI) and Digital Economy have signed a Memorandum of Understanding. With this MoU the institutes agree to make joint effort to promote scientific research and talent development, specifically in the field of computer science.

13 September 2022

With the advent of processors and the progress of data science (particularly computer vision and machine learning techniques), non-human actors have been trained to compete and, in an increasing number of cases, win against their homo sapiens counterparts. The benefits of creating AI players are not just about designing a bot that might invent new gaming strategies or be a fun opponent to play against. On the contrary, training such models gives us deep insights into the modern science of algorithms

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