Publications

  • Sohan Salahuddin Mugdho, Yuanbo Guo, Ethan Rogers, Weiwei Zhao, Yiyu Shi and Cheng Wang, "FairXbar: Improving the Fairness of Deep Neural Networks with Non-Ideal In-Memory Computing Hardware", IEEE/ACM Design Automation and Test Europe (DATE) 2025.
  • Khan, Raufur Rahman, Ohik Kwon, Avishek Das, Jacob S. Eisbrenner, Cheng Wang, Meng Lu, and Liang Dong. "Low-Voltage Gallium Oxide Memristor with Enhanced Cyclic Endurance, Stability, and Memory Window." ACS Applied Electronic Materials (2025).
  • Ethan G Rogers, Sohan Salahuddin Mugdho, Kshemal Kshemendra Gupte, and Cheng Wang, "StoX-Net: Stochastic Processing of Partial Sums for Efficient In-Memory Computing DNN Accelerators", 2024 IEEE International Conference on Rebooting Computing (ICRC), San Diego, CA, USA, 2024 (Best Student Presentation).
  • Kshemal K. Gupte, Sohan S. Mugdho and Cheng Wang, "Scalable Spintronic Synapses for Analog In-Memory Computing Based on Exchange-Coupled Nanostructures", 2024 IEEE International Conference on Rebooting Computing (ICRC), San Diego, CA, USA, 2024 (Best Paper Award).
  • Kaushik Roy, Cheng Wang, Sourjya Roy, Anand Raghunathan, Kezhou Yang, and Abhronil Sengupta. "Spintronic neural systems." Nature Reviews Electrical Engineering (2024): 1-16.
  • Dong Eun Kim, Aayush Ankit, Cheng Wang, and Kaushik Roy, “SAMBA: Sparsity Aware In-Memory Computing Based Machine Learning Accelerator”, IEEE Trans. Computer (2023).
  • Cheng Wang, "Enabling efficient machine learning with device-to-algorithm co-design of spintronic hardware: opportunities and challenges", SPIE Spintronics (2023).
  • Haensch, Wilfried, Anand Raghunathan, Kaushik Roy, Bhaswar Chakrabart, Charudatta M. Phatak, Cheng Wang, and Supratik Guha."A Co-design view of Compute in-Memory with Non-Volatile Elements for Neural Networks",Advanced Materials (2023).
  • Gobinda Saha, Cheng Wang, and Kaushik Roy, "Invited: A Cross-layer Approach to Cognitive Computing", IEEE/ACM Design Automation Conference (2022).
  • Kang He, Indranil Chakraborty, Cheng Wang, and Kaushik Roy, "Design Space and Memory Technology Co-exploration for In-Memory Computing Based Machine Learning Accelerators", IEEE/ACM International Conference on Computer-Aided Design (2022).
  • Cheng Wang, Chankyu Lee, and Kaushik Roy, “Noise resilient leaky integrate-fire neurons based on multi-domain spintronic devices”, Scientific Reports 12 (1), 1-11 (2022).
  • Bing Han, Cheng Wang, and Kaushik Roy, “Oscillatory-Fourier Neural Network: A Compact and Efficient Architecture for Sequential Processing”, Conference on Artificial Intelligence (AAAI 2022)
  • Tanvi Sharma, Cheng Wang, Amogh Agrawal, and Kaushik Roy, “Enabling Robust SOT-MTJ Crossbars for Machine Learning using Sparsity-Aware Device-Circuit Co-design”. 2021 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED).
  • Hussam Amrouch, Jian-Jia Chen, Kaushik Roy, Yuan Xie, Mikail Yayla, Indranil Chakraborty, Cheng Wang, Fengbin Tu, Wenqin Huangfu, and Ling Liang, “Brain-Inspired Computing: Adventure from Beyond CMOS Technologies to Beyond von Neumann Architectures”, IEEE/ACM International Conference on Computer-Aided Design (ICCAD) 2021.
  • Amogh Agrawal, Cheng Wang, Tanvi Sharma, and Kaushik Roy, “Magnetoresistive Circuits and Systems: Embedded Non-Volatile Memory to Crossbar Arrays”, IEEE Transactions on Circuits and Systems I. 68, 6 (2021) Selected as Highlight of 2021 June Issue.
  • Cheng Wang, Amogh Agrawal, Eunseon Yu, and Kaushik Roy, “Multi-Level Neuromorphic Devices Built on Emerging Ferroic Materials: A Review”, Frontiers in Neurosciences 15: 661667 (2021).
  • Morgan Williamson, Cheng Wang, Pin-Wei Huang, Ganping Ju, and Maxim Tsoi, “Large and Local Magnetoresistance in a State-of-the-Art Perpendicular Magnetic Medium”, Nanotechnology, Science and Applications 14, 1-6 (2021).
  • Cheng Wang, Pin-Wei Huang, Ganping Ju, and Kuo-Hsing Hwang, “Exchange Coupled Composites” (for memristive synapses), US Patent Application 16/255,698 (2019).

Before 2016

  • H. Seinige, M. Williamson, S. Shen, Cheng Wang, G. Cao, J.-S. Zhou, J. B. Goodenough, and M. Tsoi, “Electrically Tunable Transport and High-Frequency Dynamics in Antiferromagnetic Sr3Ir2O7”, Physical Review B 94(21) 214434 (2016).
  • H. Seinige, Cheng Wang, and M. Tsoi, “Current-Driven Non-Linear Magnetodynamics in Exchange Biased Spin Valves”, Journal of Applied Physics 117, 17C507 (2015).
  • Cheng Wang, H. Seinige, G. Cao, J.-S. Zhou, J. B. Goodenough, and M. Tsoi, “Electrically Tunable Transport in the Antiferromagnetic Mott Insulator Sr2IrO4”, Physical Review B 92 (11), 115136 (2015)
  • Cheng Wang, H. Seinige, G. Cao, J.-S. Zhou, J. B. Goodenough, and M. Tsoi, “Temperature Dependence Of Anisotropic Magnetoresistance in Antiferromagnetic Sr2IrO4”, J. Appl. Phys. 117, 17A310 (2015).
  • Cheng Wang, H. Seinige, G. Cao, J.-S. Zhou, J. B. Goodenough, and M. Tsoi, “Anisotropic Magnetoresistance In Antiferromagnetic Sr2IrO4”, Physical Review X 4, 041034 (2014).
  • H. Seinige, Cheng Wang, and M. Tsoi, “Ferromagnetic Resonance: Electrical Detection Vs Conventional Measurements”, J. Appl. Phys. 115, 17D116 (2014).
  • Cheng Wang, H. Seinige, and M. Tsoi, “Current-Driven Parametric Resonance in Magnetic Multilayers”, Journal of Physics D: Applied Physics 46 285001 (2013).
  • Cheng Wang, H. Seinige, and M. Tsoi, “Ferromagnetic Resonance Driven by an Ac Current: A Brief Review”, Low Temperature Physics 39, 247 (2013)
  • H. Seinige, Cheng Wang, and M. Tsoi, “Ferromagnetic Resonance Detection by A Point-Contact Bolometer”, SPIE Nano Science+ Engineering, 88131K (2013).
  • Cheng Wang and K. Xia, “Ballistic Current Induced Effective Force on Magnetic Domain Wall”, Nano-Micro Letters1, 34 (2009).