Academic Profile : Faculty
Prof Tay Wee Peng
Associate Chair (Academic), School of Electrical & Electronic Engineering
Professor, School of Electrical & Electronic Engineering
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Dr Tay Wee Peng received the B.S. degree in Electrical Engineering and Mathematics, and the M.S. degree in Electrical Engineering from Stanford University, Stanford, CA, USA, in 2002. He received the Ph.D. degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology, Cambridge, MA, USA, in 2008. He is a Professor of Signal and Information Processing in the School of Electrical and Electronic Engineering at Nanyang Technological University, Singapore.
He was an Associate Editor for the IEEE Transactions on Signal Processing (2015 -- 2019) and an Editor for the IEEE Transactions on Wireless Communications (2017 -- 2023). He is currently an Associate Editor for the IEEE Transactions on Signal and Information Processing over Networks, an Associate Editor for the IEEE Internet of Things Journal, and a Subject Editor for Signal Processing, Elsevier. His research interests include signal and information processing over networks, distributed inference and estimation, statistical privacy, and robust machine learning.
He was an Associate Editor for the IEEE Transactions on Signal Processing (2015 -- 2019) and an Editor for the IEEE Transactions on Wireless Communications (2017 -- 2023). He is currently an Associate Editor for the IEEE Transactions on Signal and Information Processing over Networks, an Associate Editor for the IEEE Internet of Things Journal, and a Subject Editor for Signal Processing, Elsevier. His research interests include signal and information processing over networks, distributed inference and estimation, statistical privacy, and robust machine learning.
- Signal and Information Processing over Networks
- Statistical Privacy for Networks
- Inference and Learning
- Detection, Estimation and Optimization
- Statistical Privacy for Networks
- Inference and Learning
- Detection, Estimation and Optimization
- Generalized Message Passing for Federated Learning in Multi-Access Edge Computing
- Graph Signal Processing for High Dimensional Structures and Spaces
- Project Ananke 2 – Aerial-Ground Place Recognition for Drones
- Project LOCUS
- Topology-enhanced physical models for biopolymer structure and interaction analysis
- Trust, failure and trust recovery in financial exchanges: towards a culturally-intelligent, dynamic and sensing AI
US 2020/0146103 A1: Wireless Sensor Network And Parameter Optimization Method Thereof (2020)
Abstract: A wireless sensor network includes an aggregator, a control device, a bridge device, and a mesh module. The control device is connected with the aggregator and the bridge device. The mesh module is wirelessly connected with the bridge device and the control device. A mesh network is built by the connections of the mesh module, the bridge device, and the control device. A duty cycle of the mesh module is less than or substantially equal to 10 percent. A command sent by the aggregator is converted into a wireless message by the control device, the wireless message is transmitted by the control device and retransmitted through a first amount of radios and repeated for a second amount of times by the bridge device, so that the wireless message is successfully received by the mesh module. Therefore, a mesh network with high efficiency and low cost is achieved.
Abstract: A wireless sensor network includes an aggregator, a control device, a bridge device, and a mesh module. The control device is connected with the aggregator and the bridge device. The mesh module is wirelessly connected with the bridge device and the control device. A mesh network is built by the connections of the mesh module, the bridge device, and the control device. A duty cycle of the mesh module is less than or substantially equal to 10 percent. A command sent by the aggregator is converted into a wireless message by the control device, the wireless message is transmitted by the control device and retransmitted through a first amount of radios and repeated for a second amount of times by the bridge device, so that the wireless message is successfully received by the mesh module. Therefore, a mesh network with high efficiency and low cost is achieved.