JOURNAL PUBLICATIONS

1. [TMAG'19] 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), 2019 (accepted)
2. [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, 2019 (accepted)
3. [JETC'19] 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, 2019 (accepted)
4. [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 2019 (accepted)
5. [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, 2019 (accepted) 
6. [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, 2019 (accepted) [pdf]
7. [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]
8. [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]
9. [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]
10. [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]
11. [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)
12. [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]
13. [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]
14. [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]
15. [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]
16. [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]
17. [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]
18. [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]
19. [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]
20. [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]
21. [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]
22. [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]
23. [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]
24. [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]
25. [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]
26. [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]
27. [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]
28. [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]
29. [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]
30. [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) http://dx.doi.org/10.1063/1.4838096 [pdf]

CONFERENCE PUBLICATIONS

1. [AAAI'20] Li Yang, Zhezhi He and Deliang Fan, “Harmonious Coexistence of Structured Weight Pruning and Ternarization for Deep Neural Networks,” Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), Feb. 7-12 2020, New York, USA
2. [DATE'20] Shaahin Angizi, Jiao Sun, Wei Zhang and Deliang Fan, “PIM-Aligner: A Processing-in-MRAM Platform for Biological Sequence Alignment,” Design, Automation and Test in Europe (DATE), 09-13 March 2020, ALPEXPO, Grenoble, France
3. [ASPDAC'20] Li Yang, Shaahin Angizi, Deliang Fan, “A Flexible Processing-in-Memory Accelerator for Dynamic Channel-Adaptive Deep Neural Networks,” Asia and South Pacific Design Automation Conference (ASP-DAC), Jan. 13-16, 2020, Beijing, China 
4. [ASPDAC'20] Baogang Zhang, Necati Uysal, Deliang Fan, Rickard Ewetz, “Representable Matrices: Enabling High Accuracy Analog Computation for Inference of DNNs using Memristors,” Asia and South Pacific Design Automation Conference (ASP-DAC), Jan. 13-16, 2020, Beijing, China 
5. [ICCV'19] Adnan Siraj Rakin*, Zhezhi He*, Deliang Fan, “Bit-Flip Attack: Crushing Neural Network with Progressive Bit Search,” IEEE International Conference on Computer Vision, Seoul, Korea, Oct 27 - Nov 3, 2019 [pdf] (* The first two authors contributed equally)
6. [ICCAD'19] Shaahin Angizi and Deliang Fan, “ReDRAM: A Reconfigurable Processing-in-DRAM Platform for Accelerating Bulk Bit-Wise Operations,” IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 4-7 November 2019, Westminster, CO
7. [NANOARCH'19] Shaahin Angizi and Deliang Fan, “Deep Neural Network Acceleration in Non-Volatile Memory: A Digital Approach?,” IEEE/ACM International Symposium on Nanoscale Architectures, 17-19 July 2019, Qingdao, CHINA
8. [ISVLSI'19] Shaahin Angizi, Zhezhi He, Dayane Reis, Xiaobo Sharon Hu, Wilman Tsai, Shy Jay Lin and Deliang Fan, “Accelerating Deep Neural Networks in Processing-in-Memory Platforms: Analog or Digital Approach?,” IEEE Computer Society Annual Symposium on VLSI, 15 - 17 July 2019, Miami, Florida, USA (invited)
9. [ISVLSI'19] Adnan Siraj Rakin and Deliang Fan, “Defense-Net: Defend Against a Wide Range of Adversarial Attacks through Adversarial Detector,” IEEE Computer Society Annual Symposium on VLSI, 15 - 17 July 2019, Miami, Florida, USA
10. [Dagstuhl Report’19] Deliang Fan, “Cognitive Computing-in-Memory: Circuit to Algorithm,” Dagstuhl Seminar 19152, Emerging Hardware Techniques and EDA Methodologies for Neuromorphic Computing, Germany, 2019
11. [DRC'19] Durjoy Dev, Adithi Krishnaprasad, Zhezhi He, Sonali Das, Mashiyat Sumaiya Shawkat, Madison Manley, Olaleye Aina, Deliang Fan, Yeonwoong Jung and Tania Roy, “Artificial Neuron using Ag/2D-MoS2/Au Threshold Switching Memristor,” 77th Device Research Conference, 23 - 26 June 2019, University of Michigan, Ann Arbor
12. [CVOPS'19] Yifan Ding, Liqiang Wang, Huan Zhang, Jinfeng Yi, Deliang Fan, and Boqing Gong, “Defending Against Adversarial Attacks Using Random Forests,” Workshop on The Bright and Dark Sides of Computer Vision: Challenges and Opportunities for Privacy and Security, June 16-20, 2019, Long Beach, CA, USA [pdf]
13. [CVPR'19] Zhezhi He*, Adnan Siraj Rakin* and Deliang Fan, “Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial Attack,” Conference on Computer Vision and Pattern Recognition (CVPR), June 16-20, 2019, Long Beach, CA, USA (* The first two authors contributed equally) [pdf] [code in GitHub]
14. [CVPR'19] Zhezhi He and Deliang Fan, “Simultaneously Optimizing Weight and Quantizer of Ternary Neural Network using Truncated Gaussian Approximation,” Conference on Computer Vision and Pattern Recognition (CVPR), June 16-20, 2019, Long Beach, CA, USA [pdf]
15. [GLSVLSI'19] Shaahin Angizi and Deliang Fan, “GraphiDe: A Graph Processing Accelerator leveraging In-DRAM-Computing,” ACM Great Lakes Symposium on VLSI(GLSVLSI), May 9-11, 2019, Washington, D.C. USA ( Best Paper Award) [pdf]
16. [GLSVLSI'19] Li Yang, Zhezhi He and Deliang Fan, “Binarized Depthwise Separable Neural Network for Object Tracking in FPGA,” ACM Great Lakes Symposium on VLSI(GLSVLSI), May 9-11, 2019, Washington, D.C. USA [pdf]
17. [DAC'19] Shaahin Angizi, Jiao Sun, Wei Zhang and Deliang Fan, “AlignS: A Processing-In-Memory Accelerator for DNA Short Read Alignment Leveraging SOT-MRAM,” Design Automation Conference (DAC), June 2-6, 2019, Las Vegas, NV, USA [pdf]
18. [DAC'19] Zhezhi He, Jie Lin, Rickard Ewetz, Jiann-Shiun Yuan and Deliang Fan, “Noise Injection Adaption: End-to-End ReRAM Crossbar Non-ideal Effect Adaption for Neural Network Mapping,” Design Automation Conference (DAC), June 2-6, 2019, Las Vegas, NV, USA [pdf] [code in GitHub]
19. [ISQED'19] Arman Roohi, Shaahin Angizi, Deliang Fan and Ronald F DeMara, “Processing-In-Memory Acceleration of Convolutional Neural Networks for Energy-Efficiency and Power-Intermittency Resilience,” The 20th International Symposium on Quality Electronic Design (ISQED), March 6-7, 2019, Santa Clara, CA, USA
20. [DATE'19] Shaahin Angizi, Jiao Sun, Wei Zhang and Deliang Fan, “GraphS: A Graph Processing Accelerator Leveraging SOT-MRAM,” Design, Automation and Test in Europe (DATE), March 25-29, 2019, Florence, Italy. [pdf]
21. [WACV'19] Zhezhi He, Boqing Gong, Deliang Fan, “Optimize Deep Convolutional Neural Network with Ternarized Weights and High Accuracy,” IEEE Winter Conference on Applications of Computer Vision, January 7-11, 2019, Hawaii, USA [pdf][code in GitHub]
22. [ASPDAC'19] Shaahin Angizi, Zhezhi He and Deliang Fan, “ParaPIM: A Parallel Processing-in-Memory Accelerator for Binary-Weight Deep Neural Networks,” Asia and South Pacific Design Automation Conference (ASP-DAC), Jan. 21-24, 2019, Tokyo, Japan [pdf]
23. [ASPDAC'19] Baogang Zhang, Necati Uysal, Deliang Fan, Rickard Ewetz, “Handling Stuck-at-faults in Memristor Crossbar Arrays using Matrix Transformations,” Asia and South Pacific Design Automation Conference (ASP-DAC), Jan. 21-24, 2019, Tokyo, Japan [pdf]( Best Paper Candidate)
24. [ICCD'18] Adnan Siraj Rakin, Shaahin Angizi, Zhezhi He and Deliang Fan, “PIM-TGAN: A Processing-in-Memory Accelerator for Ternary Generative Adversarial Networks,” IEEE International Conference on Computer Design (ICCD) , Oct. 7-10, 2018, Orlando, FL, USA [pdf]
25. [ICCAD'18] Shaahin Angizi, Zhezhi He and Deliang Fan, “DIMA: A Depthwise CNN In-Memory Accelerator,” IEEE/ACM International Conference on Computer Aided Design, Nov. 5-8, 2018, San Diego, CA, USA [pdf]
26. [ISLPED'18] Li Yang, Zhezhi He and Deliang Fan, “A Fully Onchip Binarized Convolutional Neural Network FPGA Implementation with Accurate Inference,” ACM/IEEE International Symposium on Low Power Electronics and Design, July 23-25, 2018, Bellevue, Washington, USA [pdf]
27. [ISVLSI'18] Zhezhi He, Shaahin Angizi, Adnan Siraj Rakin and Deliang Fan, “BD-NET: A Multiplication-less DNN with Binarized Depthwise Separable Convolution,” IEEE Computer Society Annual Symposium on VLSI, July 9-11, 2018, Hong Kong, CHINA [pdf] ( Best Paper Award )
28. [ISVLSI'18] Zhezhi He, Shaahin Angizi and Deliang Fan, “Accelerating Low Bit-Width Deep Convolution Neural Network in MRAM,” IEEE Computer Society Annual Symposium on VLSI, July 9-11, 2018, Hong Kong, CHINA (invited) [pdf]
29. [GLSVLSI'18] Shaahin Angizi, Zhezhi He, Yu Bai, Jie Han, Mingjie Lin and Deliang Fan, “Leveraging Spintronic Devices for Efficient Approximate Logic and Stochastic Neural Network,” ACM Great Lakes Symposium on VLSI (GLSVLSI), Chicago, IL, USA, May 23-25, 2018 (invited) [pdf]
30. [DAC'18] Shaahin Angizi*, Zhezhi He*, Adnan Siraj Rakin and Deliang Fan, “CMP-PIM: An Energy-Efficient Comparator-based Processing-In-Memory Neural Network Accelerator,” IEEE/ACM Design Automation Conference (DAC), June 24-28, 2018, San Francisco, CA, USA (* The first two authors contributed equally) [pdf]
31. [DAC'18] Shaahin Angizi, Zhezhi He and Deliang Fan, “PIMA-Logic: A Novel Processing-in-Memory Architecture for Highly Flexible and Energy-Efficient Logic Computation, ” IEEE/ACM Design Automation Conference (DAC), June 24-28, 2018, San Francisco, CA, USA [pdf]
32. [WACV'18] Y. Ding, L. Wang, D. Fan and B. Gong “A Semi-Supervised Two-Stage Approach to Learning from Noisy Labels,” IEEE Winter Conference on Applications of Computer Vision, March 12-14, 2018, Stateline, NV, USA [pdf]
33. [ASPDAC'18] F. Parveen, Z. He, S. Angizi and D. Fan, “HieIM: Highly Flexible In-Memory Computing using STT MRAM,” Asia and South Pacific Design Automation Conference (ASP-DAC), Jan. 22-25, 2018, Jeju Island, Korea [pdf]
34. [ASPDAC'18] S. Angizi, Z. He, F. Parveen and D. Fan, “IMCE: Energy-Efficient Bit-Wise In-Memory Convolution Engine for Deep Neural Network,” Asia and South Pacific Design Automation Conference (ASP-DAC), Jan. 22-25, 2018, Jeju Island, Korea [pdf]
35. [ICCD'17] Z. He, S. Angizi and D. Fan, “Exploring STT-MRAM based In-Memory Computing Paradigm with Application of Image Edge Extraction,” IEEE International Conference on Computer Design (ICCD) , Nov. 5-8, 2017, Boston, MA [pdf]
36. [ICCD'17] D. Fan and S. Angizi “Energy Efficient In-Memory Binary Deep Neural Network Accelerator with Dual-Mode SOT-MRAM,” IEEE International Conference on Computer Design (ICCD) , Nov. 5-8, 2017, Boston, MA [pdf]
37. [NCAMA'17] S. Angizi and D. Fan , “IMC: Energy-Efficient In-Memory Convolver for Accelerating Binarized Deep Neural Network,” Neuromorphic Computing Symposium: Architectures, Models, and Applications , July 17-19, 2017, Knoxville, Tennessee [pdf]
38. [ICCAD'17] M. Yang, J. Hayes, D. Fan and W. Qian, “Design of Accurate Stochastic Number Generators with Noisy Emerging Devices for Stochastic Computing,” IEEE/ACM International Conference on Computer Aided Design, Nov 13-16, Irvin, CA [pdf]
39. [ISLPED'17] F. Parveen, S. Angizi, Z. He and D. Fan , “Low Power In-Memory Computing based on Dual-Mode SOT-MRAM,” IEEE/ACM International Symposium on Low Power Electronics and Design, July 24-26, 2017, Taipei, Taiwan [pdf]
40. [NANOARCH'17] Z. He, S. Angizi, F. Parveen and D. Fan , “High Performance and Energy-Efficient In-Memory Computing Architecture based on SOT-MRAM,” IEEE/ACM International Symposium on Nanoscale Architectures , July 25-26, 2017, Newport, USA [pdf]
41. [ISVLSI'17] D. Fan, S. Angizi and Z. He, “In-Memory Computing with Spintronic Devices,” IEEE Computer Society Annual Symposium on VLSI (ISVLSI), July 3-5, 2017, Bochum, Germany (invited) [pdf]
42. [ISVLSI'17]S. Angizi, Z. He, F. Parveen and D. Fan, “RIMPA: A New Reconfigurable Dual-Mode In-Memory Processing Architecture with Spin Hall Effect-Driven Domain Wall Motion Device,” IEEE Computer Society Annual Symposium on VLSI (ISVLSI), July 3-5, 2017, Bochum, Germany [pdf]
43. [ISVLSI'17]F. Parveen, Z. He, S. Angizi and D. Fan, “Hybrid Polymorphic Logic Gate with 5-Terminal Magnetic Domain Wall Motion Device,” IEEE Computer Society Annual Symposium on VLSI (ISVLSI), July 3-5, 2017, Bochum, Germany [pdf] ( Best Paper Award )
44. [MWSCAS'17]D. Fan, Z. He and S. Angizi, “Leveraging Spintronic Devices for Ultra-Low Power In-Memory Computing: Logic and Neural Network,” 60th IEEE International Midwest Symposium on Circuits and Systems, Aug. 6-9, 2017, Boston, MA, USA (invited) [pdf]
45. [ISCAS'17]F. Parveen, S. Angizi, Z. He and D. Fan, “Hybrid Polymorphic Logic Gate Using 6 Terminal Magnetic Domain Wall Motion Device,” IEEE International Symposium on Circuits & Systems (ISCAS), Baltimore, MD, USA, May 28-31, 2017 [pdf]
46. [GLSVLSI'17]Z. He, S. Angizi, F. Parveen, and D. Fan, “Leveraging Dual-Mode Magnetic Crossbar for Ultra-low Energy In-Memory Data Encryption”, 27th GLSVLSI, Banff, Alberta, Canada, May 10-12, 2017 [pdf]
47. [GLSVLSI'17]S. Angizi, Z. He, and D. Fan, “Energy Efficient In-Memory Computing Platform Based on 4-Terminal Spin Hall Effect-Driven Domain Wall Motion Devices”, 27th GLSVLSI, Banff, Alberta, Canada, May 10-12, 2017 [pdf]
48. [GLSVLSI'17]Q. Alasad, J. Yuan, and D. Fan, “Leveraging All-Spin Logic to Improve Hardware Security”, 27th GLSVLSI, Banff, Alberta, Canada, May 10-12, 2017 [pdf]
49. [DATE'17]Z. He, D. Fan, “A Tunable Magnetic Skyrmion Neuron Cluster for Energy Efficient Artificial Neural Network,” Design, Automation and Test in Europe (DATE), Lausanne, Switzerland, 27-31 March, 2017 [pdf]
50. [ISQED'17]S. Angizi, Z. He, R. DeMara and D. Fan, “Composite Spintronic Accuracy-Configurable Adder for Low Power Digital Signal Processing,” 18th International Symposium on Quality Electronic Design(ISQED), Santa Clara, CA, USA, 13-15 March, 2017[pdf]
51. [ISLPED'16]Z. He and D. Fan, “A Low Power Current-Mode Flash ADC with Spin Hall Effect based Multi-Threshold Comparator”, International Symposium on Low Power Electronics and Design (ISLPED), San Francisco, CA, Aug. 8-10, 2016[pdf]
52. [NANOARCH'16]D. Fan, “Low Power In-Memory Computing Platform with Four Terminal Magnetic Domain Wall Motion Devices”, IEEE/ ACM International Symposium on Nanoscale Architectures, , Beijing, China, July 18-20, 2016 [pdf]
53. [GLSVLSI'16]D. Fan, “ Ultra-Low Energy Reconfigurable Spintronic Threshold Logic Gate”, 26th GLSVLSI, Boston, Massachusetts, May 18-20, 2016[pdf]
54. [IJCNN'16]C. Liyanagedera, K. Yogendra, K. Roy and D. Fan, “ Spin Torque Nano-Oscillator based Oscillatory Neural Network”, 2016 IEEE International Joint Conference on Neural Network (IJCNN), Vancouver, Canada, July 24-29, 2016[pdf]
55. [ASPDAC'16]K. Yogendra, D. Fan, Y. Shim, M. Koo, and K. Roy, “ Computing with Coupled Spin Torque Nano Oscillators”, 21st Asia and South Pacific Design Automation Conference (ASP-DAC), Macao, China, Jan. 25-28, 2016[pdf]
56. [ASPDAC'16]A. Sengupta, K. Yogendra, D. Fan and K. Roy, “Prospects of efficient neural computing with arrays of magneto-metallic neurons and synapses”, 21st Asia and South Pacific Design Automation Conference (ASP-DAC), Macao, China, Jan. 25-28, 2016[pdf]
57. [DATE'14]K. Roy, M. Sharad, D. Fan and K. Yogendra, “Brain-inspired computing with spin torque devices”, Design, Automation & Test in Europe (DATE), 2014. (invited tutorial)[pdf]
58. [ISVLSI'14]K. Roy, M. Sharad, D. Fan and K. Yogendra, “Computing with Spin-Transfer-Torque Devices: Prospects and Perspectives,” IEEE Computer Society Annual Symposium on VLSI (ISVLSI), Tampa, FL, July 9-11, 2014 (special session paper)[pdf]
59. [DAC'13]M. Sharad, D. Fan, and K. Roy, “Ultra Low Power Associative Computing With Spin Neurons and Resistive Crossbar Memory,” IEEE/ACM Design Automation Conference (DAC), Austin, TX, June 2-6, 2013[pdf]
60. [ISLPED'13]K. Roy, M. Sharad, D. Fan, and K. Yogendra, “Beyond Charge-Base Computing: Boolean and Non Boolean computing Using spin Devices,” International Symposium on Low Power and Design (ISLPED), 2013. (invited tutorial)[pdf]
61. [ICCAD'13]K. Roy, M. Sharad, D. Fan, and K. Yogendra, “Exploring Boolean and Non Boolean Computing Using Spin torque Switches” International Conference on Computer-Aided Design (ICCAD), 2013. (invited tutorial)[pdf]
62. [ISQED'13]M. Sharad, D. Fan, and K. Roy, “Low Power and Compact Mixed-Mode Signal Processing Hardware using Spin-Neurons,” IEEE International Symposium on Quality Electronic Design (ISQED), Santa Clara, CA, March 4-6, 2013[pdf]
63. [E3S'13]M. Sharad, D. Fan, K. Yogendra, and K. Roy, “Ultra-Low Power Neuromorphic Computing with Spin-Torque Devices,” 3rd Berkeley Symposium on Energy Efficient Electronic Systems, 2013[pdf]