Welcome to Lei Yang's Homepage
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Associate Professor Department of Computer Science and Engineering University of Nevada, Reno Reno, NV 89557 Office: WPEB 427 Phone: (775) 682-6872 Email: leiy@unr.edu |
News
Our paper Communication-efficient training workload balancing for decentralized multi-agent learning has been accepted by IEEE ICDCS 2024.
Our paper ZeRO: Extremely efficient collective communication for giant model training has been accepted by ICLR 2024.
Our paper Feature collusion attack on PMU data-driven event classification has been accepted by IEEE PES ISGT 2024.
Our paper TopoCommit: A topological commit protocol for cross-ledger transactions in scientific computing has been accepted by IEEE Cluster 2023.
Our paper Towards distributed learning of PMU data: A federated learning based event classification approach has been accepted by IEEE PES General Meeting 2023.
Our paper Many-to-many matching based task allocation for dispersed computing has been accepted by Computing.
Congradulations to Amirhesam Yazdi, who successfully passed his PhD defense (11/30/2022) and is going to join the Information Systems department at UNR as Teaching Associate Professor!
Congradulations to Heyang Qin, who successfully passed his PhD defense (11/7/2022) and is going to join Microsoft Research as Researcher!
Our paper Toward efficient homomorphic encryption for outsourced databases through parallel caching has been accepted by ACM SIGMOD 2023.
Our paper Nemo: An open-sourced transformer-supercharged benchmark for fine-grained wildfire smoke detection has been accepted by Remote Sensing. The first labeled wildfire smoke dataset that includes bounding box to highlight the size and location of the smoke.
Congradulations to Yunchuan Liu, who successfully passed his PhD defense (6/23/2022) and is going to join Governors State University as a tenure-track Assistant Professor!
Our paper Weakly supervised event classification using imperfect real-world PMU data with scarce labels has been selected as one of the Best Conference Papers by IEEE PES General Meeting 2022.
Our paper Robust event classification using imperfect real-world PMU data has been accepted by IEEE Internet of Things Journal.
Our paper Affective computing model with impulse control in internet of things based on affective robotics has been accepted by IEEE Internet of Things Journal.
Our paper Data imputation for multivariate time series sensor data with large gaps of missing data has been accepted by IEEE Sensors Journal.
Our paper Weakly supervised event classification using imperfect real-world PMU data with scarce labels has been accepted by IEEE PES General Meeting 2022.
Our paper Real-time event detection using rank signatures of real-world PMU data has been accepted by IEEE PES General Meeting 2022.
Our paper DCCA enhanced forced oscillation frequency detection using real-world PMU data has been accepted by TPEC 2022.
Our paper Topological modeling and parallelization of multidimensional data on microelectrode arrays has been accepted by IPDPS 2022.
Our paper SimiGrad: Fine-grained adaptive batching for large scale training using gradient similarity measurement has been accepted by NeurIPS 2021 (Acceptance rate: 2371/9122=26%).
Our paper The age of correlated features in supervised learning based forecasting has been accepted by IEEE INFOCOM Age of Information Workshop 2021.
Our paper Collusion-resistant worker recruitment in crowdsourcing systems has been accepted by IEEE Transactions on Mobile Computing.
Our paper ULPT: A user-centric location privacy trading framework for mobile crowd sensing has been accepted by IEEE Transactions on Mobile Computing.
Our paper Privacy-preserving data aggregation for mobile crowdsensing with externality: An auction approach has been accepted by IEEE/ACM Transactions on Networking.
Our paper CoEdge: Cooperative DNN inference with adaptive workload partitioning over heterogeneous edge devices has been accepted by IEEE/ACM Transactions on Networking.
Our paper A regularized tensor completion approach for PMU data recovery has been accepted by IEEE Transactions on Smart Grid.
Our papers PMU-data-driven event classification in power transmission grids and Low-rank tensor completion for PMU data recovery have been accepted by IEEE PES ISGT NA 2021.
Our paper Seasonal self-evolving neural networks based short-term wind farm generation forecast has been accepted by IEEE SmartGridComm 2020.
Our paper SEFEE: Lightweight storage error forecasting in large scale enterprise storage systems has been accepted by SC20 (68/380=18%).
Our paper Blockchain for future smart grid: A comprehensive survey has been accepted by IEEE Internet of Things Journal.
Congradulations to Amir Ghasemkhani, who has accepted a tenure-track Assistant Professor position in the School of Computer Science and Engineering at California State University, San Bernardino!
Our project “REU Site: Cross-disciplinary Research Experience for Undergraduates on Big Data Analytics in Smart Cities” is funded by NSF! REU Application
Wireless Communications and Mobile Computing Special Issue on “Recent Advances in Cloud-Aware Mobile Fog Computing 2020,” Submission Deadline: April 24, 2020
Our paper Reinforcement Learning Empowered MLaaS Scheduling for Serving Intelligent Internet of Things has been accepted by IEEE Internet of Things Journal.
Our paper Deepgrid: Robust deep reinforcement learning-based contingency management has been accepted by IEEE ISGT 2020.
Our paper Intelligent edge: Leveraging deep imitation learning for mobile edge computation offloading has been accepted by IEEE Wireless Communications.
Congradulations to Amir Ghasemkhani for successfully defending his dissertation today (11/25/2019)!
IEEE Internet of Things Journal Special Issue on “Artificial Intelligence Powered Edge Computing for Internet of Things,” Submission Deadline: December 15, 2019
Our paper Privacy-preserving database assisted spectrum access for industrial Internet of things: A distributed learning approach has been accepted by IEEE Transactions on Industrial Electronics.
Our project “A Robust Event Diagnostics Platform: Integrating Tensor Analytics and Machine Learning Into Real-time Grid Monitoring” is funded by DOE!
Our paper Swift Deep Learning Serving Scheduling: A Region Based Reinforcement Learning Approach has been accepted by SC19 (78/344=22%).
Our paper Modeling Error Learning based Post-Processor Framework for Hydrologic Models Accuracy Improvement has been accepted by the journal Geoscientific Model Development (GMD).
Our paper Learning-based demand response for privacy-preserving users has been accepted by IEEE Transactions on Industrial Informatics.
Our paper Dynamic pricing for privacy-preserving mobile crowdsensing: A reinforcement learning approach has been accepted by IEEE Network Magazine.
Our paper Node state monitoring scheme in fog radio access networks for intrusion detection has been accepted by IEEE Access.
Our project “BIGDATA: IA: Collaborative Research: Protecting Yourself from Wildfire Smoke: Big Data Driven Adaptive Air Quality Prediction Methodologies” is funded by NSF!
New NSF RET Site Grant “RET Site: Cross-disciplinary Research Experiences on Smart Cities for Nevada Teachers: Integrating Big Data into Robotics”! This NSF grant emphasizes on research experiences for Nevada Teachers in the fields of Robotics and Big Data.
Our paper on privacy-preserving data aggregation for crowdsensing has been accepted by MobiHoc’18 (30/178=16.9%).
Our paper on novel user authentication for smartwatches has been accepted by ASIACCS’18 (62/310=20.0%).
Our paper on privacy-preserving auction for crowdsensing has been accepted by CNS’18.
Our paper on wireless service pricing competition has been accepted by IEEE Transactions on Vehicular Technology.
Our research on investigating improved wind forecasting to harness clean energy potential was published as the TOP story in today's (01/08/2018) edition of the National Science Foundation Science360 News. The original and full story was published on the Solar Nexusproject website and also posted on the UNR's Nevada Today.
Openings
RA positions available. I am currently looking for highly self-motivated Ph.D. students who are strongly committed to research. If you are interested, please send your resume or CV, transcripts, TOEFL and GRE scores, and everything else that you believe will help your application to me in one email.
Information about admission can be found on the department website (http://www.unr.edu/degrees/computer-science-and-engineering/phd).
Due to the large volume of application emails, I may not be able to respond every email. I usually review them in a batch and will contact you if I decide to move forward with you to the next stage.
If you want a prioritized consideration and my email response, you can pick one (or a few) paper(s) from my recent publications and write a paper review (summary, your thoughts of the paper, especially weakness, what can be improved, potential follow up directions, etc.).
About Me
I am currently an Associate Professor in the Department of Computer Science and Engineering at the University of Nevada, Reno. Previously, I was an Assistant Research Professor at School of Electrical, Computer and Energy Engineering of Arizona State University, and a Postdoctoral Scholar at ASU working with Professor Junshan Zhang and Professor Vijay Vittal and at Princeton University working with Professor Vincent Poor. I received my Ph.D. degree in Electrical Engineering from Arizona State University in Fall 2012 under the supervision of Professor Junshan Zhang. Before that, I received both my B.S. and M.S. degrees in Electrical Engineering from Radio Engineering Department of Southeast University, Nanjing, China, in 2005 and 2008, respectively