Today marks the 10th anniversary of the International Day of Women and Girls in Science, an opportunity to recognize both achievements and ongoing challenges. While we celebrate the highly valuable contributions of women in research, we must also acknowledge that tech-related fields, including AI and media technology, still lack a diverse representation, often rooted in systemic barriers and biases.

At MediaFutures, we believe that innovation thrives when different perspectives come together. The development of responsible AI cannot be shaped by a single group alone – it must reflect a broad range of experiences, backgrounds, and ways of thinking. Diversity goes also beyond gender: It includes culture, language, ability, and many other factors that shape how we understand and develop technology. Ethical and impactful research depends on inclusivity, ensuring that technology serves society as a whole, rather than reinforcing biases or limitations.

Women in science play a key role in driving forward collaboration, integrity, and curiosity – core values in our work. We are proud of the many women in our center who are shaping the future of responsible media technology.

In recognition of today’s occasion, we asked four of our researchers about their role models, motivations, and advice for women aspiring to work in research. You can read their answers below.

Anastasiia Klimashevskaia
Anastasiia Klimashevskaia, PhD Candidate, UiB
Publications

2024

Anastasiia Klimashevskaia; Mehdi Elahi; Dietmar Jannach; Christoph Trattner; Simen Buodd. Empowering Editors: How Automated Recommendations Support Editorial Article CurationRecSys 2024, INRA workshop, 2024. 

Anastasiia Klimashevskaia; Dietmar Jannach; Mehdi Elahi; Christoph Trattner. A Survey on Popularity Bias in Recommender Systems. In: User Modeling and User-Adapted Interaction (UMUAI), 2024.

2023

Anastasiia Klimashevskaia; Mehdi Elahi; Dietmar Jannach; Lars Skjærven; Astrid Tessem; Christoph Trattner. Evaluating The Effects of Calibrated Popularity Bias Mitigation: A Field Study Conference. Association for Computing Machinery (ACM) RecSys ’23, 2023. 

Lilja Øvrelid, Professor, UiO
Publications

2024

Étienne Simon; Helene Olsen; Huiling You; Samia Touileb; Lilja Øvrelid; Erik Velldal. Generative Approaches to Event Extraction: Survey and Outlook Proceedings. 2024. 

Samia Touileb; Jeanett Murstad; Petter Mæhlum; Lubos Steskal; Lilja Charlotte Storset; Huiling You; Lilja Øvrelid. EDEN: A Dataset for Event Detection in Norwegian News Conference. LREC-COLING 2024, 2024.

2023

David Samuel; Andrey Kutuzov; Samia Touileb; Erik Velldal; Lilja Øvrelid; Egil Rønningstad; Elina Sigdel; Anna Palatkina. NorBench – A Benchmark for Norwegian Language Models Conference. 2023.

Samia Touileb; Lilja Øvrelid; Erik Velldal. Measuring Normative and Descriptive Biases in Language Models Using Census Data Conference. 2023.

2022

Samia Touileb; Lilja Øvrelid; Erik Velldal. Occupational Biases in Norwegian and Multilingual Language Models Workshop. 2022.

2021

Christoph Trattner; Dietmar Jannach; Enrico Motta; Irene Costera Meijer; Nicholas Diakopoulos; Mehdi Elahi; Andreas L. Opdahl; Bjørnar Tessem; Njål Borch; Morten Fjeld; Lilja Øvrelid; Koenraad De Smedt; Hallvard Moe. Responsible media technology and AI: challenges and research directions Journal Article. In: AI and Ethics, 2021.

Samia Touileb; Lilja Øvrelid; Erik Velldal. Using Gender- and Polarity-informed Models to Investigate Bias Working paper. 2021.

2020

Samia Touileb; Lilja Øvrelid; Erik Velldal. Gender and sentiment, critics and authors: a dataset of Norwegian book reviews Journal Article. In: Gender Bias in Natural Language Processing. Association for Computational Linguistics, 2020, (Pre SFI).

J Barnes; Erik Velldal; Lilja Øvrelid. Improving sentiment analysis with multi-task learning of negation Journal Article. In: 2020, (Pre SFI).

J Barnes; Lilja Øvrelid; Erik Velldal. Sentiment analysis is not solved! Assessing and probing sentiment classification Proceedings. 2020, (Pre SFI).

Lilja Øvrelid; Petter Mæhlum; Jeremy Barnes; Erik Velldal. A Fine-Grained Sentiment Dataset for Norwegian Proceedings. 2020, (Pre SFI).

F Jørgensen; T Aasmoe; ASR Husevåg; Lilja Øvrelid; Erik Velldal (Ed.). NorNE: Annotating Named Entities for Norwegian Proceedings. 2020, (Pre SFI).

2019

Jeremy Barnes; Samia Touileb; Lilja Øvrelid; Erik Velldal. Lexicon information in neural sentiment analysis: a multi-task learning approach Conference. Linköping University Electronic Press, 2019, (Pre SFI). 

2018

Andrey Kutuzov; Lilja Øvrelid; Terrence Szymanski; Erik Velldal. Diachronic word embeddings and semantic shifts: a survey Proceedings. 2018, (Pre SFI).

Erik Velldal; Lilja Øvrelid; Eivind Alexander Bergem; Cathrine Stadsnes; Samia Touileb; Fredrik Jørgensen. NoReC: The Norwegian Review Corpus Proceedings. 2018, (Pre SFI).

2016

Lilja Øvrelid; Petter Hohle. Universal dependencies for Norwegian Proceedings. 2016, (Pre SFI).

2012

Emanuele Lapponi; Jonathon Read; Lilja Øvrelid. Representing and resolving negation for sentiment analysis Proceedings. 2012, (Pre SFI).

Erik Velldal; Lilja Øvrelid; Jonathon Read; Stephan Oepen. Speculation and negation: Rules, rankers, and the role of syntax Journal Article. In: 2012, (Pre SFI).

Khadiga Seddik, PhD Candidate, UiB
Publications

2024

Khadiga Seddik. Exploring the Ethical Challenges of AI and Recommender Systems in the Democratic Public Sphere Conference. 

2023

Khadiga Seddik; Erik Knudsen; Damian Trilling; Christoph Trattner. Understanding How News Recommender Systems Influence Selective Exposure Conference. Association for Computing Machinery (ACM) RecSys ’23, 2023.

Samia Touileb, Associate Professor, UiB
Publications

2024

Étienne Simon; Helene Olsen; Huiling You; Samia Touileb; Lilja Øvrelid; Erik Velldal. Generative Approaches to Event Extraction: Survey and Outlook Proceedings. 2024.

Bilal Mahmood; Mehdi Elahi; Samia Touileb; Lubos Steskal. Can Large Language Models Support Editors Pick Related News Articles? Conference. NIKT 2024, 2024.

Bilal Mahmood; Mehdi Elahi; Fahrhad Vadiee; Samia Touileb; Lubos Steskal. A Supervised Machine Learning Approach for Supporting Editorial Article Selection Working paper. 2024.

Bilal Mahmood; Mehdi Elahi; Samia Touileb; Lubos Steskal; Christoph Trattner. Incorporating Editorial Feedback in the Evaluation of News Recommender Systems Conference. ACM UMAP 2024, 2024.

Samia Touileb; Jeanett Murstad; Petter Mæhlum; Lubos Steskal; Lilja Charlotte Storset; Huiling You; Lilja Øvrelid. EDEN: A Dataset for Event Detection in Norwegian News Conference. LREC-COLING 2024, 2024.

2023

Ghazaal Sheikhi; Samia Touileb; Sohail Ahmed Khan. Automated Claim Detection for Fact-checking: A Case Study using Norwegian Pre-trained Language Models Conference. 2023.

David Samuel; Andrey Kutuzov; Samia Touileb; Erik Velldal; Lilja Øvrelid; Egil Rønningstad; Elina Sigdel; Anna Palatkina. NorBench – A Benchmark for Norwegian Language Models Conference. 2023.

Samia Touileb; Lilja Øvrelid; Erik Velldal. Measuring Normative and Descriptive Biases in Language Models Using Census Data Conference. 2023.

2022

Samia Touileb; Debora Nozza. Measuring Harmful Representations in Scandinavian Language Models Conference. 2022.

Samia Touileb; Debora Nozza. Measuring Harmful Representations in Scandinavian Language Models Proceedings Article. In: Proceedings of the Fifth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS), 2022.

Petter Mæhlum; Andre Kåsen; Samia Touileb; Jeremy Barnes. Annotating Norwegian language varieties on Twitter for Part-of-speech Workshop. 2022.

Samia Touileb; Lilja Øvrelid; Erik Velldal. Occupational Biases in Norwegian and Multilingual Language Models Workshop. 2022. 

Andrei Kutuzov; Samia Touileb; Petter Mæhlum; Tita Enstad; Alexandra Witteman. NorDiaChange: Diachronic Semantic Change Dataset for Norwegian Book Chapter. In: pp. 2563-2572, European Language Resources Association NVI-nivå 1, 2022, ISBN: 979-10-95546-72-6.

2021

Samia Touileb; Lilja Øvrelid; Erik Velldal. Using Gender- and Polarity-informed Models to Investigate Bias Working paper. 2021.

2020

Samia Touileb; Lilja Øvrelid; Erik Velldal. Gender and sentiment, critics and authors: a dataset of Norwegian book reviews In: Gender Bias in Natural Language Processing. Association for Computational Linguistics, 2020, (Pre SFI).

Wafia Adouane; Samia Touileb; Jean-Philippe Bernardy. Identifying Sentiments in Algerian Code-switched User-generated Comments. 2020, (Pre SFI).

Pierre Lison; Aliaksandr Hubin; Jeremy Barnes; Samia Touileb. Named Entity Recognition without Labelled Data: A Weak Supervision Approach. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 1518–1533, 2020, (Pre SFI).

2019

Jeremy Barnes; Samia Touileb; Lilja Øvrelid; Erik Velldal. Lexicon information in neural sentiment analysis: a multi-task learning approach Conference. Linköping University Electronic Press, 2019, (Pre SFI).

2018

Erik Velldal; Lilja Øvrelid; Eivind Alexander Bergem; Cathrine Stadsnes; Samia Touileb; Fredrik Jørgensen. NoReC: The Norwegian Review Corpus Proceedings. 2018, (Pre SFI).

2017

Samia Touileb; Truls Pedersen; Helle Sjøvaag. Automatic identification of unknown names with specific roles Journal Article. In: Proceedings of the Second Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, pp. 150-158, 2017, (Pre SFI). 

What do you enjoy most working in research?
Anastasiia Klimashevskaia

“I enjoy working in research because it’s a very dynamic and ever changing environment, with interesting people and where the knowledge is shared freely. I also like working with engaged and curious students, helping them discover new things.”

Lilja Øvrelid

“I started doing research because I really enjoyed the focused, problem-solving tasks involved in doing research and seeing a project through from the early stages of planning, through experiments, analysis and final write-up of a paper. Over time I have come to enjoy the fact that the job is very varied and involves both the focused, solitary work, but also a lot of collaboration, mentoring and dissemination, which means that every day is different and I get to use different sides of myself at work. Growing into a more senior role in academia means more leadership responsibilities and a focus on helping young researchers develop their own research agendas, which is also very meaningful.”

Khadiga Seddik

“What I enjoy most about working in research is the constant opportunity to learn and discover. Every project feels like solving a puzzle, asking questions, testing ideas, and uncovering new insights. I love that research allows me to connect with brilliant minds from different backgrounds, exchange ideas, and see the world from new perspectives. he fact that research is always evolving means there’s never a dull moment, there’s always something new to explore, and that keeps me excited every day.”

Samia Touileb

“Having the opportunity to contribute to knowledge that hopefully can make a real difference in the world.”

Do you have a role model, and if so, who is that?
Anastasiia Klimashevskaia

Not one role model in particular, but many other women I met among researchers so far who are also passionate about what they are doing. When I was just starting my PhD I sometimes looked at them at conferences, seminars or talks and thought to myself “I hope that one day I could be like that too”.”

Lilja Øvrelid

Professor Janne Bondi Johannessen was the supervisor for my master thesis and introduced me to the academic world by taking me to my first conference. She was a pioneer for Norwegian NLP and a true community builder who supported and encouraged many young, female researchers to enter academia. Sadly, Janne passed away from cancer in 2020, but she left an important legacy and taught me about the importance of opening doors for others and encouraging female researchers in particular to pursue an academic career.  “

Khadiga Seddik

One of my biggest role models is Dr. Ahmed Zewail, the Egyptian scientist who won the Nobel Prize in Chemistry. Beyond his research, Zewail was deeply committed to education and using science to improve society, especially in Egypt and the Arab world. His journey from a small town in Egypt to becoming a global scientific leader is a powerful reminder that knowledge knows no boundaries.”

Samia Touileb

I don’t have one specific role model. There are countless incredible female researchers who have made significant contributions to the research community and their respective fields. However, if I were to highlight one person, it would be Professor Lilja Øvrelid (WP5 leader at MediaFutures), who played an important role in establishing Norway and the Norwegian language in the field of natural language processing.”

What is a tip you would give to future women/girls who want to work in research?
Anastasiia Klimashevskaia

Don’t be afraid to be curious and inquisitive, ask questions, have opinions, but remember to stay kind and be a nice human being.”

Lilja Øvrelid

Progress in science is built on failure, be prepared to fail: not getting the results you hoped for,  having your paper rejected etc. is all part of academic life. So don’t hide your failures away, speak openly about them and find out what you can learn from them. There is always something to learn and your research almost always improves in the end!”

Khadiga Seddik

My biggest tip for women and girls who want to work in research is to stay curious and never hesitate asking questions. Surround yourself with supportive mentors and peers, and don’t be afraid to take up space in academic discussions.”

Samia Touileb

Remember that your unique perspective is valuable. Believe in your abilities and don’t be afraid to raise questions.”