2024
[1] Malyaban Bal, Abhronil Sengupta, “SpikingBERT: Distilling BERT to Train Spiking Language Models Using Implicit Differentiation”, AAAI Conference on Artificial Intelligence (AAAI), 2024 (Acceptance rate ~23%). [Code]
[2] A. N. M. Nafiul Islam, Kezhou Yang, Amit K. Shukla, Pravin Khanal, Bowei Zhou, Wei-Gang Wang, Abhronil Sengupta, “Hardware in Loop Learning with Spin Stochastic Neurons”, Advanced Intelligent Systems, In Press.
[3] Bibhas Manna, Arnob Saha, Zhouhang Jiang, Kai Ni, Abhronil Sengupta, “Variation-Resilient FeFET-Based In-Memory Computing Leveraging Probabilistic Deep Learning”, IEEE Transactions on Electron Devices, In Press.
[4] Sen Lu, Abhronil Sengupta, “Deep Unsupervised Learning Using Spike-Timing-Dependent Plasticity”, Neuromorphic Computing and Engineering, In Press.
[5] Malyaban Bal, Abhronil Sengupta, “Equilibrium-Based Learning Dynamics in Spiking Architectures”, IEEE International Symposium on Circuits and Systems (ISCAS), 2024 (Invited Special Session Paper).
[6] Arnob Saha, Bibhas Manna, Sen Lu, Zhouhang Jiang, Kai Ni, Abhronil Sengupta, “Device Feasibility Analysis of Multi-level FeFETs for Neuromorphic Computing”, IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2024.
[7] Tao Zhang, Mingjie Hu, Md Zesun Ahmed Mia, Hao Zhang, Wei Mao, Katsuyuki Fukutani, Hiroyuki Matsuzaki, Lingzhi Wen, Cong Wang, Hongbo Zhao, Xuegang Chen, Yakun Yuan, Fanqi Meng, Ke Yang, Lili Zhang, Juan Wang, Aiguo Li, Weiwei Zhao, Shiming Lei, Jikun Chen, Pu Yu, Abhronil Sengupta, Hai-Tian Zhang, “Self-sensitizable neuromorphic device based on adaptive hydrogen gradient”, Matter, In Press.
2023
[1] Kezhou Yang, Dhuruva Priyan G M, Abhronil Sengupta, “Leveraging Probabilistic Switching in Superparamagnets for Temporal Information Encoding in Neuromorphic Systems”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Vol. 42, Iss. 10, pp. 3464-3468, 2023.
[2] Malyaban Bal, Abhronil Sengupta, “Sequence Learning using Equilibrium Propagation”, International Joint Conference on Artificial Intelligence (IJCAI), 2023 (Oral presentation, Acceptance rate ~15%). [Code]
[3] Zhuangyu Han, A. N. M. Nafiul Islam, Abhronil Sengupta, “Astromorphic Self-Repair of Neuromorphic Hardware Systems”, AAAI Conference on Artificial Intelligence (AAAI), 2023 (Oral presentation, Acceptance rate ~19%). [Code]
[4] A N M Nafiul Islam, Kai Ni, Abhronil Sengupta, “Cross-Layer Optimizations for Ferroelectric Neuromorphic Computing”, IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), 2023. (Invited Special Session Paper)
[5] Malyaban Bal, George M. Nishibuchi, Suhas Chelian, Srini Vasan, Abhronil Sengupta, “Bio-plausible Hierarchical Semi-Supervised Learning for Intrusion Detection”, ACM International Conference on Neuromorphic Systems (ICONS), 2023.
[6] Kezhou Yang, Abhronil Sengupta, “Leveraging Voltage-Controlled Magnetic Anisotropy to Solve Sneak Path Issues in Crossbar Arrays”, IEEE Transactions on Electron Devices, Vol. 70, Iss. 4, pp. 2021 – 2027, 2023.
[7] A. N. M. Nafiul Islam, Arnob Saha, Zhouhang Jiang, Kai Ni, Abhronil Sengupta, “Hybrid Stochastic Synapses Enabled by Scaled Ferroelectric Field-effect Transistors”, Applied Physics Letters, Vol. 122, Iss. 12, pp. 123701, 2023.
[8] Sunbin Deng, Haoming Yu, Tae Joon Park, A. N. M. Nafiul Islam, Sukriti Manna, Alexandre Pofelski, Qi Wang, Yimei Zhu, Subramanian K. R. S. Sankaranarayanan, Abhronil Sengupta, Shriram Ramanathan, “Selective area doping for Mott neuromorphic electronics”, Science Advances, Vol. 9, Iss. 11, pp. 1-9, 2023.
[9] Sunbin Deng, Tae Joon Park, Haoming Yu, Arnob Saha, A. N. M. Nafiul Islam, Qi Wang, Abhronil Sengupta, Shriram Ramanathan, “Hydrogenated VO2 Bits for Probabilistic Computing”, IEEE Electron Device Letters, Vol. 44, Iss. 10, pp. 1776-1779, 2023.
[10] Tae Joon Park, Sunbin Deng, Sukriti Manna, A. N. M. Nafiul Islam, Haoming Yu, Yifan Yuan, Dillon D Fong, Alexander A Chubykin, Abhronil Sengupta, Subramanian KRS Sankaranarayanan, Shriram Ramanathan, “Complex oxides for brain‐inspired computing: A review”, Advanced Materials, Vol. 35, Iss. 37, pp. 2203352, 2023.
2022
[1] Hai-Tian Zhang*, Tae Joon Park*, A. N. M. Nafiul Islam*, Dat S. J. Tran*, Sukriti Manna*, Qi Wang*, Sandip Mondal, Haoming Yu, Suvo Banik, Shaobo Cheng, Hua Zhou, Sampath Gamage, Sayantan Mahapatra, Yimei Zhu, Yohannes Abate, Nan Jiang, Subramanian K. R. S. Sankaranarayanan, Abhronil Sengupta, Christof Teuscher, Shriram Ramanathan, “Reconfigurable perovskite nickelate electronics for artificial intelligence”, Science, Vol. 375, Iss. 6580, pp. 533-539, 2022 (Featured in PSU News, Featured in News & Views of Nature Materials, Featured in IEEE Spectrum, * denotes equal first author contribution).
[2] Sen Lu, Abhronil Sengupta, “Neuroevolution Guided Hybrid Spiking Neural Network Training”, Frontiers in Neuroscience, Vol. 16, No. 838523, 2022.
[3] Sen Lu, Abhronil Sengupta, “Hybrid Neuromorphic Systems: An Algorithm-Application-Hardware-Neuroscience Co-Design Perspective”, IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2022.
[4] Haoming Yu, A. N. M. Nafiul Islam, Sandip Mondal, Abhronil Sengupta, Shriram Ramanathan, “Switching Dynamics in Vanadium Dioxide-Based Stochastic Thermal Neurons”, IEEE Transactions on Electron Devices, Vol. 69, Iss. 6, pp. 3135 – 3141, 2022.
[5] Chengyang Zhang, Ravindra Singh Bisht, Amin Nozariasbmarz, Arnob Saha, Chan Su Han, Qi Wang, Yifan Yuan, Abhronil Sengupta, Shashank Priya, and Shriram Ramanathan, “Synthesis and electrical behavior of VO2 thin films grown on SrRuO3 electrode layers”, Journal of Vacuum Science and Technology A, Vol. 40, Iss. 4, pp. 043405, 2022.
[6] Sandip Mondal, Zhen Zhang, A. N. M. Nafiul Islam, Robert Andrawis, Sampath Gamage, Neda Alsadat Aghamiri, Qi Wang, Hua Zhou, Fanny Rodolakis, Richard Tran, Jasleen Kaur, Chi Chen, Shyue Ping Ong, Abhronil Sengupta, Yohannes Abate, Kaushik Roy, Shriram Ramanathan, “All-Electric Nonassociative Learning in Nickel Oxide”, Advanced Intelligent Systems, Vol. 4, Iss. 10, No. 2200069, 2022 (Featured in Advanced Science News).
[7] Wyler Zahm, Tyler Stern, Malyaban Bal, Abhronil Sengupta, Aswin Jose, Suhas Chelian, Srini Vasan, “Cyber-Neuro RT: Real-time Neuromorphic Cybersecurity”, Procedia Computer Science, Vol. 213, pp. 536-545, 2022.
[8] Sonali Singh, Anup Sarma, Sen Lu, Abhronil Sengupta, Mahmut T. Kandemir, Emre Neftci, Vijaykrishnan Narayanan, Chita R. Das, “Skipper: Enabling efficient SNN training through activation-checkpointing and time-skipping”, IEEE/ACM International Symposium on Microarchitecture (MICRO), 2022.
2021
[1] Umang Garg, Kezhou Yang, Abhronil Sengupta, “Emulation of Astrocyte Induced Neural Phase Synchrony in Spin-Orbit Torque Oscillator Neurons”, Frontiers in Neuroscience, Vol. 15, No. 699632, 2021 (Featured in PSU News).
[2] Arnob Saha*, A. N. M. Nafiul Islam*, Zijian Zhao, Shan Deng, Kai Ni, Abhronil Sengupta, “Intrinsic synaptic plasticity of ferroelectric field effect transistors for online learning”, Applied Physics Letters, Vol. 119, Iss. 13, pp. 133701, 2021 (* denotes equal first author contribution, DOE EFRC 3DFeM Highlight).
[3] Mehul Rastogi, Sen Lu, Nafiul Islam, Abhronil Sengupta, “On the Self-Repair Role of Astrocytes in STDP Enabled Unsupervised SNNs”, Frontiers in Neuroscience, Vol. 14, No. 603796, 2021.
[4] Kaveri Mahapatra, Sen Lu, Abhronil Sengupta, Nilanjan Ray Chaudhuri, “Power System Disturbance Classification with Online Event-Driven Neuromorphic Computing”, IEEE Transactions on Smart Grid, Vol. 12, Iss. 3, pp. 2343 – 2354, 2021.
[5] Shubham Jain, Abhronil Sengupta, Kaushik Roy, Anand Raghunathan, “RxNN: A Framework for Evaluating Deep Neural Networks on Resistive Crossbars”, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Vol. 40, Iss. 2, pp. 326 – 338, 2021.
[6] Sonali Singh, Anup Sarma, Sen Lu, Abhronil Sengupta, Vijaykrishnan Narayanan, Chita Das, “Gesture-SNN: Co-optimizing accuracy, latency and energy of SNNs for neuromorphic vision sensors”, ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED), 2021.
[7] Wilson Yanez, Yongxi Ou, Run Xiao, Jahyun Koo, Jacob T. Held, Supriya Ghosh, Jeffrey Rable, Timothy Pillsbury, Enrique González Delgado, Kezhou Yang, Juan Chamorro, Alexander J. Grutter, Patrick Quarterman, Anthony Richardella, Abhronil Sengupta, Tyrel McQueen, Julie A. Borchers, K. Andre Mkhoyan, Binghai Yan, and Nitin Samarth, “Spin and charge interconversion in Dirac semimetal thin films”, Physical Review Applied, Vol. 16, Iss. 5, pp. 054031, 2021 (Editor’s Suggestion).
2020
[1] Sen Lu, Abhronil Sengupta, “Exploring the Connection Between Binary and Spiking Neural Networks”, Frontiers in Neuroscience, Vol. 14, No. 535, 2020. [Code]
[2] Kezhou Yang, Akul Malhotra, Sen Lu, Abhronil Sengupta, “All-Spin Bayesian Neural Networks”, IEEE Transactions on Electron Devices, Vol. 67, Iss. 3, pp. 1340 – 1347, 2020.
[3] Kezhou Yang, Abhronil Sengupta, “Stochastic magnetoelectric neuron for temporal information encoding”, Applied Physics Letters, Vol. 116, Iss. 4, pp. 043701, 2020.
[4] Akul Malhotra, Sen Lu, Kezhou Yang, Abhronil Sengupta, “Exploiting Oxide Based Resistive RAM Variability for Bayesian Neural Network Hardware Design”, IEEE Transactions on Nanotechnology, Vol. 19, pp. 328 – 331, 2020.
[5]
[6] Amogh Agrawal, Indranil Chakraborty, Deboleena Roy, Utkarsh Saxena, Saima Sharmin, Yong Shim, Gopalakrishnan Srinivasan, Chamika Liyanagedera, Abhronil Sengupta, Kaushik Roy, “Revisiting Stochastic Computing in the Era of Nano-scale Non-volatile Technologies”, IEEE Transactions on Very Large Scale Integration Systems, Vol. 28, Iss. 12, pp. 2481 – 2494, 2020 (Invited Keynote Paper).
[7] Sonali Singh, Anup Sarma, Nicholas Jao, Ashutosh Pattnaik, Sen Lu, Kezhou Yang, Abhronil Sengupta, Vijaykrishnan Narayanan, Chita Das, “NEBULA: A Neuromorphic Spin-Based Ultra-Low Power Architecture for SNNs and ANNs”, IEEE/ACM International Symposium on Computer Architecture (ISCA), 2020.
[8] Gopalakrishnan Srinivasan, Chankyu Lee, Abhronil Sengupta, Priyadarshini Panda, Syed Shakib Sarwar, Kaushik Roy, “Training Deep Spiking Neural Networks for Energy Efficient Neuromorphic Computing”, International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020.