Mehdi Elahi is a Professor at the University of Bergen (UiB). He obtained his Ph.D. in Computer Science and has since published more than 100 peer-reviewed journal and conference papers. His research interest primarily focuses on AI and Data Analytics, with an emphasis on their industrial applications, particularly in Recommender Systems. He is also the co-inventor and co-owner of a US patent in this field. Mehdi Elahi has been involved in the development of several grant proposals, including a large-scale project with a budget of nearly NOK 300 million (i.e., MediaFutures) where he has served as WP-Leader (ongoing for 8 years). In his research, he has collaborated with the largest media platforms in Norway. Previously, he received prestigious research credits from major IT companies such as Amazon. His research findings have been published in some of the top outlets in the field, including a book on Social Data Analytics. He has also organized international events, including data challenges, in collaboration with leading companies such as Spotify and XING.

Conference report

• Lucien Heitz; Luca Rossetto; Benjamin Uwe Kille et al. (2025). NewsImages in MediaEval 2025 – Comparing Image Retrieval and Generation for News Articles. (external link)

Book anthology

• Himan Abdollahpouri; Mehdi Elahi (2021). MORS 2021: Multi-Objective Recommender Systems 2021. (external link)
• Anastasiia Klimashevskaia; Mehdi Elahi; Christoph Trattner (2023). Addressing Popularity Bias in Recommender Systems: An Exploration of Self-Supervised Learning Models. (external link)

Academic article

• Claudio Agostino Ardagna; Rasool Asal; Ernesto Damiani et al. (2020). From Trustworthy Data to Trustworthy IoT: A Data Collection Methodology Based on Blockchain. (external link)
• Elham Motamedi; Danial Khosh Kholgh; Sorush Saghari et al. (2024). Predicting movies’ eudaimonic and hedonic scores: A machine learning approach using metadata, audio and visual features. (external link)
• Mehdi Elahi; Danial Khosh Kholgh; Mohammad Sina Kiarostami et al. (2023). Hybrid recommendation by incorporating the sentiment of product reviews. (external link)
• Mohammad Reza Zarei; Mohammad R. Moosavi; Mehdi Elahi (2022). Adaptive trust-aware collaborative filtering for cold start recommendation. (external link)
• Mehdi Elahi; Alain Dominique Starke; Nabil El Ioini et al. (2022). Developing and Evaluating a University Recommender System. (external link)
• Shahpar Yakhchi; Amin Beheshti; Seyed-mohssen Ghafari et al. (2022). A Convolutional Attention Network for Unifying General and Sequential Recommenders. (external link)
• Stefano Savian; Mehdi Elahi; Andrea Alexander Janes et al. (2023). Benchmarking equivariance for Deep Learning based optical flow estimators. (external link)
• Benjamin Uwe Kille; Andreas Lommatzsch; Özlem Özgöbek et al. (2021). News Images in MediaEval 2021. (external link)
• Ayoub el Majjodi; Sohail Ahmed Khan; Alain Dominique Starke et al. (2024). Advancing Visual Food Attractiveness Predictions for Healthy Food Recommender Systems. (external link)
• Christoph Trattner; Dietmar Jannach; Enrico Motta et al. (2021). Responsible media technology and AI: challenges and research directions. (external link)
• Benjamin Uwe Kille; Andreas Lommatzsch; Özlem Özgöbek et al. (2022). News Images in MediaEval 2022. (external link)
• Bilal Mahmood; Mehdi Elahi; Farhad Vadiee et al. (2025). A Supervised Machine Learning Approach for Supporting Editorial Article Selection. (external link)
• Bilal Mahmood; Mehdi Elahi; Lubos Steskal et al. (2024). Can Large Language Models Support Editors Pick Related News Articles?. (external link)
• Naieme Hazrati; Mehdi Elahi (2020). Addressing the New Item problem in video recommender systems by incorporation of visual features with restricted Boltzmann machines. (external link)
• Fatemeh Elahi; Mahmood Fazlali; Hadi Tabatabaee Malazi et al. (2022). Parallel Fractional Stochastic Gradient Descent With Adaptive Learning for Recommender Systems. (external link)
• Mehdi Elahi; Danial Khosh Kholgh; Mohammad Sina Kiarostami et al. (2021). Investigating the impact of recommender systems on user-based and item-based popularity bias. (external link)

Academic book chapter

• Anastasiia Klimashevskaia; Mehdi Elahi; Dietmar Jannach et al. (2022). Mitigating Popularity Bias in Recommendation: Potential and Limits of Calibration Approaches.. (external link)
• Mehdi Elahi; Farshad Bakhshandegan Moghaddam; Reza Hosseini et al. (2021). Recommending Videos in Cold Start With Automatic Visual Tags. (external link)
• Mehdi Elahi; Himan Abdollahpouri; Masoud Mansoury et al. (2021). Beyond Algorithmic Fairness in Recommender Systems. (external link)
• Anastasiia Klimashevskaia; Mehdi Elahi; Dietmar Jannach et al. (2023). Evaluating The Effects of Calibrated Popularity Bias Mitigation: A Field Study. (external link)
• Himan Abdollahpouri; Mehdi Elahi; Masoud Mansoury et al. (2021). MORS 2021: 1st Workshop on Multi Objective Recommender Systems. (external link)
• Tord Kvifte; Mehdi Elahi; Christoph Trattner (2022). Hybrid Recommendation of Movies based on Deep Content Features. (external link)
• Ayoub El Majjodi; Mehdi Elahi; Nabil El Ioini et al. (2020). Towards Generating Personalized Country Recommendation. (external link)
• Ayoub el Majjodi; Alain Dominique Starke; Mehdi Elahi et al. (2023). The Interplay between Food Knowledge, Nudges, and Preference Elicitation Methods Determines the Evaluation of a Recipe Recommender System. (external link)
• Naieme Hazrati; Mehdi Elahi; Francesco Ricci (2020). Simulating the Impact of Recommender Systems on the Evolution of Collective Users' Choices. (external link)
• Mehdi Elahi; Reza Hosseini; Mohammad H. Rimaz et al. (2020). Visually-Aware Video Recommendation in the Cold Start. (external link)

Conference poster

• Bilal Mahmood; Mehdi Elahi; Farhad Vadiee et al. (2024). A Supervised Machine Learning Approach for Supporting Editorial Article Selection. (external link)
• Mehdi Elahi; Farshad Bakhshandegan Moghaddam; Reza Hosseini et al. (2021). Enhanced Movie Recommendation Incorporating Visual Features. (external link)
• Mehdi Elahi; Himan Abdollahpouri; Masoud Mansoury et al. (2021). Beyond Algorithmic Fairness in Recommender System. (external link)
• Van Thanh Le; Nabil El Ioini; Claus Pahl et al. (2022). Capacity-Based Trust System in Untrusted MEC Environments. (external link)

Academic literature review

• Anastasiia Klimashevskaia; Dietmar Jannach; Mehdi Elahi et al. (2024). A survey on popularity bias in recommender systems. (external link)
• Mehdi Elahi; Dietmar Jannach; Lars Skjærven et al. (2021). Towards Responsible Media Recommendation. (external link)

Master’s thesis

• Mehdi Elahi; Frank Rune Espeseth; Igor Pipkin (2023). Media Analytics for Personalization in Advertisement. (external link)
• Mehdi Elahi; Peter Kolbeinsen Klingenberg; Thomas Husken (2023). Using content- and behavioural data for recommendations in the Norwegian news market. (external link)
• Mehdi Elahi; Øyvind Johannessen (2021). Novel Methods Using Human Emotion and Visual Features for Recommending Movies. (external link)
• Mehdi Elahi; Lars Skjærven; Astrid Johnsen Tessem et al. (2024). Large-scale Evaluation of Context-Aware Recommender Systems in Media Domain. (external link)
• Mehdi Elahi; Sebastian Cornelius Bergh; Lars Skjærven et al. (2023). Personalized Recommendations of Upcoming Sport Events. (external link)
• Mehdi Elahi; Tord Kvifte (2021). Video Recommendations Based on Visual Features Extracted with Deep Learning. (external link)
• Vanessa Marie Haaland; Mehdi Elahi; Igor Pipkin (2024). Personalized Advertisement Recommendations Using Implicit Feedback. (external link)
• Mehdi Elahi; David Kvasnes Olsen; Lars Skjærven (2022). Movie recommendation based on stylistic visual features.. (external link)

Non-fiction book chapter

• Bilal Mahmood; Mehdi Elahi; Samia Touileb et al. (2024). Incorporating Editorial Feedback in the Evaluation of News Recommender Systems. (external link)

Textbook

• Amin Beheshti; Samira Ghodratnama; Mehdi Elahi et al. (2022). Social Data Analytics. (external link)

See a complete overview of publications in Cristin.

Google Scholar page: https://scholar.google.com/citations?user=aUWF7LYAAAAJ 

MediaFutures page: https://mediafutures.no/2020/11/25/mehdi-elahi/