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.

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.

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.