ARISE: A Multi-Task Weak Supervision Framework for Network Measurements

Leveraging recent machine learning innovations in weak supervision and multi-task learning for network traffic classification.

Peer-reviewed and accepted for publication in IEEE JSAC 2022, published in July 2022. The paper is available at https://ieeexplore.ieee.org/document/9791308 and the source code is available at https://gitlab.com/onrg/arise.

This research was supported by the National Science Foundation through grants CNS 1850297, CNS 2145813, and OAC 2126281, as well as a University of Oregon VPRI fellowship and Ripple Undergraduate Scholarship.

Citation:
J. Knofczynski, R. Durairajan and W. Willinger, “ARISE: A Multi-Task Weak Supervision Framework for Network Measurements,” in IEEE Journal on Selected Areas in Communications, 2022, doi: 10.1109/JSAC.2022.3180783.

Combating Covid on College Campuses, altREU.

A computational modeling simulation of airborne pathogen transmission in academic spaces demonstrating the importance of ventilation and social distancing in scholastic settings. Research conducted as part of the Summer 2020 altREU program at Portland State University. This research was conducted in collaboration with myself, Oregon Health & Science University faculty, and three other undergraduate across the U.S.

The final report from this program is available on the Portland State University Library Archive, available here.

Citation:
J. Knofczynski, A. Killebrew Bruehl, B. Warner, and R. Shelton, “Combating COVID on College Campuses: The Impact of Structural Changes on Viral Transmissions,” Portland State University Teuscher Labs, August 2020.