Yiran Chen | Scholars@Duke

Yiran Chen
Professor in the Department of Electrical and Computer Engineering

Yiran Chen received B.S. (1998) and M.S. (2001) from Tsinghua University and Ph.D. (2005) from Purdue University. After five years in the industry, he joined the University of Pittsburgh in 2010 as Assistant Professor and was promoted to Associate Professor with tenure in 2014, holding Bicentennial Alumni Faculty Fellow. He is now the John Cocke Distinguished Professor of Electrical and Computer Engineering at Duke University and serving as the director of the NSF AI Institute for Edge Computing Leveraging the Next-generation Networks (Athena), the NSF Industry-University Cooperative Research Center (IUCRC) for Alternative Sustainable and Intelligent Computing (ASIC), and the co-director of Duke Center for Computational Evolutionary Intelligence (DCEI). His group focuses on the research of new memory and storage systems, machine learning and neuromorphic computing, and mobile computing systems. Dr. Chen has published 1 book and about 600 technical publications and has been granted 96 US patents. He has served as the associate editor of more than a dozen international academic periodicals and served on the technical and organization committees of about 70 international conferences. He is now serving as the Editor-in-Chief of the IEEE Circuits and Systems Magazine. He received 9 best paper awards, 1 best poster award, and 15 best paper nominations from international conferences and workshops. He received numerous awards for his technical contributions and professional services such as the IEEE CASS Charles A. Desoer Technical Achievement Award, the IEEE Computer Society Edward J. McCluskey Technical Achievement Award, etc. He has been the distinguished lecturer of IEEE CEDA and CAS. He is a Fellow of the AAAS, ACM, and IEEE, and now serves as the chair of ACM SIGDA.

Current Research Interests

Emerging memory and storage technologies

Embedded systems, CPS, edge computing, and mobile applications

Neuromorphic computing, deep learning and system security

Low power circuit and system

Office Hours

^{Appointment only.}

Current Appointments & Affiliations

Professor in the Department of Electrical and Computer Engineering, Electrical and Computer Engineering, Pratt School of Engineering 2019
Professor of Computer Science, Computer Science, Trinity College of Arts & Sciences 2019

Contact Information

130 Hudson Hall, PO Box 90291, Durham, NC 27708
405 Wilkison Building, 534 Research Dr., Durham, NC 27705
yiran.chen@duke.edu (919) 660-1372
Duke Center of Computational Evolutionary Intelligence (CEI)
Google Scholar Page
NSF AI Institute for Edge Computing Leveraging Next Generation Networks (Athena)
NSF IUCRC for Alternative Sustainable and Intelligent Computing (ASIC)

Background
Education, Training, & Certifications
- Ph.D., Purdue University 2005
Previous Appointments & Affiliations
- Associate Professor in the Department of Electrical and Computer Engineering, Electrical and Computer Engineering, Pratt School of Engineering 2017 - 2019
- Associate Professor of Computer Science, Computer Science, Trinity College of Arts & Sciences 2018 - 2019
- Adjunct Associate Professor in the Department of Electrical and Computer Engineering, Electrical and Computer Engineering, Pratt School of Engineering 2016
Leadership & Clinical Positions at Duke
- Director of NSF AI Institute for Edge Computing Leveraging Next Generation Networks (Athena)
  Director of NSF IUCRC for Alternative Sustainable and Intelligent Computing (ASIC)
  Co-director of Duke Center for Computational Evolutionary Intelligence (CEI)
Recognition
In the News
- MAY 4, 2023 Duke Today
  
  Duke Awards 44 Distinguished Professorships
- JAN 31, 2023 Duke Today
  
  Three Duke Faculty Elected AAAS Fellows
- JUL 29, 2021
  
  NSF Launches Artificial Intelligence Research Center at Duke
- JAN 3, 2017
  
  Yiran Chen: Integrating Tomorrows Technology into Todays Devices
Awards & Honors
Research
Selected Grants
- AI Institute: Athena: AI-Driven Next-generation Networks at the Edge awarded by National Science Foundation 2021 - 2026
- Collaborative Research: SHF: Medium: Revitalizing EDA from a Machine Learning Perspective awarded by National Science Foundation 2021 - 2025
- Collaborative Research: CCRI:NEW: Research Infrastructure for Real-Time Computer Vision and Decision Making via Mobile Robots awarded by National Science Foundation 2021 - 2024
- FET: Small:RESONANCE:Accelerating Speech/Language Processing through Collective Training using Commodity ReRAM Chips awarded by National Science Foundation 2019 - 2023
- Operating at the intersection of Out-of-distribution detection and adversarial machine learning awarded by Air Force Research Laboratory 2021 - 2023
- Distributed Heterogenous Data Analytics via Federated Learning awarded by National Science Foundation 2021 - 2023
- Collaborative Research: Two-dimensional Synaptic Array for Advanced Hardware Acceleration of Deep Neural Networks awarded by National Science Foundation 2020 - 2023
- IUCRC Proposal Phase 1 Duke: Center for Alternative Sustainable and Intelligent Computing (ASIC) awarded by National Science Foundation 2018 - 2023
- Acceleration for Adversarial Machine Learning (AML) awarded by Army Research Office 2019 - 2023
- Collaborative Workshop Proposal: Redefining the Future of Computer Architecture from First Principles awarded by National Science Foundation 2022 - 2023
- RTML: Large: Collaborative: Harmonizing Predictive Algorithms and Mixed Signal/Precision Circuits via Computation-Data Access Exchange and Adaptive Dataflows awarded by National Science Foundation 2019 - 2022
- SPX: Collaborative Research: Ula! - An Integrated DNN Acceleration Framework with Enhanced Unsupervised Learning Capability awarded by National Science Foundation 2017 - 2022
- A Collaborative Machine Learning Approach to Fast and High-Fidelity Design Prediction awarded by The University of Texas at Dallas 2019 - 2021
- Workshop Proposal: Processing-In-Memory (PIM) Technology - Grand Challenges and Killer Applications awarded by National Science Foundation 2020 - 2021
- Exploring Vulnerability & Robustness of Deep Learning Systems awarded by Air Force Research Laboratory 2018 - 2021
- CCRI: Planning: Collaborative Research: Low-Power Computer Vision Platform awarded by National Science Foundation 2019 - 2020
- CSR: Small: Collaborative Research: EUReCa: Enabling Untethered VR/AR System via Human-centric Graphic Computing and Distributed Data Processing awarded by National Science Foundation 2017 - 2020
- SMALE: Enhancing Scalability of Machine Learning Algorithms on Extreme Scale Computing Platforms awarded by Department of Energy 2017 - 2020
- SHF:Small: Cross-Platform Solutions for Pruning and Accelerating Neural Models awarded by National Science Foundation 2017 - 2019
- NeoNexus: The Next-generation Information Processing System across Digital and Neuromorphic Computing Domains awarded by National Science Foundation 2017 - 2018
- Planning IUCRC Duke University: Center for Alternative Sustainable and Intelligent Computing awarded by National Science Foundation 2017 - 2018
- "CAREER: Centaur: A Bio-inspired Ultra Low Power Hybrid Embedded Computing Engine Beyond One TeraFlops/Watts" awarded by National Science Foundation 2017 - 2018
- The Design of Neuromorphic Controller System Built with Memristor Crossbars awarded by University of Pittsburgh 2017
External Relationships
- A*STAR Singapore
- AI Chip Center for Emerging Smart Systems (ACCESS)
- American University in Cairo
- City University of Hong Kong
- FELLOWS FUND, LLC
- Institute of Electrical and Electronics Engineers
- International Conference on Neuromorphic Computing
- Khalifa University
- National Science Foundation
- NeoNexus Group
- Northeastern University
- Research Grants Council of Hong Kong
- Texas A&M University at Qatar
- The Hong Kong Polytechnic University
- The University of Hong Kong
- University of Florida
- University of Kansas
Publications & Artistic Works
Selected Publications
- Books
  - Fang, L., Y. Chen, G. Zhai, J. Wang, R. Wang, and W. Dong. Preface. Vol. 13069 LNAI, 2021.
  - Fang, L., Y. Chen, G. Zhai, J. Wang, R. Wang, and W. Dong. Preface. Vol. 13070 LNAI, 2021.
  - Sangvai, Devdutta G., and Anthony J. Viera. Preface. Vol. 46, 2019. https://doi.org/10.1016/j.pop.2019.09.001.
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  - Li, H., and Y. Chen. Nonvolatile memory design: Magnetic, resistive, and phase change, 2017. https://doi.org/10.1201/b11354.
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- Academic Articles
  - Hanson, E., S. Li, X. Qian, H. H. Li, and Y. Chen. “DyNNamic: Dynamically Reshaping, High Data-Reuse Accelerator for Compact DNNs.” Ieee Transactions on Computers 72, no. 3 (March 1, 2023): 880–92. https://doi.org/10.1109/TC.2022.3184272.
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  - Lyu, Bo, Shiping Wen, Yin Yang, Xiaojun Chang, Junwei Sun, Yiran Chen, and Tingwen Huang. “Designing Efficient Bit-Level Sparsity-Tolerant Memristive Networks.” Ieee Transactions on Neural Networks and Learning Systems PP (March 2023). https://doi.org/10.1109/tnnls.2023.3250437.
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  - Pang, Meng, Binghui Wang, Mang Ye, Yiu-Ming Cheung, Yiran Chen, and Bihan Wen. “DisP+V: A Unified Framework for Disentangling Prototype and Variation From Single Sample per Person.” Ieee Transactions on Neural Networks and Learning Systems 34, no. 2 (February 2023): 867–81. https://doi.org/10.1109/tnnls.2021.3103194.
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  - Hu, S., Y. Chen, Q. Zhu, and A. W. Colombo. “Guest Editorial Machine Learning for Resilient Industrial Cyber-Physical Systems.” Ieee Transactions on Automation Science and Engineering 20, no. 1 (January 1, 2023): 3–4. https://doi.org/10.1109/TASE.2022.3223583.
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  - Li, Z., Q. Zheng, Y. Chen, and H. Li. “SpikeSen: Low-latency In-sensor-intelligence Design with Neuromorphic Spiking Neurons.” Ieee Transactions on Circuits and Systems Ii: Express Briefs, January 1, 2023. https://doi.org/10.1109/TCSII.2023.3235888.
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  - Wu, C., X. Yang, Y. Chen, and M. Li. “Photonic Bayesian Neural Network Using Programmed Optical Noises.” Ieee Journal of Selected Topics in Quantum Electronics 29, no. 2 (January 1, 2023). https://doi.org/10.1109/JSTQE.2022.3217819.
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  - Liu, F., W. Zhao, Z. Wang, Y. Zhao, T. Yang, Y. Chen, and L. Jiang. “IVQ: In-Memory Acceleration of DNN Inference Exploiting Varied Quantization.” Ieee Transactions on Computer Aided Design of Integrated Circuits and Systems 41, no. 12 (December 1, 2022): 5313–26. https://doi.org/10.1109/TCAD.2022.3156017.
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  - Zheng, Q., X. Li, Y. Guan, Z. Wang, Y. Cai, Y. Chen, G. Sun, and R. Huang. “PIMulator-NN: An Event-Driven, Cross-Level Simulation Framework for Processing-In-Memory-Based Neural Network Accelerators.” Ieee Transactions on Computer Aided Design of Integrated Circuits and Systems 41, no. 12 (December 1, 2022): 5464–75. https://doi.org/10.1109/TCAD.2022.3160947.
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  - Li, T., N. Jing, J. Jiang, Q. Wang, Z. Mao, and Y. Chen. “A Novel Architecture Design for Output Significance Aligned Flow with Adaptive Control in ReRAM-based Neural Network Accelerator.” Acm Transactions on Design Automation of Electronic Systems 27, no. 6 (November 22, 2022). https://doi.org/10.1145/3510819.
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  - Chen, Y., and Q. Qiu. “Guest Editorial: IEEE TC Special Issue on Software, Hardware and Applications for Neuromorphic Computing.” Ieee Transactions on Computers 71, no. 11 (November 1, 2022): 2705–6. https://doi.org/10.1109/TC.2022.3208389.
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  - Xie, Z., R. Liang, X. Xu, J. Hu, C. C. Chang, J. Pan, and Y. Chen. “Preplacement Net Length and Timing Estimation by Customized Graph Neural Network.” Ieee Transactions on Computer Aided Design of Integrated Circuits and Systems 41, no. 11 (November 1, 2022): 4667–80. https://doi.org/10.1109/TCAD.2022.3149977.
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  - Wang, C., D. Feng, W. Tong, J. Liu, B. Wu, and Y. Chen. “Space-Time-Efficient Modeling of Large-Scale 3-D Cross-Point Memory Arrays by Operation Adaption and Network Compaction.” Ieee Transactions on Computer Aided Design of Integrated Circuits and Systems 41, no. 10 (October 1, 2022): 3479–91. https://doi.org/10.1109/TCAD.2021.3123591.
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  - Li, T., N. Jing, Z. Mao, and Y. Chen. “A Hybrid-Grained Remapping Defense Scheme Against Hard Failures for Row-Column-NVM.” Ieee Transactions on Computer Aided Design of Integrated Circuits and Systems 41, no. 6 (June 1, 2022): 1842–54. https://doi.org/10.1109/TCAD.2021.3097288.
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  - Taylor, B., Q. Zheng, Z. Li, S. Li, and Y. Chen. “Processing-in-Memory Technology for Machine Learning: From Basic to ASIC.” Ieee Transactions on Circuits and Systems Ii: Express Briefs 69, no. 6 (June 1, 2022): 2598–2603. https://doi.org/10.1109/TCSII.2022.3168404.
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  - Mao, J., Q. Yang, A. Li, K. W. Nixon, H. Li, and Y. Chen. “Toward Efficient and Adaptive Design of Video Detection System with Deep Neural Networks.” Acm Transactions on Embedded Computing Systems 21, no. 3 (May 1, 2022). https://doi.org/10.1145/3484946.
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  - Yang, X., B. Taylor, A. Wu, Y. Chen, and L. O. Chua. “Research Progress on Memristor: From Synapses to Computing Systems.” Ieee Transactions on Circuits and Systems I: Regular Papers 69, no. 5 (May 1, 2022): 1845–57. https://doi.org/10.1109/TCSI.2022.3159153.
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  - Chen, Y., and Y. Wang. “A survey of architectures of neural network accelerators.” Scientia Sinica Informationis 52, no. 4 (April 1, 2022): 596–611. https://doi.org/10.1360/SSI-2021-0409.
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  - Inkawhich, N., J. Zhang, E. K. Davis, R. Luley, and Y. Chen. “Improving Out-of-Distribution Detection by Learning from the Deployment Environment.” Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15 (January 1, 2022): 2070–86. https://doi.org/10.1109/JSTARS.2022.3146362.
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  - Wu, Changming, Xiaoxuan Yang, Heshan Yu, Ruoming Peng, Ichiro Takeuchi, Yiran Chen, and Mo Li. “Harnessing optoelectronic noises in a photonic generative network.” Science Advances 8, no. 3 (January 2022): eabm2956. https://doi.org/10.1126/sciadv.abm2956.
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  - Huang, T., Y. Chen, Z. Zeng, and L. Chua. “Editorial Special Issue for 50th Birthday of Memristor Theory and Application of Neuromorphic Computing Based on Memristor - Part II.” Ieee Transactions on Circuits and Systems I: Regular Papers 68, no. 12 (December 1, 2021): 4835–36. https://doi.org/10.1109/TCSI.2021.3124407.
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  - Huang, T., Y. Chen, Z. Zeng, and L. Chua. “Editorial Special Issue for 50th Birthday of Memristor Theory and Application of Neuromorphic Computing Based on Memristor - Part i.” Ieee Transactions on Circuits and Systems I: Regular Papers 68, no. 11 (November 1, 2021): 4417–18. https://doi.org/10.1109/TCSI.2021.3115842.
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  - Wen, S., W. Liu, Y. Yang, P. Zhou, Z. Guo, Z. Yan, Y. Chen, and T. Huang. “Multilabel Image Classification via Feature/Label Co-Projection.” Ieee Transactions on Systems, Man, and Cybernetics: Systems 51, no. 11 (November 1, 2021): 7250–59. https://doi.org/10.1109/TSMC.2020.2967071.
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  - Chen, Y., Q. Qiu, and Y. Lin. “Introduction to the Special Issue on Hardware and Algorithms for Efficient Machine Learning-Part 2.” Acm Journal on Emerging Technologies in Computing Systems 17, no. 4 (October 1, 2021). https://doi.org/10.1145/3464917.
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  - Mao, J., H. Yang, A. Li, H. Li, and Y. Chen. “TPrune: Efficient Transformer Pruning for Mobile Devices.” Acm Transactions on Cyber Physical Systems 5, no. 3 (July 1, 2021). https://doi.org/10.1145/3446640.
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  - Chai, X., X. Zhi, Z. Gan, Y. Zhang, Y. Chen, and J. Fu. “Combining improved genetic algorithm and matrix semi-tensor product (STP) in color image encryption.” Signal Processing 183 (June 1, 2021). https://doi.org/10.1016/j.sigpro.2021.108041.
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  - Wen, S., M. Dong, Y. Yang, P. Zhou, T. Huang, and Y. Chen. “End-to-End Detection-Segmentation System for Face Labeling.” Ieee Transactions on Emerging Topics in Computational Intelligence 5, no. 3 (June 1, 2021): 457–67. https://doi.org/10.1109/TETCI.2019.2947319.
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  - Chai, X., H. Wu, Z. Gan, D. Han, Y. Zhang, and Y. Chen. “An efficient approach for encrypting double color images into a visually meaningful cipher image using 2D compressive sensing.” Information Sciences 556 (May 1, 2021): 305–40. https://doi.org/10.1016/j.ins.2020.10.007.
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  - Rao, J., Z. Fan, L. Hong, S. Cheng, Q. Huang, J. Zhao, X. Xiang, et al. “An electroforming-free, analog interface-type memristor based on a SrFeOx epitaxial heterojunction for neuromorphic computing.” Materials Today Physics 18 (May 1, 2021). https://doi.org/10.1016/j.mtphys.2021.100392.
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  - Chen, Y., Q. Qiu, and Y. Lin. “Introduction of Special Issue on Hardware and Algorithms for Efficient Machine LearningΓÇôPart 1.” Acm Journal on Emerging Technologies in Computing Systems 17, no. 2 (April 5, 2021). https://doi.org/10.1145/3449045.
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  - Wang, C., D. Feng, W. Tong, J. Liu, B. Wu, W. Zhao, Y. Zhang, and Y. Chen. “Improving Write Performance on Cross-Point RRAM Arrays by Leveraging Multidimensional Non-Uniformity of Cell Effective Voltage.” Ieee Transactions on Computers 70, no. 4 (April 1, 2021): 566–80. https://doi.org/10.1109/TC.2020.2990884.
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  - Wang, C., D. Feng, W. Tong, Y. Hua, J. Liu, B. Wu, W. Zhao, et al. “Improving Multilevel Writes on Vertical 3-D Cross-Point Resistive Memory.” Ieee Transactions on Computer Aided Design of Integrated Circuits and Systems 40, no. 4 (April 1, 2021): 762–75. https://doi.org/10.1109/TCAD.2020.3006188.
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  - Sun, Bo, Yuting Cao, Zhenyuan Guo, Zheng Yan, Shiping Wen, Tingwen Huang, and Yiran Chen. “Sliding Mode Stabilization of Memristive Neural Networks With Leakage Delays and Control Disturbance.” Ieee Transactions on Neural Networks and Learning Systems 32, no. 3 (March 2021): 1254–63. https://doi.org/10.1109/tnnls.2020.2984000.
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  - Wen, S., H. Wei, Y. Yang, Z. Guo, Z. Zeng, T. Huang, and Y. Chen. “Memristive LSTM Network for Sentiment Analysis.” Ieee Transactions on Systems, Man, and Cybernetics: Systems 51, no. 3 (March 1, 2021): 1794–1804. https://doi.org/10.1109/TSMC.2019.2906098.
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  - Liang, F., Z. Tian, M. Dong, S. Cheng, L. Sun, H. Li, Y. Chen, and G. Zhang. “Efficient neural network using pointwise convolution kernels with linear phase constraint.” Neurocomputing 423 (January 29, 2021): 572–79. https://doi.org/10.1016/j.neucom.2020.10.067.
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  - Chen, Y. “2021: The Greatest Reset [From the Editor].” Ieee Circuits and Systems Magazine 21, no. 1 (January 1, 2021): 4. https://doi.org/10.1109/MCAS.2020.3046386.
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  - Inkawhich, N. A., E. K. Davis, M. J. Inkawhich, U. K. Majumder, and Y. Chen. “Training SAR-ATR Models for Reliable Operation in Open-World Environments.” Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14 (January 1, 2021): 3954–66. https://doi.org/10.1109/JSTARS.2021.3068944.
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  - Inkawhich, N., M. J. Inkawhich, E. K. Davis, U. K. Majumder, E. Tripp, C. Capraro, and Y. Chen. “Bridging a Gap in SAR-ATR: Training on Fully Synthetic and Testing on Measured Data.” Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14 (January 1, 2021): 2942–55. https://doi.org/10.1109/JSTARS.2021.3059991.
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  - Liu, X., M. Mao, X. Bi, H. Li, and Y. Chen. “Exploring Applications of STT-RAM in GPU Architectures.” Ieee Transactions on Circuits and Systems I: Regular Papers 68, no. 1 (January 1, 2021): 238–49. https://doi.org/10.1109/TCSI.2020.3031895.
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  - Pang, M., B. Wang, Y. M. Cheung, Y. Chen, and B. Wen. “VD-GAN: A Unified Framework for Joint Prototype and Representation Learning from Contaminated Single Sample per Person.” Ieee Transactions on Information Forensics and Security 16 (January 1, 2021): 2246–59. https://doi.org/10.1109/TIFS.2021.3050055.
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  - Zhang, Oliver, Cheng Ding, Tania Pereira, Ran Xiao, Kais Gadhoumi, Karl Meisel, Randall J. Lee, Yiran Chen, and Xiao Hu. “Explainability Metrics of Deep Convolutional Networks for Photoplethysmography Quality Assessment.” Ieee Access : Practical Innovations, Open Solutions 9 (January 2021): 29736–45. https://doi.org/10.1109/access.2021.3054613.
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  - Lan, Y., K. W. Nixon, Q. Guo, G. Zhang, Y. Xu, H. Li, and Y. Chen. “FCDM: A Methodology Based on Sensor Pattern Noise Fingerprinting for Fast Confidence Detection to Adversarial Attacks.” Ieee Transactions on Computer Aided Design of Integrated Circuits and Systems 39, no. 12 (December 1, 2020): 4791–4804. https://doi.org/10.1109/TCAD.2020.2969982.
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  - Chai, X., J. Bi, Z. Gan, X. Liu, Y. Zhang, and Y. Chen. “Color image compression and encryption scheme based on compressive sensing and double random encryption strategy.” Signal Processing 176 (November 1, 2020). https://doi.org/10.1016/j.sigpro.2020.107684.
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  - Wang, S., Y. Cao, S. Wen, Z. Guo, T. Huang, and Y. Chen. “Projective Synchroniztion of Neural Networks via Continuous/Periodic Event-Based Sampling Algorithms.” Ieee Transactions on Network Science and Engineering 7, no. 4 (October 1, 2020): 2746–54. https://doi.org/10.1109/TNSE.2020.2985409.
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  - Yang, C., B. Liu, H. Li, Y. Chen, M. Barnell, Q. Wu, W. Wen, and J. Rajendran. “Thwarting Replication Attack against Memristor-Based Neuromorphic Computing System.” Ieee Transactions on Computer Aided Design of Integrated Circuits and Systems 39, no. 10 (October 1, 2020): 2192–2205. https://doi.org/10.1109/TCAD.2019.2937817.
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  - Zhu, J., G. Sun, X. Zhang, C. Zhang, W. Zhang, Y. Liang, T. Wang, Y. Chen, and J. Di. “Fork Path: Batching ORAM Requests to Remove Redundant Memory Accesses.” Ieee Transactions on Computer Aided Design of Integrated Circuits and Systems 39, no. 10 (October 1, 2020): 2279–92. https://doi.org/10.1109/TCAD.2019.2948914.
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  - Feng, D., J. Xu, Y. Hua, W. Tong, J. Liu, C. Li, and Y. Chen. “A Low-Overhead Encoding Scheme to Extend the Lifetime of Nonvolatile Memories.” Ieee Transactions on Computer Aided Design of Integrated Circuits and Systems 39, no. 10 (October 1, 2020): 2516–29. https://doi.org/10.1109/TCAD.2019.2962127.
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  - Chen, L., Z. He, C. Li, S. Wen, and Y. Chen. “Revisiting memristor properties.” International Journal of Bifurcation and Chaos 30, no. 12 (September 30, 2020). https://doi.org/10.1142/S0218127420501722.
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  - Gan, Z., X. Chai, J. Zhang, Y. Zhang, and Y. Chen. “An effective image compression–encryption scheme based on compressive sensing (CS) and game of life (GOL).” Neural Computing and Applications 32, no. 17 (September 1, 2020): 14113–41. https://doi.org/10.1007/s00521-020-04808-8.
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  - Chen, Y., D. Fan, Y. Wang, and S. Yamashita. “Editorial for the special issue on disruptive computing technologies.” Ccf Transactions on High Performance Computing 2, no. 3 (September 1, 2020): 209–10. https://doi.org/10.1007/s42514-020-00048-3.
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  - Xie, X., S. Wen, Z. Yan, T. Huang, and Y. Chen. “Designing pulse-coupled neural networks with spike-synchronization-dependent plasticity rule: image segmentation and memristor circuit application.” Neural Computing and Applications 32, no. 17 (September 1, 2020): 13441–52. https://doi.org/10.1007/s00521-020-04752-7.
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  - Guo, Q., J. Ye, Y. Chen, Y. Hu, Y. Lan, G. Zhang, and X. Li. “INOR—An Intelligent noise reduction method to defend against adversarial audio examples.” Neurocomputing 401 (August 11, 2020): 160–72. https://doi.org/10.1016/j.neucom.2020.02.110.
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  - Yan, Zheng, Jiadong Chen, Rui Hu, Tingwen Huang, Yiran Chen, and Shiping Wen. “Training memristor-based multilayer neuromorphic networks with SGD, momentum and adaptive learning rates.” Neural Networks : The Official Journal of the International Neural Network Society 128 (August 2020): 142–49. https://doi.org/10.1016/j.neunet.2020.04.025.
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  - Wen, S., H. Wei, Z. Yan, Z. Guo, Y. Yang, T. Huang, and Y. Chen. “Memristor-Based Design of Sparse Compact Convolutional Neural Network.” Ieee Transactions on Network Science and Engineering 7, no. 3 (July 1, 2020): 1431–40. https://doi.org/10.1109/TNSE.2019.2934357.
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  - Chai, X., H. Wu, Z. Gan, Y. Zhang, and Y. Chen. “Hiding cipher-images generated by 2-D compressive sensing with a multi-embedding strategy.” Signal Processing 171 (June 1, 2020). https://doi.org/10.1016/j.sigpro.2020.107525.
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  - Chai, X., X. Zheng, Z. Gan, and Y. Chen. “Exploiting plaintext-related mechanism for secure color image encryption.” Neural Computing and Applications 32, no. 12 (June 1, 2020): 8065–88. https://doi.org/10.1007/s00521-019-04312-8.
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  - Chai, X., X. Fu, Z. Gan, Y. Zhang, Y. Lu, and Y. Chen. “An efficient chaos-based image compression and encryption scheme using block compressive sensing and elementary cellular automata.” Neural Computing and Applications 32, no. 9 (May 1, 2020): 4961–88. https://doi.org/10.1007/s00521-018-3913-3.
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  - Wang, S., Y. Cao, T. Huang, Y. Chen, and S. Wen. “Event-triggered distributed control for synchronization of multiple memristive neural networks under cyber-physical attacks.” Information Sciences 518 (May 1, 2020): 361–75. https://doi.org/10.1016/j.ins.2020.01.022.
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  - Jia, X., J. Yang, P. Dai, R. Liu, Y. Chen, and W. Zhao. “SPINBIS: Spintronics-based Bayesian inference system with stochastic computing.” Ieee Transactions on Computer Aided Design of Integrated Circuits and Systems 39, no. 4 (April 1, 2020): 789–802. https://doi.org/10.1109/TCAD.2019.2897631.
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  - Zhang, G., B. Li, J. Wu, R. Wang, Y. Lan, L. Sun, S. Lei, H. Li, and Y. Chen. “A low-cost and high-speed hardware implementation of spiking neural network.” Neurocomputing 382 (March 21, 2020): 106–15. https://doi.org/10.1016/j.neucom.2019.11.045.
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  - Sun, B., S. Wen, S. Wang, T. Huang, Y. Chen, and P. Li. “Quantized synchronization of memristive neural networks with time-varying delays via super-twisting algorithm.” Neurocomputing 380 (March 7, 2020): 133–40. https://doi.org/10.1016/j.neucom.2019.11.003.
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  - Chen, Y., Y. Xie, L. Song, F. Chen, and T. Tang. “A Survey of Accelerator Architectures for Deep Neural Networks.” Engineering 6, no. 3 (March 1, 2020): 264–74. https://doi.org/10.1016/j.eng.2020.01.007.
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