Rate My Professor Yas Silva

Silva's research focuses on social media analysis, online misbehavior and cyberbullying detection, social computing, big data processing, similarity-aware data analysis, scalable database systems, and fairness and transparency in AI. He leads projects such as BullyBlocker for detecting cyberbullying on social networks like Instagram and Facebook, developing datasets and apps including ActionPoint; SimCloud for similarity grouping in big data systems; SimDB for similarity-aware databases; and DBSnap for visual database query construction. His grants as PI or co-PI include multiple NSF SaTC awards totaling over $1.2 million (e.g., $406,421 in 2022, $516,000 in 2021), Google Research $60,000 AIR award (2023), and co-PI on $3.8 million CyberCorps SFS (2024). Major honors comprise the 2025 Sujack Family Award for Faculty Research Excellence, Best Paper Awards at IEEE/ACM ASONAM 2022, CyberSafety 2020, and SISAP 2013, and Finalist for Arizona Innovator of the Year (2018). Select publications include "Xbully: Cyberbullying Detection within a Multi-Modal Context" (2019, 160 citations), "Hierarchical Attention Networks for Cyberbullying Detection on the Instagram Social Network" (2019, 134 citations), "SQL: From Traditional Databases to Big Data" (2016, 93 citations), "Analyzing Adversarial Strategies and Countermeasures for Cyberbullying Detection" (2025), and "SpectrumNet: Detecting LGBTQ+ Cyberbullying with Dynamic Context-Aware Attention" (2026). With 1,961 citations on Google Scholar, his work impacts social network analysis and database systems. Silva contributes extensively through technical program committees (e.g., IEEE BigData, SISAP), journal reviewing, and university service.