Stratis Ioannidis


Recent Publications

Revisiting Hilbert-Schmidt Information Bottleneck for Adversarial Robustness, Z. Wang, T. Jian, A. Masoomi, S. Ioannidis, and J. Dy. NeurIPS, 2021. [code][talk]

Deep Spectral Ranking, İ. Yıldız, J. Dy, D. Erdoğmuş, S. Ostmo, J. P. Campbell, M. F. Chiang, and S. Ioannidis. AISTATS, 2021. [code][talk]

Submodular Maximization via Taylor Series Approximation, G. Özcan, A. Moharrer, and S. Ioannidis. SDM, 2021. [code][talk]

Graph Transfer Learning, A. Gritsenko, Y. Guo, K. Shayestehfard, A. Moharrer, J. Dy, and S. Ioannidis ICDM, 2021. [code][talk]

Cache Networks of Counting Queues, Y. Li and S. Ioannidis. ACM/IEEE ToN, 2021.

Research Interests

  • Machine Learning
  • Distributed Systems
  • Networking
  • Privacy

Technical Program Commitees

  • NeurIPS (2017-2021), ICML (2017-2021),
  • INFOCOM (2014-2021), ACM MobiHoc (2016–2021)


News and research highlights, google scholar profile, patents granted and pending. If you are interested in pursuing a Ph.D. in machine learning, distributed systems, or privacy, please feel free to reach out to ioannidis@ece.neu.edu.

Our research is generously supported by the National Science Foundation via the NSF AI Institute for Future Edge Networks and Distributed Intelligence (AI-EDGE), a CAREER award CCF-1750539 and grants CNS 2107062, CCF-1937500, IIS-1741197, IIS-1622536, NeTS-1718355, and CNS-1717213, by the Defence Advanced Research Projects Agency, as well as by a Google Faculty Research Award and a Facebook Research Award.