Yanning Shen
Assistant Professor
Department of EECS
Department of CS (Joint appointment, WoS)
University of California, Irvine
Email: yannings@uci.edu
My research interests span the areas of machine learning, network science, data science, optimization, and statistical signal processing; along with their applications in social, brain, gene-regulatory, environmental, financial, and IoT systems.
I am looking for self-motivated undergrad and grad students. For students at UCI, please contact me and include your research interest, CV, transcripts, as well as writing samples (if any) in your email. For prospective graduate students, please apply to UCI ECE or Network Systems and mention my name in your application.
Selected Awards (See Awards tab for the full list)
2023 UCI CORCL Research Award
2023 UCI Newkirk Faculty Fellow
2022 MIT Technology Review Innovators under 35 Asia Pacific
2022-2023 Hellman Fellowship Award
2022 Google Research Scholar Award
2022 UCI CORCL Research Award
2021 Microsoft Academic Grant Award for AI Research
2020 Academic Senate Council on Research, Computing, and Libraries (CORCL) Research Award
2018-2019 Doctoral Dissertation Fellowship, UMN
2017 Rising Stars in EECS
News
02/2024 New paper on fairness-aware Graph Generative Model "FairWire: Fair Graph Generation" O. D. Kose, Y. Shen is available!
02/2024 Constanza joined the group as a visiting student from the Universitat Politècnica de Catalunya, Barcelona Tech. Welcome!
01/2024 Our paper "Budgeted Online Model Selection and Fine-Tuning via Federated Learning," P. M. Ghari, and Y. Shen has been accepted by the Transactions on Machine Learning Research. Congratulations to Pouya!
01/2024 Our new preprint "Long-term Fairness For Real-time Decision Making: A Constrained Online Optimization Approach" R. Du, D. Muthirayan, P. P Khargonekar, Y. Shen is available. Congratulations to Ruijie for the new work.
01/2024 Our paper "Fairness-aware Optimal Graph Filter Design" O. D. Kose, G. Mateos, Y. Shen is accepted by the IEEE Journal of Selected Topics in Signal Processing. Congratulations to Deniz!
12/2023 Yanning gave a talk on "Demystifying and Mitigating Unfairness for Machine Learning over Graphs" at the ECE department of the University of Maryland, Colege Park.
11/2023 Yanning organized a special session on "Machine Learning over Graphs" in Asilomar 2023
10/2023 Ruijie finished his MS degree and is officially a PhD student! Congratulations to Ruijie!
09/2023 Erfan joined the group as an MS/PhD student. Welcome!
08/2023 New paper "Fairness-Aware Graph Filter Design" is accepted by Asilomar 2023
07/2023 Two papers were accepted at the 62nd IEEE Conference on Decision and Control (CDC).
06/2023 New collaborative paper "Analysis of Relative Error in Perturbation Monte Carlo Simulations of Radiative Transport" published in the Journal of Biomedical Optics.
05/2024 Yanning gave a talk on "Demystifying and Mitigating Unfairness for Machine Learning over Graphs" at the ECE Department at the University of Michigan, Ann Arbor.
05/2023 Our tutorial "Fairness in Graph Machine Learning: Recent Advances and Future Prospectives" is accepted by KDD 2023!
04/2023 New paper with Deniz "Fast&Fair: Training Acceleration and Bias Mitigation for GNNs" accepted by the Transactions on Machine Learning Research.
03/2023 Yanning receive the 2023 CORCL Research Award
Selected Publications (See Publications tab for the full list)
Summary: 30 published journal papers, 45 published conference papers, and 4 preprints. The underlined author is a UCI student I advise.
P.M. Ghari and Y. Shen, "Graph-Aided Online Multi-Kernel Learning," the Transactions on Machine Learning Research, 2024 (TMLR).
O. D. Kose, G. Mateos, Y. Shen, "Fairness-aware Optimal Graph Filter Design" the IEEE Journal of Selected Topics in Signal Processing. (JSTSP) 2024
P.M. Ghari and Y. Shen, "Graph-Aided Online Multi-Kernel Learning," Journal of Machine Learning Research (JMLR), 2023.
O. D. Kose and Y. Shen, "Fast&Fair: Training Acceleration and Bias Mitigation for GNNs," the Transactions on Machine Learning Research, 2023 (TMLR).
O. D. Kose and Y. Shen, "Demystifying and Mitigating Bias for Node Representation Learning," IEEE Transactions on Neural Networks and Learning Systems, 2023. (TNNLS)
P.M. Ghari and Y. Shen, "Online Learning with Uncertain Feedback Graphs," IEEE Transactions on Neural Networks and Learning Systems, 2023.
P. M. Ghari and Y. Shen, "Personalized Online Federated Multi-Kernel Learning", NeurIPS 2022
M. Li, S. Chen, Y. Shen, G. Liu, I. W. Tsang, Y. Zhang "Online Multi-Agent Forecasting with Interpretable Collaborative Graph Neural Network," IEEE Transactions on Neural Networks and Learning Systems, 2022.
P. M. Ghari, Y. Shen*, "Online Multi-Kernel Learning with Graph-Structured Feedback," ICML 2020.
Y. Shen, T. Chen, and G. B. Giannakis, "Random Feature-based Online Multi-kernel Learning in Non-stationary and Adversarial Environments," Journal of Machine Learning Research (JMLR), February 2019. [pdf]
G. B. Giannakis, Y. Shen, and G. V. Karanikolas, "Topology Identification and Learning over Graphs: Accounting for Nonlinearities and Dynamics," Proceedings of the IEEE, May 2018. [pdf]
Y. Shen, T. Chen and G. B. Giannakis, “Online Ensemble Multi-kernel Learning Adaptive to Non-stationary and Adversarial Environments,” AISTATS, 2018.
Q. Lu, G. V. Karanikolas, Y. Shen, and G. B. Giannakis, "Ensemble Gaussian Processes with Spectral Features for Online Interactive Learning with Scalability," AISTATS, 2020.
Y. Shen*, S. K.Bidhendi and H. Jafarkhani, “Distributed and Quantized Online Multiple Kernel Learning,” IEEE Transactions on Signal Processing, 2021.
Y. Shen, Geert Leus and G. B. Giannakis, “Online Graph-Adaptive Learning with Scalability and Privacy,” IEEE Transactions on Signal Processing, 2019.
Sponsors:
