The QuantumC3 research group from the Federal University of Rio Grande (FURG) participated in the 1st Brazilian Symposium on Quantum Computing and Communication (SBCCQ 2026), held as part of the XLVI Brazilian Computer Society Congress (CSBC 2026) in Gramado, Rio Grande do Sul, Brazil.
During the event, the team presented the poster "dc-qml: data-centric quantum machine learning," which introduces a methodology focused on data preparation, representation, and encoding for quantum machine learning applications. The proposed approach complements traditional model-centric methods by emphasizing the role of data quality in improving the performance of near-term quantum systems.
The poster also presented preliminary results in industrial anomaly detection, highlighting the potential of the dc-qml methodology to support the development of practical quantum machine learning applications.
Participation in SBCCQ 2026, as part of CSBC 2026, provided an opportunity to disseminate the group's ongoing research and to engage with researchers and students from institutions across Brazil working in quantum computing, quantum communication, and artificial intelligence.