Daria Alexander in Utrecht

Meet our ESR Daria Alexander

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 --   Interview with Daria Alexander   --

S: Tell us a bit about your background!

D: I grew up in Russia and I did a Bachelors in journalism at Moscow State University. After graduating, I started a Masters in Information and Communication at Paris 2 University. Afterwards I started working as a journalist, taught languages at language schools and moved to Brussels. As I wanted to teach at universities, I decided to go back to academics and do a Bachelor in linguistics at Saint Louis University in Brussels. There I heard from a fellow student about a small masters programme in Natural Language Processing at the Catholic University of Louvain and I really liked its contents. I enrolled in it, together with only 10 other students. Out of these 10 students only 3 graduated, and I am happy to be one of them.

S: How did you find out about the DoSSIER project and what made you decide to apply?

D: After I finished my masters in Natural Language Processing, I applied for positions at several companies, but I was especially looking for research positions. Luckily it didn’t work out with the companies, as the hiring teams were mostly looking for more senior people, and then I found the DoSSIER research project on LinkedIn! I was excited by the fact that it is an international project hosted by several  European countries such as Italy, Austria, the Netherlands and many more and so I decided to apply to project 9 “Identifying Work, Tasks, and Information Flows”. What I especially liked about project 9 was that I would be working in a company, so I would work at a company and do research at the same time.

S: How long are you already working on the project?

D: I’ve been working on project 9 at Spinque (an IT-company located in Utrecht which offers a knowledge graph technology to various clients) since September, so now for about 3.5 months.

S: What are your initial thoughts on DoSSIER and your experience?

D: During my interview with Arjen P. De Vries and Roberto Cornacchia‬, we immediately had a good connection and I had the impression that I would really like to work with them. Because of the COVID-19 situation, I was only able to work at the office for my first month at the company; since then I have been working from home and I see my colleagues during the online meetings. The working environment is really friendly, everyone is very open and helpful if I have any questions or problems. Even if there is something lacking in my program, my supervisors point out the good things, so I feel that it is a good environment to develop and grow.

S: What excites you the most about the field of IR and HCI?

D: What I’m most excited about are the applications of natural Language Processing for information retrieval from text. At the moment, I am doing a named entity recognition task in scientific papers. For the moment, I am analysing the ”acknowledgements” parts from which I can get information about projects, grants and contracts and establish links between them. Classical named entity recognition approaches do not work very well on this kind of text, but as the documents are written in quite formal language, we are able to use these formal structures to improve the named entity recognition for these documents.

S: Walk us through a day in the life of a DoSSIER PhD student.

D: There has been quite a difference between lockdown-days and non-lockdown days! If there were no lockdown, I would work and meet people at the office and chat with them. In the morning I would read articles and work on programs, afterwards I would have lunch with my colleagues. In the afternoon I would do some tutorials, for example machine learning tutorials and continue reading articles. Because of the lockdown, my working days now look a little bit different. After waking up I try to do some yoga , I have breakfast and then start programming. In the second half of the day, I often have meetings or read articles. From this week on I will start to write my first research paper, so this is very exciting!

This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860721