Gergely Ács

Gergely Ács is an Associate Professor at Budapest University of Technology and Economics (BME), affiliated with the CrySyS Lab. He holds a PhD and MSc in Computer Science from BME, and previously served as a post-doctoral researcher and research engineer at INRIA's Privatics Team in France. His research focuses on data privacy, security, and machine learning applications in these domains. He has contributed to federated learning frameworks, privacy-preserving techniques for healthcare and IoT, and secure aggregation methods. Dr. Ács teaches courses on privacy technologies and security in machine learning at BME. He has received the Pollák-Virág Award and authored over 50 publications in top-tier conferences/journals. His work spans industries, including drug discovery collaborations and automotive cybersecurity.

• Education:
  • PhD in Computer Science, BME (2009)
  • MSc in Computer Science, BME (2005)
• Research Interests: Federated Learning, Differential Privacy, IoT Security, Machine Learning Security, Privacy-Preserving Technologies.
• Key Projects: MELLODDY (cross-pharma federated learning), SIMBIoTA-ML (IoT malware detection), Privacy-Preserving Smart Metering.