report by Lil Squid from the Noun Project. See:
  1. [TC’22]  Gokul Krishnan, Li Yang, Jingbo Sun, Jubin Hazra, Xiaocong Du, Maximilian Liehr, Zheng Li, Karsten beckmann, Rajiv V. Joshi, Nathaniel C. Cady, Deliang Fan and Yu Cao, “Exploring Model Stability of Deep Neural Networks for Reliable RRAM-based In-Memory Acceleration,” IEEE Transactions on Computers (TC), DOI: 10.1109/TC.2022.3174585, 2022 [pdf]
  2. [TPAMI’21]  Adnan Siraj Rakin, Zhezhi He, Jingtao Li, Fan Yao, Chaitali Chakrabarti and Deliang Fan, “T-BFA: Targeted Bit-Flip Adversarial Weight Attack,” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), DOI: 10.1109/TPAMI.2021.3112932 2021 [pdf]
  3. [IEEE-Micro’21]  Jian Meng, Wonbo Shim, Li Yang, Deliang Fan, Shimeng Yu, and Jae-sun Seo, “Temperature-Resilient RRAM-based In-Memory Computing for DNN Inference,”  IEEE Micro, Volume: 42, Issue: 1, Jan.-Feb. 1, DOI: 10.1109/MM.2021.3131114, 2022 [pdf]
  4. [SST’22]  Sai Kiran Cherupally, Jian Meng, Adnan Rakin, Shihui Yin, Injue Yeo, Shimeng Yu, Deliang Fan, and Jae-sun Seo, “Improving the Accuracy and Robustness of RRAM-based In-Memory Computing Against RRAM Hardware Noise and Adversarial Attacks,”  Semiconductor Science and Technology, Special Issue on Neuromorphic Devices and Applications, Vol. 37, no.3, 2022 [pdf]
  5. [IEEE-DT’21]  Sai Kiran Cherupally, Jian Meng, Adnan Rakin, Shihui Yin, Mingoo Seok, Deliang Fan and Jae-sun Seo, “Improving DNN Hardware Accuracy by In-Memory Computing Noise Injection,” IEEE Design & Test of Computers , DOI: 10.1109/MDAT.2021.3139047, 2021 [pdf]
  6. [TODAES’21]  Shaahin Angizi, Navid Khoshavi, Andrew Marshall, Peter Dowben, and Deliang Fan, “MeF-RAM: A New Non-Volatile Cache Memory Based on Magneto-Electric FET,” ACM Transactions on Automation of Electronic Systems (TODAES) , Volume 27, Issue 2, March 2022, [pdf]
  7. [IJMS’21]  Jiao Sun, Naima Ahmed Fahmi, Heba Nassereddeen, Irene Martinez, Sze Cheng, Deliang Fan, Jeongsik Yong, Wei Zhang, “Computational Methods to Study Transcript Variants in COVID-19,” International Journal of Molecular Sciences (IJMS), 2021, 22(18), 9684 [pdf]
  8. [TCAS-II’21]  Jian Meng, Li Yang, Xiaochen Peng, Shimeng Yu, Deliang Fan and Jae-Sun Seo, “Structured Pruning of RRAM Crossbars for Efficient In-Memory Computing Acceleration of Deep Neural Networks,” IEEE Transactions on Circuits and Systems- II (TCAS-II) Vol. 68, No. 5, May 2021 [pdf]
  9. [TCAS-I’21] Honglan Jiang, Shaahin Angizi, Deliang Fan, Jie Han and Leibo Liu, “Non-Volatile Approximate Arithmetic Circuits using Scalable Hybrid Spin-CMOS Majority Gates,” IEEE Transactions on Circuits and Systems – I (TCAS-I) vol. 68, issue 3, page 1217-1230, March 2021. DOI: 10.1109/TCSI.2020.3044728 [pdf]
  10. [IJMS’21]  Naima Ahmed Fahmi, Heba Nassereddeen, Jae Woong Chang, Meeyeon Park, Hsin Sung Yeh, Jiao Sun, Deliang Fan, Jeongsik Yong and Wei Zhang, “AS Quant: Detection and Visualization of Alternative Splicing Events with RNA seq Data,” International Journal of Molecular Sciences (IJMS) 2021, 22(9), 4468; [pdf]
  11. [TCAD’21]  Han Xu, Ziwei Li, Ziru Li, Deliang Fan, Fei Qiao, Qi Wei, Li Luo, Xinjun Liu and Huazhong Yang, “Reducing SRAM Reading Power With Column Data Segment and Weights Correlation Enhancement for CNN,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) DOI: 10.1109/TCAD.2020.3041380 [pdf]
  12. [JETC’21] Qutaiba Alasad, Jie Lin, Jiann-Shuin Yuan, Amro Awad, Deliang Fan, “Resilient and Secure Hardware Devices Using ASL,” ACM Journal on Emerging Technologies in Computing Systems, January 2021, article no. 11, [pdf]
  13. [TNNLS’21] Xiaolong Ma, Sheng Lin, Shaokai Ye, Zhezhi He, Linfeng Zhang, Geng Yuan, Sia Huat Tan, Zhenggang Li, Deliang Fan, Xuehai Qian, Xue Lin, Kaisheng Ma, and Yanzhi Wang, “Non-Structured DNN Weight Pruning – Is It Beneficial in Any Platform?,” IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021, DOI: 10.1109/TNNLS.2021.3063265 (accept) [pdf]
  14. [EDL’20] Durjoy Dev, Adithi Krishnaprasad, Mashiyat S. Shawkat, Zhezhi He, Sonali Das, Deliang Fan, Hee-Suk Chung, Yeonwoong Jung, and Tania Roy, “2D MoS2 Based Threshold Switching Memristor For Artificial Neuron,” IEEE Electron Device Letters (EDL), Vol. 41, issue 6, page 936-939, June 2020, DOI: 10.1109/LED.2020.2988247 [pdf]
  15. [TMAG’20] Shaahin Angizi, Zhezhi He, An Chen and Deliang Fan, “Hybrid Spin-CMOS Polymorphic Logic Gate with Application in In-Memory Computing,” IEEE Transactions on Magnetics (TMAG) , Volume: 56 , Issue: 2 , Feb. 2020, DOI: 10.1109/TMAG.2019.2955626 [pdf]
  16. [JETC’20] Zhezhi He, Li Yang, Shaahin Angizi, Adnan Siraj Rakin and Deliang Fan, “Sparse BD-Net: A Multiplication-Less DNN with Sparse Binarized Depth-wise Separable Convolution,” ACM Journal on Emerging Technologies in Computing Systems (JETC), January 2020 Article No.: 15 [pdf]
  17. [Bioinformatics’19] Zhibo Wang, Zhezhi He, Milan Shah, Teng Zhang, Deliang Fan and Wei Zhang, “Network-based multi-task learning models for biomarker selection and cancer outcome prediction,” Bioinformatics, Volume 36, Issue 6, 15 March 2020, Pages 1814–1822,, 05 November 2019 [pdf]
  18. [TC’19] Arman Roohi, Shadi Sheikhfaal, Shaahin Angizi, Deliang Fan, Ronald DeMara, “ApGAN: Approximate GAN for Robust Low Energy Learning from Imprecise Components,” IEEE Transactions on Computers, 23 October 2019, DOI: 10.1109/TC.2019.2949042 [pdf]
  19. [TCAD’19] Baogang Zhang, Necati Uysal, Deliang Fan, Rickard Ewetz, “Handling Stuck-at-fault Defects using Matrix Transformation for Robust Inference of DNNs,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 30 September 2019, DOI: 10.1109/TCAD.2019.2944582  [pdf]
  20. [TCAD’19] Shaahin Angizi, Zhezhi He, Amro Awad and Deliang Fan, “MRIMA: An MRAM-based In-Memory Accelerator,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 27 March 2019, DOI: 10.1109/TCAD.2019.2907886  [pdf]
  21. [JETC’18] Farhana Parveen, Shaahin Angizi and Deliang Fan, “IMFlexCom: Energy Efficient In-memory Flexible Computing using Dual-mode SOT-MRAM,” ACM Journal on Emgerging Technologies in Computing Systems, Vol.14, no.3, Oct. 2018 [pdf]
  22. [TNANO’18] Shaahin Angizi, Honglan Jiang, Ronald Demara, Jie Han and Deliang Fan, “Majority-Based Spin-CMOS Primitives for Approximate Computing,” IEEE Transactions on Nanotechnology, vol. 17, no. 4, July 2018 [pdf]
  23. [TMSCS’18] Zhezhi He, Yang Zhang, Shaahin Angizi, Boqing Gong and Deliang Fan, “Exploring A SOT-MRAM based In-Memory Computing for Data Processing,” IEEE Transactions on Multi-Scale Computing Systems, 2018 [pdf]
  24. [TMAG’18] Farhana Parveen, Shaahin Angizi, Zhezhi He and Deliang Fan, “IMCS2: Novel Device-to-Architecture Co-design for Low Power In-memory Computing Platform using Coterminous Spin-Switch,” IEEE Transactions on Magnetics, vol. 54, no.7, July 2018 [pdf]
  25. [TMAG’18] S. Pyle, D. Fan, R. DeMara, “Compact Spintronic Muller C-Element with Near-Zero Standby Energy,” IEEE Transactions on Magnetics, vol.54, no.2, Feb. 2018 [pdf] (Front Cover Paper)
  26. [TMSCS’17] Y. Bai, D. Fan and M. Lin, “Stochastic-Based Synapse and Soft-Limiting Neuron with Spintronic Devices for Low Power and Robust Artificial Neural Networks,” IEEE Transactions on Transactions on Multi-Scale Computing Systems, vol.4, no.3, pp.463-476, Dec. 2017 [pdf]
  27. [TCAD’17] S. Angizi, Z. He, N. Bagherzadeh and D. Fan, “Design and Evaluation of a Spintronic In-Memory Processing Platform for Non-Volatile Data Encryption,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol.37, no.9, Sept. 2018 [pdf]
  28. [MAGL’17] Z. He, S. Angizi, and D. Fan, “Current Induced Dynamics of Multiple Skyrmions with Domain Wall Pair and Skyrmion-based Majority gate Design,” IEEE Magnetics Letters, vol.8, March 30, 2017 [pdf]
  29. [TCAD’17] A. Roohi, R. Zand, D. Fan and R. DeMara, “Voltage-based Concatenatable Full Adder using Spin Hall Effect Switching,” IEEE Transactions on Computer Aided Design of Integrated Circuits and Systems, vol.36, no.12, Dec. 2017 [pdf]
  30. [JETC’17] K. Yogendra, C. Liyanagedera, D. Fan, Y. Shim and K. Roy, “Coupled Spin-Torque Nano-Oscillator based Computation: A Simulation Study,” ACM Journal on Emerging Technologies in Computing Systems, vol. 13, no.4, July 2017 [pdf]
  31. [TETC’17] Z. He and D. Fan, “Energy Efficient Reconfigurable Threshold Logic Circuit with Spintronic Devices,” IEEE Transactions on Emerging Topics in Computing, vol.5, no.2, May 2017 [pdf]
  32. [JETCAS’17] S. Salehi, D. Fan, R. DeMara, “Survey of STT-MRAM Cell Design Strategies: Taxonomy and Sense Amplifier Tradeoffs for Resiliency,” IEEE Journal on Emerging and Selected Topics in Circuits and Systems, Vol. 13, no. 3, May 2017 [pdf]
  33. [TNANO’17] R. Zand, A. Roohi, D. Fan and R. DeMara, “Energy-Efficient Nonvolatile Reconfigurable Logic using Spin Hall Effect-based Lookup Tables,” IEEE Transactions on Nanotechnology, vol. 16, no. 1, pp.32-43, Jan. 2017 [pdf]
  34. [TCAD’16] X. Fong, Y. Kim, K. Yogendra, D. Fan, A. Sengupta, and K. Roy, “Spin-Transfer Torque Devices: Prospects and Perspectives,” IEEE Transactions on Computer Aided Design of Integrated Circuits and Systems (TCAD), Vol. 25, no. 1, pp.1-22, Jan 2016, [pdf]
  35. [TED’16] K Yogendra, D. Fan, B. Jung and K. Roy, “Magnetic Pattern Recognition using Injection Locked Spin Torque Nano-Oscillators”, IEEE Transactions on Electron Devices, vol. 63, no. 4, pp.1674-1680, Feb. 2016 [pdf]
  36. [TNANO’15] D. Fan, S. Maji, K. Yogendra, M. Sharad and K. Roy, “Injection Locked, Spin Hall Induced Coupled-Oscillators for Energy Efficient Associative Computing,” IEEE Transaction on Nanotechnology (TNANO), Vol. 14, No. 6, Aug, 2015. DOI: 10.1109/TNANO.2015.2471092 [pdf]
  37. [TNNLS’15] D. Fan, M. Sharad, A. Sengupta and K. Roy, “Hierarchical Temporal Memory Based on Spin-Neurons and Resistive Memory for Energy-Efficient Brain-Inspired Computing,” IEEE Transaction on Neural Networks and Learning Systems (TNNLS), Vol.27, no.9, Sept. 2016. DOI: 10.1109/TNNLS.2015.2462731 [pdf]
  38. [JETCAS’15] K. Roy, D. Fan, X. Fong, Y. Kim, M. Sharad, S. Paul, S. Chatterjee, S. Bhunia, and S. Mukhopadhyay “Exploring Spin Transfer Torque Devices for Unconventional Computing”, IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS), Vol. 5, No. 1, March 2015. DOI: 10.1109/JETCAS.2015.2405171 [pdf]
  39. [TNANO’15] D. Fan, Y. Shim, A. Raghunathan and K. Roy, “STT-SNN: A Spin-Transfer-Torque Based Non-Linear Soft-Limiting Neuron for Low-Power Artificial Neural Networks,” IEEE Transactions on Nanotechnology (TNANO), June 2015. DOI: 10.1109/TNANO.2015.2437902 [pdf]
  40. [TMAG’15] K Yogendra, D. Fan and K. Roy, “Coupled Spin Torque Nano Oscillators for Low Power Neural Computation”, IEEE Transactions on Magnetics, Vol. 51, no. 10, June, 2015. DOI: 10.1109/TMAG.2015.2443042 [pdf]
  41. [TMAG’15] M. Sharad, D. Fan and K. Roy, “Energy-Efficient and Robust Associative Computing with Injection-Locked Dual Pillar Spin-Torque Oscillators”, IEEE Transactions on Magnetics, Vol. 51, No. 7, June 2015. DOI: 10.1109/TMAG.2015.2394379 [pdf]
  42. [TNANO’14] D. Fan, M. Sharad and K. Roy, “Design and Synthesis of Ultra Low Energy Spin-Memristor Threshold Logic,” IEEE Transaction on Nanotechnology (TNANO) Vol. 13, No. 3, May, 2014. DOI: 10.1109/TNANO.2014.2312177 [pdf]
  43. [TNANO’14] M. Sharad, D. Fan, and K. Roy, “Energy Efficient Non-Boolean Computing With Spin Neurons and Resistive Memory”, IEEE Transaction on Nanotechnology (TNANO), vol. 13, No.1, 2014. DOI: 10.1109/TNANO.2013.2286424 [pdf]
  44. [JAP’13] M. Sharad, D. Fan and K. Roy , “Spin Neurons: A Possible Path to Energy-Efficient Neuromorphic Computers”, Journal of Applied Physics (JAP), 114, 234906 (2013) [pdf]