Congratulations to the CISE Best Student Paper Award Winners

The Center for Information of Systems and Engineering is delighted to announce the winners of the 2021 CISE Best Student Paper Award. The CISE Best Student Paper Award Competition is an annual event established to promote student research and to recognize the scientific quality and scope of research being conducted by CISE students. This year’s event drew 20 submissions of excellent quality showcasing the strength and diversity of research pursued by CISE students and faculty. We are grateful for the support of the paper review team, which included 16 CISE faculty affiliates from the College of Engineering and the College of Arts & Sciences. Based on these reviews, we are awarding two Best Paper Awards, and recognize three papers as Finalists.

[Background Image: Andy Di/Adobe Stock]

First Place (tie)

Sheila Seidel, PhD Candidate, ECE. (Advisor: Vivek Goyal). “Two-Dimensional Non-Line-of-Sight Scene Estimation from a Single Edge Occluder.” IEEE Transactions on Computational Imaging, vol. 7, pp. 58-72, 2021, doi: 10.1109/TCI.2020.3037405.

Ali Siahkamari, PhD Candidate, ECE. (Advisor, Brian Kulis). “Piecewise Linear Regression via a Difference of Convex Functions.” Proceedings of the 37th International Conference on Machine Learning. PMLR 119:8895-8904, 2020 119:8895-8904, 2020.


Beliz Kaleli, PhD Candidate, ECE. (Advisors: Gianluca Stringhini, Manuel Egele). “To Err.Is Human: Characterizing the Threat of Unintended URLs in Social Media.” Network and Distributed System Security Symposium (NDSS) 2021. Session 3A-4.

James Queeney, PhD Candidate, SE. (Advisors: Yannis Paschalidis, Christos Cassandras) “Uncertainty-Aware Policy Optimization: A Robust, Adaptive Trust Region Approach.” Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21) 5930.

Artin Spiridonoff, PhD Candidate, SE. (Advisors: Yannis Paschalidis, Alex Olshevsky)  “Robust Asynchronous Stochastic Gradient-Push: Asymptotically Optimal and Network-Independent Performance for Strongly Convex Functions.” Journal of Machine Learning Research  JMLR. 21(58):1−47, 2020.