Sandra Mitrović, PhD

Sandra Mitrović, PhD

sandra.mitrovic@supsi.ch
Researcher
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Natural Language Processing Multi-Agent Systems Machine Learning Learning on/of Graphs Social Network Analytics Computational Psychology

Projects

Software

Publications

Article Paper Read more
Multi-Agent Systems for Software Development: a Multi-Faceted Research Question-driven Reference Guide
Sandra Mitrović, Vincenzo Giuffrida, Fabio Barth, Alba Bonet-Jover, Lidia López, Shaibal Barua, Santiago Massé, Estela Saquete, Aitana Delgado, Mobyen Uddin Ahmed, Shahina Begum, Georg Rehm, Matteo Salani Elsevier BV, 2026
Journal Paper Read more
Assessing the~Trustworthiness of~Large Language Models on~Domain-Specific Questions
Sandra Mitrović, Matteo Mazzola, Robert Larcher, Jérôme Guzzi Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2025
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Flotta: a Secure and Flexible Spark-inspired Federated Learning Framework
Claudio Bonesana, Daniele Malpetti, Sandra Mitrović, Francesca Mangili, Laura Azzimonti arXiv, 2024
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AngryBERT: Joint Learning Target and~Emotion for Hate Speech Detection
Md Rabiul Awal, Rui Cao, Roy Ka-Wei Lee, Sandra Mitrović Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2021
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Neural machine translation for conditional generation of novel procedures
Joppe Geluykens, Sandra Mitrović, Carlos Ortega-V{\'a}zquez, Teodoro Laino, Alain Vaucher, Jochen de Weerdt Proceedings of the Annual Hawaii International Conference on System Sciences, 2021
Conference Paper Read more
A Comparative Study of Representation Learning Techniques for Dynamic Networks
Carlos Ortega Vázquez, Sandra Mitrović, Jochen De Weerdt, Seppe vanden Broucke Trends and Innovations in Information Systems and Technologies, 2020
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Representation Learning in Graphs for Credit Card Fraud Detection
Raffa\"el Van Belle, Sandra Mitrović, Jochen De Weerdt Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2020
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SST-BERT at semeval-2020 task 1: Semantic shift tracing by clustering in BERT-based embedding spaces
Vani K., Sandra Mitrović, Alessandro Antonucci, Fabio Rinaldi arXiv, 2020
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A comparison of methods for link sign prediction with signed network embeddings
Sandra Mitrović, Laurent Lecoutere, Jochen De Weerdt Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019, 2019
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Benefits of using symmetric loss in recommender systems
Gaurav Singh, Sandra Mitrović Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018
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On the operational efficiency of different feature types for telco Churn prediction
Sandra Mitrović, Bart Baesens, Wilfried Lemahieu, Jochen De Weerdt European Journal of Operational Research, 2018
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Churn prediction using dynamic RFM-augmented Node2vec
Sandra Mitrović, Gaurav Singh, Bart Baesens, Wilfried Lemahieu, Jochen De Weerdt Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017
Journal Paper Read more
Scalable RFM-Enriched representation learning for churn prediction
Sandra Mitrović, Gaurav Singh, Bart Baesens, Wilfried Lemahieu, Jochen De Weerdt Proceedings - 2017 International Conference on Data Science and Advanced Analytics, DSAA 2017, 2017
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Summarizing citation contexts of scientific publications
Sandra Mitrović, Henning M{\"u}ller Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015
Preprint Paper Read more
Multi-Agent Systems for Software Development: a Multi-Faceted Research Question-driven Reference Guide
Sandra Mitrović, Vincenzo Giuffrida, Fabio Barth, Alba Bonet-Jover, Lidia López, Shaibal Barua, Santiago Massé, Estela Saquete, Aitana Delgado, Mobyen Uddin Ahmed, Matteo Salani, et al. SSRN
Machine Learning Operations Research