Riccardo Guidotti (male), Assistant Professor at University of Pisa. Riccardo Guidotti was born in 1988 in Pitigliano (GR) Italy. In 2013 and 2010 he graduated cum laude in Computer Science (MS and BS) at University of Pisa. He received the PhD in Computer Science with a thesis on Personal Data Analytics in the same institution. He is currently an Assistant Professor at the Department of Computer Science University of Pisa, Italy and a member of the Knowledge Discovery and Data Mining Laboratory (KDDLab), a joint research group with the Information Science and Technology Institute of the National Research Council in Pisa. He won the IBM fellowship program and has been an intern in IBM Research Dublin, Ireland in 2015. He also won the DSAA New Generation Data Scientist Award 2018. His research interests are in explainable artificial intelligence and machine learning, personal data mining, clustering, and analysis of mobility and transactional data. More recently, he is interested in exploiting quantum mechanics phenomena to improve data mining and machine learning methods.
Relevant Publications
Guidotti, R., Monreale, A., Matwin, S., & Pedreschi, D. (2019, September). Black Box Explanation by Learning Image Exemplars in the Latent Feature Space. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases (pp. 189-205). Springer, Cham.
Guidotti, R., Monreale, A., Giannotti, F., Pedreschi, D., Ruggieri, S., & Turini, F. (2019). Factual and counterfactual explanations for black box decision making. IEEE Intelligent Systems, 34(6), 14-23.
Guidotti, R., Monreale, A., Ruggieri, S., Turini, F., Giannotti, F., & Pedreschi, D. (2018). A survey of methods for explaining black box models. ACM computing surveys (CSUR), 51(5), 1-42.
Guidotti, R., Rossetti, G., Pappalardo, L., Giannotti, F., & Pedreschi, D. (2018). Personalized market basket prediction with temporal annotated recurring sequences. IEEE Transactions on Knowledge and Data Engineering, 31(11), 2151-2163.
Trasarti, R., Guidotti, R., Monreale, A., & Giannotti, F. (2017). Myway: Location prediction via mobility profiling. Information Systems, 64, 350-367.
Teaching activities related to quantum computing and technologies
Teacher for the course “Data Mining Advanced Topics” in the Master Degree in Data Science and Business Informatics at the University of Pisa, year 2020/2021.
Co-Teacher for the course “Logic for Programming” in the Bachelor Degree in Computer Science at the University of Pisa, year 2019/2020.
Assistant Teacher for the course “Data Mining and Machine Learning” in the Master in Big Data Analytics & Social Mining at the University of Pisa, from 2016 to today.
Assistant Teacher for the course “Foundations of Data Mining” in the Master Degree in Data Science and Business Informatics at the University of Pisa, from 2016 to 2019.