About me

I am an assistant professor at Polytechnic University of Bari (Politecnico di Bari), affiliated with the Information Systems Laboratory (SisInf Lab), with the lead of research group done by Prof. Tommaso di Nioa. Prior to that, I was a postDoctoral Researcher at SisInf Lab, Polytechnic University of Bari and a research collaborator at IR Lab-University of Milano Bicocca, Italy overall for a period of 1.5 year. My main areas of research span a range of topics focusing largely on recommender systems.

I graduated in Electrical Engineering from Chalmers University of Technology (CTH) by completing MSc thesis at Multimedia Department of Ericsson Research in Stockholm, Sweden. My MSc courses were completed at three leading technical univeristies in Sweden: Royal Institute of Technology (KTH), Chalmers University of Technology (CTH), and Blekinge Institute of Technology (BTH) where I ranked first among all fellow students of the programme with straight A+ GPA (see here). I was awarded a PhD degree with distinction in Computer Science from Polytechnic University of Milano (Politecnico di Milano). During my PhD, I was a visiting researcher at Institute of Computational Perception, Johannes Kepler University (JKU) Linz, Austria for a period of 6 months. I had the pleasure to work with Paolo Cremonesi In addition, I studied English Linguistics at University of Gothenburg (GU), which lead to a Bachelor's degree in Art.

I have (co-)authored different refereed articles at internationally recognized conferences and peer-reviewed journals among others published in Journal of UMUAI, IEEE TKDE, Journal of Data Semantics, ACM RecSys, ACM MMSys, ACM CHI in addition to a 2018 US Patent. I have served as a PC member or reviewer for different top-tier conferences and journals. I have been involved in organization of the ACM RecSys Challenges 2019 (hosted by Trivago) and ACM RecSys Challenges 2017 (hosted by Xing ) as part of the ACM Conference on Recommender Systems as well as MediaEval Benchmarking Initiative for Multimedia Evaluation with the focus on leveraging multimedia content for enhancing recommendation of different products (media or non-media items). To know more about my research activities, see my publication page.

Special Issues News

• *New* Special Issue call for papers on "Multimedia Recommendation Systems" in International Journal of Multimedia Information Retrieval - Springer (Deadline: Oct 1st, 2019 Nov 1st, 2019)

Current Research Topics

• Recommender systems, user modelling and personalization
• Multimedia Recommender Systems
• Fairness of Recommender Systems
• Advanced Machine Learning (Advarsarial Learning, Federated Learning)

Academic Services

• Organizer: ACM RecSys Challenge 2019 (session-based hotel recommendation/Trivago), ACM RecSys Challenge 2017 (Job Recommendation/Xing), MediaEval 2019 (MovieRec and NEWSReel), MediaEval 2018 (MOvieRec)
• PC Member: RecSys 2019, ACM Multimedia 2019, UMAP 2019, ECIR 2019, MMSys 2019, ExHumWS@UMAP2019, RecSys Challenge WS 2017, 2018, 2019
• Reviewer: SIGIR, CIKM, AAAI, ACM MM, RECSYS, ECML-PKDD, ECIR, IDC, IPMU

Selected Publications

• Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara. "Towards Effective Device-Aware Federated Learning", AIIA 2019.
• Yashar Deldjoo, Yashar Deldjoo, Vito Walter Anelli, Hamed Zamani, Alejandro Bellogin, Tommaso Di Noia. "Recommender Systems Fairness Evaluation via Generalized Cross Entropy", RMSE@RecSys'19.
• Yashar Deldjoo, Maurizio Ferrari Dacrema, Mihai Gabriel Constantin, Hamid Eghbal-Zadeh, Stefano Cereda, Markus Schedl, Bogdan Ionescu, Paolo Cremonesi. "Movie Genome: Alleviating New Item Cold Start in Movie Recommendation", UMUAI 2019.
• Vahid Jalili, Matteo Matteucci, Jeremy Goecks, Yashar Deldjoo, Stefano Ceri."Next Generation Indexing for Genomic Intervals", TKDE 2018.
• Yashar Deldjoo, Mihai Gabriel Constantin, Hamid Eghbal-zadeh, Markus Schedl, Bogdan Ionescu, Paolo Cremonesi."Audio-Visual Encoding of Multimedia Content to Enhance Movie Recommendations", RecSys 2018.
• Yashar Deldjoo, Mihai Gabriel Constantin, Markus Schedl, Bogdan Ionescu, Paolo Cremonesi."MMTF-14K: A Multifaceted Movie Trailer Feature Dataset for Recommendation and Retrieval", MMSyS 2018.
• Yashar Deldjoo, Markus Schedl, Paolo Cremonesi, Gabriella Pasi."Content-Based Multimedia Recommendation Systems: Definition and Application Domains", IIR 2018.