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Yang (Cindy) Yi

Associate Professor
  • Associate Director of Multifunctional Integrated Circuits & Systems (MICS)
Yi
302 Whittemore (0111)
Dept. of Electrical and Computer Engineering, Virginia Tech
Blacksburg, VA 24061
USA

Office: 441 Whittemore Hall

http://www.yangyi.ece.vt.edu/

Research Interests:

  • Very Large Scale Integrated (VLSI) Circuits and Systems, High Performance Computing, Computer Aided Design (CAD), Artificial Intelligence, and Emerging Nano-device

Research Topics:

  • 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

Teaching Interests:

  • Digital Design
  • VLSI Design
  • Advanced Analog Integrated Circuit Design

Recognition:

  • 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 2019:

  • Google Scholar Profile
  • List of entire publications
  • H. Chang, H. Song, Y. Yi, J. Zhang, H. He, and L. Liu ‘‘Distributive Dynamic Spectrum Access Through Deep Reinforcement Learning: A Reservoir Computing-Based Approach,’’ IEEE Internet of Things Journal, vol. 6, no. 2, pp. 1983-1948, April 2019.
  •  H. Chen, L. Liu, H. S. Dhillon, and Y. Yi, ‘‘QoS-Aware D2D Cellular Networks with Spatial Spectrum Sensing: A Stochastic Geometry View,’’ IEEE Transactions on Communications, vol. 67, issue 5, pp. 3651-3664, May 2019.
  • H. An, Q. An, and Y. Yi, ‘‘Realizing Behavior Level Associative Memory Learning Through Three-Dimensional Memristor-Based Neuromorphic Circuits,’’ IEEE Transactions on Emerging Topics in Computational Intelligence, Early Access, Jul. 2019.
  •  R. Atat, L. Liu, J. Wu, J. Ashdown, and Y. Yi, ‘‘Green massive traffic offloading for cyber-physical systems over heterogeneous cellular networks,’’ Mobile Networks and Applications, vol. 24, issue 4, pp. 1364-1372, Aug. 2019.
  • C. Zhao, Q. An, K. Bai, B. Wysocki, C. Thiem, L. Liu, and Y. Yi, ‘‘Energy Efficient Temporal Spatial Information Processing Circuits Based on STDP and Spike Iteration,’’ IEEE Transactions on Circuits and Systems II: Express Briefs, Early Access, Oct. 2019.
  •  K. Bai, Q. An, L. Liu, and Y. Yi, ‘‘A Training-Efficient Hybrid-Structured Deep Neural Network With Reconfigurable Memristive Synapses,’’ IEEE Transactions on Very Large Scale Integration (VLSI) Systems            , Early Access, Oct. 2019.
  •  K. Hamedani, L. Liu, S. Hu, J. Ashdown, J. Wu, and Y. Yi, ‘‘Detecting Dynamic Attacks in Smart Grids Using Reservoir Computing: A Spiking Delayed Feedback Reservoir Based Approach,’’ IEEE Transactions on Emerging Topics in Computational Intelligence, Early Access, Oct. 2019.
  • M. Liu, L. Liu, H. Song, Y. Hu, Y. Yi, and F. Gong, ‘‘Signal Estimation in Underlay Cognitive Networks for Industrial Internet of Things,’’ IEEE Transactions on Industrial Informatics, Early Access, Nov. 2019.
  • H. Song, J. Bai, Y. Yi, J. Wu, L. Liu, “Artificial Intelligence Enabled Internet of Things: Network Architecture and Spectrum Access,” Accepted, IEEE Computational Intelligence Magazine (CIM), 2019.
  • Q. An, K. Bai, Y, Yi, “A Unified Information Perceptron using Deep Reservoir Computing
    Journal: Computers and Electrical Engineering,” Accepted, Computers & Electrical Engineering - Journal – Elsevier, 2019.
  • F. Shen, J. Roccosalvo, J. Zhang, Y. Yi, Y. Ji, K. Guo, A. M. Kok, and, Y. Han, “STEM Education Enrichment in NYC,” in 16th International Conference on Information Technology-New Generations (ITNG 2019), pp. 277-282, May 2019.
  • H. Song, L. Liu, H. Chang, J. Ashdown, Y. Yi, “Deep Q-Network Based Power Allocation Meets Reservoir Computing in Distributed Dynamic Spectrum Access Networks,” in IEEE INFOCOM 2019-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) pp. 774-779, April 2019,.
  • K. Bai, Q.  An, Y. Yi, “Deep-DFR: A Memristive Deep Delayed Feedback Reservoir Computing System with Hybrid Neural Network Topology,” in DAC '19 Proceedings of the 56th Annual Design Automation Conference 2019, June 2019.
  • C. Zhao, L. Liu, Y. Yi, “Design and Analysis of Real Time Spiking Neural Network Decoder for Neuromorphic Chips,” in ICONS '19 Proceedings of the International Conference on Neuromorphic Systems, Jul. 2019.
  • K. Bai, S. Liu, Y. Yi, “High speed and energy efficient deep neural network for edge computing,” in SEC '19 Proceedings of the 4th ACM/IEEE Symposium on Edge Computing, pp. 347-349, Nov. 2019.
  • K. Hamedani, S. Liu, Y. Yi, “Deep Spiking Delayed Feedback Reservoirs and Its Application in Spectrum Sensing of MIMO-OFDM Dynamic Spectrum Sharing,” Accepted, Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20) 
  • Z. Zhou, L. Liu, J. Zhang, J. Ashdown, Y. Yi, “Deep Reservoir Computing Meets 5G MIMO-OFDM Systems in Symbol Detection,” Accepted, Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20) 
  • S. Liu, V. Gan, Y, Liang, Y. Yi, “Accurate and Efficient Quantized Reservoir Computing System,” Accepted, 2020 21th International Symposium on Quality Electronic Design (ISQED).
  • H. Song, L. Liu, H. Chang, J. Ashdown, Y. Yi, “Maximizing System Throughput in D2D Networks using Alternative DC Programming,” Accepted, IEEE Global Communications Conference (GLOBECOM), 2019.
  • H. An, K. Bai, and Y. Yi, “The roadmap to realize memristive three-dimensional neuromorphic computing system,” in Advances in MemristorNeural Networks-Modeling and Applications. London, U.K.: IntechOpen, 2019.
  • K. Bai and Y. Yi, "Opening the “Black Box” of Silicon Chip Design in Neuromorphic Computing," in Bio-Inspired Technology: IntechOpen, 2019.