All Publications

(2023). Adversarial Machine Learning: A New Threat Paradigm for Next-generation Wireless Communications. AI, Machine Learning and Deep Learning.
(2022). The Methodological Pitfall of Dataset-Driven Research on Deep Learning: An IoT Example. MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM).
(2022). Maximizing Energy Efficiency With Channel Uncertainty Under Mutual Interference. IEEE Transactions on Wireless Communications.
(2022). URSABench: A System for Comprehensive Benchmarking of Bayesian Deep Neural Network Models and Inference Methods. Proceedings of Machine Learning and Systems.
(2022). EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks. Proceedings of the ACM Web Conference 2022.
(2022). Impact of Parameter Sparsity on Stochastic Gradient MCMC Methods for Bayesian Deep Learning. arXiv:2202.03770 [cs].
(2021). Robust Decision-Making in the Internet of Battlefield Things Using Bayesian Neural Networks. 2021 Winter Simulation Conference (WSC).
(2021). Task Offloading with Uncertain Processing Cycles. Proceedings of the Twenty-second International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing.