معرفی
Roberto Corizzo is a faculty member at American University, where he teaches courses such as Introduction to Data Mining (CSC-480/680) and Intro to Computer Science II (CSC-208). His research spans machine learning, big data computing, and data mining, focusing on sensor data forecasting, time series classification, anomaly detection, and feature extraction for applications in energy, cybersecurity, astrophysics, and social networks.
- PhD in Computer Science (University of Bari, 2018)
- MSc and BSc in Computer Science (University of Bari, 2012 and 2010)
His research emphasizes continual learning, explainable AI, and handling imbalanced data. He has contributed to domains like gravitational wave detection, stock market prediction, and social bias mitigation in sentiment analysis. His recent publications focus on efficient neural architectures (TinySubNets), explainability in spatio-temporal modeling (pyCLAD), and multimodal approaches for misinformation detection.
Corizzo actively engages in academic service as an Editorial Board Member for Frontiers in Big Data and has organized workshops at conferences like KDD, ICLR, and ECML/PKDD. He has supervised students and research projects through the SPIRAL/SPATIAL REU (Ampere Project) and serves as a reviewer for journals including IEEE Transactions on Neural Networks and Machine Learning.
