Yang (Cindy) Yi
- Very Large Scale Integrated (VLSI) Circuits and Systems, High Performance Computing, Computer Aided Design (CAD), Artificial Intelligence, and Emerging Nano-device
- Neuromorphic Electronic Circuits Design and Automation for Brain-Inspired Computing System
- Three-dimensional Integrated Circuits Design and Analysis
- Artificial Intelligence, Machine Learning, and Cognitive Computing in Wireless Communications and Cybersecurity
- Integrated Circuit/Transceiver Design in Wireless/Cellular Networks, eHealth Systems, and Internet of Things
- Hardware Reliability and Variability Analysis in High Performance Computing Systems
- Interconnect Modeling and Simulation, Signal Integrity and Power Integrity
- Digital Design
- VLSI Design
- Advanced Analog Integrated Circuit Design
- IEEE Senior Member
- Miller Professional Development Award for Distinguished Research, 2016
- Best Paper Award, IEEE GLOBECOM, 2016
- United States Air Force (USAF) Faculty Fellowship, 2015, 2016
- National Science Foundation (NSF) EPSCoR First Award, 2015
- Miller Scholar Award, 2015
Publications in 2017:
- Google Scholar Profile
- List of entire publications
- S. Mosleh, L. Liu, C. Sahin, R. Zheng, and Y. Yi, "Brain-Inspired Wireless Communications: Where Reservoir Computing Meets MIMO-OFDM", IEEE Transactions on Neural Networks and Learning Systems (TNNLS) (2017).
- A. Ehsan, H. An, Z. Zhou, and Y. Yi, "A Novel Approach for using TSVs as Membrane Capacitance in Neuromorphic 3D IC", IEEE Transaction on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol: PP, issue: 99 (2017).
- K. Hamedani, L. Liu, R. Atat, J. Wu, and Y. Yi, " Reservoir Computing Meets Smart Grids: Attack Detection using Delayed Feedback Networks", IEEE Transactions on Industrial Informatics (TII) (2017).
- H. An, A. Ehsan, Z. Zhou, F. Shen, and Y. Yi, "Monolithic 3D Neuromorphic Computing System with Hybrid CMOS and Memristor-based Synapses and Neurons", Integration, the VLSI Journal - Elsevier (2017).
- C. Zhao, K. Hamedani, J. Li, and Y. Yi, "Analog Spike-timing-dependent Resistive Crossbar Design for Brain Inspired Computing", IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS) (2017).
- C. Zhao, Y. Yi, J. Li, and L. Liu, “Inter-Spike Intervals (ISI) based Analog Spike-Time- Dependent Encoder for Neuromorphic Processors,” IEEE Transactions on Very Large Scale Integration Systems (TVLSI) (2017).
- R. Atat, L. Liu, H. Chen, J. Wu, H. Li, and Y. Yi, “Enabling Cyber-Physical Communication in 5G Cellular Networks: Challenges, Spatial Spectrum Sensing, and Cyber-Security,” IET Cyber-Physical Systems: Theory & Applications, vol. 2, no. 1, pp. 49 – 54 (2017).
- H. An, J. Li, Y. Li, X. Fu, and Y. Yi, "Three Dimensional Memristor Based Neuromorphic Computing System and its Application to Cloud Robotics," Computers & Electrical Engineering an International Journal - Elsevier (2017).
- C. Xie, J. Tan, M. Chen, Y. Yi, L. Peng, X. Fu, “Emerging technology enabled energy-efficient GPGPUs register file,” Journal of Microprocessors and Microsystems - Elsevier, vol. 50, pp. 175-188 (2017).
- Y. Li, P. Fan, L. Liu, and Y. Yi, “Distributed MIMO Precoding for In-band Full-duplex Wireless Backhaul in Heterogeneous Networks,” IEEE Transactions on Vehicular Technology (TVT) (2017).
- A. Ehsan, H. An, Z. Zhou, and Y. Yi, “Adaptation of Enhanced TSV Capacitance as Membrane Property in 3D Brain-inspired Computing System,” in Proc. of IEEE/ACM Design Automation Conference (DAC) (2017).
- J. Li, R. Atat, L. Liu, and Y. Yi “Enabling Sustainable Cyber Physical Security Systems through Neuromorphic Computing,” IEEE Transactions on Sustainable Computing (T-SUSC) (2017).
- R. Atat, L. Liu, and Y. Yi, “Energy Harvesting-Based D2D-Assisted Machine-Type Communications,” IEEE Transactions on Communications (TCOM), vol. 65, no. 3, pp. 1289 – 1302 (2017).
- A. Ehsan, Z. Zhou, and Y, Yi, “Neuromorphic 3D Integrated Circuit: A Hybrid, Reliable and Energy Efficient Approach for Next Generation Computing,” in Proc. of ACM Great Lakes Symposium on VLSI, Best Paper Award Finalist (2017).
- H. An, M. Ehsan, Z. Zhou, and Y. Yi, "Electrical Modeling and Analysis of 3D Synaptic Array using Vertical RRAM Structure,” in Pro. of IEEE International Symposium on Quality Electronic Design (ISQED), Best Paper Award Finalist (2017).
- J. Li, C. Zhao, and Y. Yi, “Energy Efficient and Compact AnalogIntegrated Circuit Design for Delay-dynamical Reservoir Computing System,” Special Session in Hardware in Reservoir Computing, IEEE International Joint Conference on Neural Networks (IJCNN) (2017).
- H. An, Z. Zhou, and Y, Yi, “Opportunities and Challenges on Nanoscale 3D Neuromorphic Computing System,” in Proceedings of IEEE International Symposium on Electromagnetic Compatibility (EMC) (2017).
- A. Ehsan, Z. Zhou, and Y, Yi, “Modeling and Analysis of Ion Transportation and Membrane Activities in 3D Neuromorphic Computing System,” in Proceedings of IEEE International Symposium on Electromagnetic Compatibility (EMC) (2017).
- C. Zhao, J. Li, and Y. Yi, "Energy efficient analog IC design for data compression in spiking neuromorphic systems," DAC Work-in-Progress Session (2017).
- C. Zhao, J. Li, and Y. Yi, “Analog Spiking Temporal Encoder with Inter-spike Intervals with Verification and Recovery Scheme for Neuromorphic Computing Systems,” in Proceedings of IEEE International Symposium on Quality Electronic Design (ISQED) (2017).
- A. Ehsan, Z. Zhou, and Y. Yi, “3D Integration Meets Neuromorphic Computing: A Novel Way to Reach a High Performance and Energy Efficient Computing System,” in Proceedings of IEEE International Symposium on VLSI Design, Automation and Test (VLSI-DAT) (2017).
- H. An, Z. Zhou, and Y. Yi, “Memristor-Based 3D Neuromorphic Computing System and Its Application to Associative Memory Learning,” in Proceedings of IEEE Nanotechnology Conference (2017).
- H. An, Z. Zhou, and Y. Yi, “3D Memristor-based Adjustable Deep Recurrent Neural Network with Programmable Attention Mechanism,” in Proceedings of Neuromorphic Computing Symposium (2017).
- C. Zhao, J. Li, H. An, and Y. Yi, “When Energy Efficient Spike-Based Temporal Encoding Meets Resistive Crossbar: From Circuit Design to Application,” in Proceedings of Neuromorphic Computing Symposium (2017).
- (540) 231-7561
302 Whittemore (0111)
Dept. of Electrical and Computer Engineering, Virginia Tech
Blacksburg, VA 24061
Office: 441 Whittemore Hall