• BE, Electronics and Telecommunication Engineering, Jadavpur University, 2013
• Ph D, Electrical and Computer Engineering, Purdue University, 2018

Journal Articles

A. N. M. Nafiul Islam, Arnob Saha, Zhouhang Jiang, Kai Ni and Abhronil Sengupta, 2023, "Hybrid stochastic synapses enabled by scaled ferroelectric field-effect transistors", Applied Physics Letters, 122, (12), pp. 123701

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 and Shriram Ramanathan, 2023, "Selective area doping for Mott neuromorphic electronics", Science Advances, 9, (11), pp. 1-9

Kezhou Yang and Abhronil Sengupta, 2023, "Leveraging Voltage-Controlled Magnetic Anisotropy to Solve Sneak Path Issues in Crossbar Arrays", IEEE Transactions on Electron Devices, 70, (4), pp. 2021 - 2027

Kezhou Yang, Dhuruva Priyan G M and Abhronil Sengupta, 2023, "Leveraging Probabilistic Switching in Superparamagnets for Temporal Information Encoding in Neuromorphic Systems", IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 42, (10), pp. 3464 - 3468

Sunbin Deng, Tae Joon Park, Haoming Yu, Arnob Saha, A N M Nafiul Islam, Qi Wang, Abhronil Sengupta and Shriram Ramanathan, 2023, "Hydrogenated VO2 Bits for Probabilistic Computing", IEEE Electron Device Letters, 44, (10), pp. 1776 - 1779

Nitin Rathi, Indranil Chakraborty, Adarsh Kosta, Abhronil Sengupta, Aayush Ankit, Priyadarshini Panda and Kaushik Roy, 2022, "Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware", ACM Computing Surveys

Sandip Mondal, Zhen Zhang, A. N. M. Nafiul Islam, Robert Andrawis, Sampath Gamage, Neda Alsadat Aghamiri, Hua Zhou, Fanny Rodolakis, Richard Tran, Jasleen Kaur, Chi Chen, Shyue Ping Ong, Abhronil Sengupta, Yohannes Abate, Kaushik Roy and Shriram Ramanathan, 2022, "All-Electric Nonassociative Learning in Nickel Oxide", Advanced Intelligent Systems, 4, (10), pp. 2200069

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 and Shriram Ramanathan, 2022, "Complex oxides for brain-inspired computing: A review", Advanced Materials, pp. 2203352

Chengyang Zhang, Ravindra Singh Bisht, Amin Nozariasbmarz, Arnob Saha, Chan Su Han, Qi Wang, Yifan Yuan, Abhronil Sengupta, Shashank Priya and Shriram Ramanathan, 2022, "Synthesis and electrical behavior of VO2 thin films grown on SrRuO3 electrode layers", Journal of Vacuum Science and Technology A, 40, (4), pp. 043405

Haoming Yu, Nafiul Islam, Sandip Mondal, Abhronil Sengupta and Shriram Ramanathan, 2022, "Switching Dynamics in Vanadium Dioxide-Based Stochastic Thermal Neurons", IEEE Transactions on Electron Devices, 69, (6), pp. 3135 – 3141

Sen Lu and Abhronil Sengupta, 2022, "Neuroevolution Guided Hybrid Spiking Neural Network Training", Frontiers in Neuroscience, 16, pp. 838523

Hai-Tian Zhang, Tae Joon Park, 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 and Shriram Ramanathan, 2022, "Reconfigurable perovskite nickelate electronics for artificial intelligence", Science, 375, (6580), pp. 533-539

Wilson Yanez, Yongxi Ou, Run Xiao, Jahyun Koo, Jacob T Held, Supriya Ghosh, Jeffrey Rable, Timothy Pillsbury, Enrique Gonzalez 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, 2021, "Spin and charge interconversion in Dirac semimetal thin films", Physical Review Applied, 16, (5), pp. 054031

Umang Garg, Kezhou Yang and Abhronil Sengupta, 2021, "Emulation of astrocyte induced neural phase synchrony in spin-orbit torque oscillator neurons", Frontiers in Neuroscience, 14, pp. 699632

Arnob Saha, Nafiul Islam, Zijian Zhao, Shan Deng, Kai Ni and Abhronil Sengupta, 2021, "Intrinsic synaptic plasticity of ferroelectric field effect transistors for online learning", Applied Physics Letters, 119, (13), pp. 133701

Kaveri Mahapatra, Sen Lu, Abhronil Sengupta and Nilanjan Ray Chaudhuri, 2021, "Power System Disturbance Classification with Online Event-Driven Neuromorphic Computing", IEEE Transactions on Smart Grid, 12, (3), pp. 2343-2354

Mehul Rastogi, Sen Lu, Nafiul Islam and Abhronil Sengupta, 2021, "On the Self-Repair Role of Astrocytes in STDP Enabled Unsupervised SNNs", Frontiers in Neuroscience, 14, pp. 603796

Shubham Jain, Abhronil Sengupta, Kaushik Roy and Anand Raghunathan, 2021, "RxNN: A Framework for Evaluating Deep Neural Networks on Resistive Crossbars", IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 40, (2), pp. 326-338

Kezhou Yang, Akul Malhotra, Sen Lu and Abhronil Sengupta, 2020, "All-Spin Bayesian Neural Networks", IEEE Transactions on Electron Devices, 67, (3), pp. 1340 – 1347

Kezhou Yang and Abhronil Sengupta, 2020, "Stochastic Magnetoelectric Neuron for Temporal Information Encoding", Applied Physics Letters, 116, (4), pp. 043701

Aayush Ankit, Timur Ibrayev, Abhronil Sengupta and Kaushik Roy, 2020, "TraNNsformer: Clustered Pruning on Crossbar-based Architectures for Energy Efficient Neural Networks", IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 39, (10), pp. 2361 - 2374

Amogh Agrawal, Indranil Chakraborty, Deboleena Roy, Utkarsh Saxena, Saima Sharmin, Yong Shim, Gopalakrishnan Srinivasan, Chamika Liyanagedera, Abhronil Sengupta and Kaushik Roy, 2020, "Revisiting Stochastic Computing in the Era of Nano-scale Non-volatile Technologies", IEEE Transactions on Very Large Scale Integration Systems, 28, (12), pp. 2481 - 2494

Akul Malhotra, Sen Lu, Kezhou Yang and Abhronil Sengupta, 2020, "Exploiting Oxide Based Resistive RAM Variability for Bayesian Neural Network Hardware Design", IEEE Transactions on Nanotechnology, 19, pp. 328 - 331

Sen Lu and Abhronil Sengupta, 2020, "Exploring the Connection Between Binary and Spiking Neural Networks", Frontiers in Neuroscience, 14, pp. 535

Abhronil Sengupta, Yuting Ye, Robert Wang, Chiao Liu and Kaushik Roy, 2019, "Going deeper in spiking neural networks: Vgg and residual architectures", Frontiers in neuroscience, 13

Parami Wijesinghe, Aayush Ankit, Abhronil Sengupta and Kaushik Roy, 2018, "An All-Memristor Deep Spiking Neural Computing System: A Step Toward Realizing the Low-Power Stochastic Brain", IEEE Transactions on Emerging Topics in Computational Intelligence, 2, (5), pp. 345--358

Indranil Chakraborty, Gobinda Saha, Abhronil Sengupta and Kaushik Roy, 2018, "Toward Fast Neural Computing using All-Photonic Phase Change Spiking Neurons", Scientific Reports, 8, (1), pp. 12980

Yong Shim, Abhronil Sengupta and Kaushik Roy, 2018, "Biased Random Walk Using Stochastic Switching of Nanomagnets: Application to SAT Solver", IEEE Transactions on Electron Devices, 65, (4), pp. 1617--1624

Mei-Chin Chen, Abhronil Sengupta and Kaushik Roy, 2018, "Magnetic Skyrmion as a Spintronic Deep Learning Spiking Neuron Processor", IEEE Transactions on Magnetics, 54, (8), pp. 1--7

Abhronil Sengupta and Kaushik Roy, 2018, "Neuromorphic computing enabled by physics of electron spins: Prospects and perspectives", Applied Physics Express, 11, (3), pp. 030101

Kaushik Roy, Abhronil Sengupta and Yong Shim, 2018, "Perspective: Stochastic magnetic devices for cognitive computing", Journal of Applied Physics, 123, (21), pp. 210901

Bing Han, Aayush Ankit, Abhronil Sengupta and Kaushik Roy, 2017, "Cross-Layer Design Exploration for Energy-Quality Tradeoffs in Spiking and Non-Spiking Deep Artificial Neural Networks", IEEE Transactions on Multi-Scale Computing Systems, (1), pp. 1--1

Abhronil Sengupta and Kaushik Roy, 2017, "Encoding neural and synaptic functionalities in electron spin: A pathway to efficient neuromorphic computing", Applied Physics Reviews, 4, (4), pp. 041105

Priyadarshini Panda, Swagath Venkataramani, Abhronil Sengupta, Anand Raghunathan and Kaushik Roy, 2017, "Energy-efficient object detection using semantic decomposition", IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 25, (9), pp. 2673--2677

Abhronil Sengupta, Chamika Mihiranga Liyanagedera, Byunghoo Jung and Kaushik Roy, 2017, "Magnetic tunnel junction as an on-chip temperature sensor", Scientific reports, 7, (1), pp. 11764

Chamika M Liyanagedera, Abhronil Sengupta, Akhilesh Jaiswal and Kaushik Roy, 2017, "Stochastic spiking neural networks enabled by magnetic tunnel junctions: From nontelegraphic to telegraphic switching regimes", Physical Review Applied, 8, (6), pp. 064017

Yong Shim, Shuhan Chen, Abhronil Sengupta and Kaushik Roy, 2017, "Stochastic spin-orbit torque devices as elements for bayesian inference", Scientific Reports, 7, (1), pp. 14101

Priyadarshini Panda, Abhronil Sengupta and Kaushik Roy, 2017, "Energy-efficient and improved image recognition with conditional deep learning", ACM Journal on Emerging Technologies in Computing Systems (JETC), 13, (3), pp. 33

Abhronil Sengupta and Kaushik Roy, 2016, "A vision for all-spin neural networks: A device to system perspective", IEEE Transactions on Circuits and Systems I: Regular Papers, 63, (12), pp. 2267--2277

Deliang Fan, Mrigank Sharad, Abhronil Sengupta and Kaushik Roy, 2016, "Hierarchical temporal memory based on spin-neurons and resistive memory for energy-efficient brain-inspired computing", IEEE transactions on neural networks and learning systems, 27, (9), pp. 1907--1919

Abhronil Sengupta, Aparajita Banerjee and Kaushik Roy, 2016, "Hybrid spintronic-CMOS spiking neural network with on-chip learning: Devices, circuits, and systems", Physical Review Applied, 6, (6), pp. 064003

Gopalakrishnan Srinivasan, Abhronil Sengupta and Kaushik Roy, 2016, "Magnetic tunnel junction based long-term short-term stochastic synapse for a spiking neural network with on-chip STDP learning", Scientific Reports, 6, pp. 29545

Abhronil Sengupta, Priyadarshini Panda, Parami Wijesinghe, Yusung Kim and Kaushik Roy, 2016, "Magnetic tunnel junction mimics stochastic cortical spiking neurons", Scientific Reports, 6, pp. 30039

Abhronil Sengupta, Maryam Parsa, Bing Han and Kaushik Roy, 2016, "Probabilistic deep spiking neural systems enabled by magnetic tunnel junction", IEEE Transactions on Electron Devices, 63, (7), pp. 2963--2970

Abhronil Sengupta, Yong Shim and Kaushik Roy, 2016, "Proposal for an all-spin artificial neural network: Emulating neural and synaptic functionalities through domain wall motion in ferromagnets", IEEE transactions on biomedical circuits and systems, 10, (6), pp. 1152--1160

Abhronil Sengupta and Kaushik Roy, 2016, "Short-term plasticity and long-term potentiation in magnetic tunnel junctions: Towards volatile synapses", Physical Review Applied, 5, (2), pp. 024012

Zubair Al Azim, Abhronil Sengupta, Syed Shakib Sarwar and Kaushik Roy, 2016, "Spin-torque sensors for energy efficient high-speed long interconnects", IEEE Transactions on Electron Devices, 63, (2), pp. 800--808

Xuanyao Fong, Yusung Kim, Karthik Yogendra, Deliang Fan, Abhronil Sengupta, Anand Raghunathan and Kaushik Roy, 2016, "Spin-transfer torque devices for logic and memory: Prospects and perspectives", IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 35, (1), pp. 1--22

Abhronil Sengupta, Zubair Al Azim, Xuanyao Fong and Kaushik Roy, 2015, "Spin-orbit torque induced spike-timing dependent plasticity", Applied Physics Letters, 106, (9), pp. 093704

Abhronil Sengupta, Sri Harsha Choday, Yusung Kim and Kaushik Roy, 2015, "Spin orbit torque based electronic neuron", Applied Physics Letters, 106, (14), pp. 143701

Saugat Bhattacharyya, Abhronil Sengupta, Tathagatha Chakraborti, Amit Konar and DN Tibarewala, 2014, "Automatic feature selection of motor imagery EEG signals using differential evolution and learning automata", Medical & biological engineering & computing, 52, (2), pp. 131--139

Conference Proceedings

Malyaban Bal and Abhronil Sengupta, 2023, "Sequence Learning using Equilibrium Propagation", pp. 2949-2957

Zhuangyu Han, A. N. M. Nafiul Islam and Abhronil Sengupta, 2023, "Astromorphic Self-Repair of Neuromorphic Hardware Systems", 37, (6), pp. 7821-7829

A. N. M. Nafiul Islam, Kai Ni and Abhronil Sengupta, 2023, "Cross-Layer Optimizations for Ferroelectric Neuromorphic Computing"

Sonali Singh, Anup Sharma, Sen Lu, Abhronil Sengupta, Mahmut T. Kandemir, Emre Neftci, Vijaykrishnan Narayanan and Chita Das, 2022, "Skipper: Enabling efficient SNN training through activation-checkpointing and time-skipping", pp. 1-17

Wyler Zahm, Tyler Stern, Malyaban Bal, Abhronil Sengupta, Aswin Jose, Suhas Chelian and Srini Vasan, 2022, "Cyber-Neuro RT: Real-time Neuromorphic Cybersecurity", 213, pp. 536-545

Sen Lu and Abhronil Sengupta, 2022, "Hybrid Neuromorphic Systems: An Algorithm-Application-Hardware-Neuroscience Co-Design Perspective", pp. 1-4

Sonali Singh, Anup Sharma, Sen Lu, Abhronil Sengupta, Vijaykrishnan Narayanan and Chita Das, 2021, "Gesture-SNN: Co-optimizing accuracy, latency and energy of SNNs for neuromorphic vision sensors", pp. 1-6

Sonali Singh, Anup Sharma, Nicholas Jao, Ashutosh Pattnaik, Sen Lu, Kezhou Yang, Abhronil Sengupta, Vijaykrishnan Narayanan and Chita Das, 2020, "NEBULA: A Neuromorphic Spin-Based Ultra-Low Power Architecture for SNNs and ANNs", pp. 363-376

Gopalakrishnan Srinivasan, Chankyu Lee, Abhronil Sengupta, Priyadarshini Panda, Syed Shakib Sarwar and Kaushik Roy, 2020, "Training Deep Spiking Neural Networks for Energy Efficient Neuromorphic Computing", pp. 8549-8553

Nicholas Jao, Akshay Krishna Ramanathan, Abhronil Sengupta, John Sampson and Vijaykrishnan Narayanan, 2019, "Programmable Non-Volatile Memory Design Featuring Reconfigurable In-Memory Operations", pp. 1--5

Aayush Ankit, Abhronil Sengupta and Kaushik Roy, 2018, "Neuromorphic Computing Across the Stack: Devices, Circuits and Architectures", pp. 1--6

Abhronil Sengupta, Gopalakrishnan Srinivasan, Deboleena Roy and Kaushik Roy, 2018, "Stochastic Inference and Learning Enabled by Magnetic Tunnel Junctions", pp. 15--6

Gopalakrishnan Srinivasan, Abhronil Sengupta and Kaushik Roy, 2017, "Magnetic tunnel junction enabled all-spin stochastic spiking neural network", pp. 530--535

Abhronil Sengupta, Aayush Ankit and Kaushik Roy, 2017, "Performance analysis and benchmarking of all-spin spiking neural networks", pp. 4557--4563

Aayush Ankit, Abhronil Sengupta, Priyadarshini Panda and Kaushik Roy, 2017, "RESPARC: A reconfigurable and energy-efficient architecture with memristive crossbars for deep spiking neural networks", pp. 27

Aayush Ankit, Abhronil Sengupta and Kaushik Roy, 2017, "TraNNsformer: Neural network transformation for memristive crossbar based neuromorphic system design", pp. 533--540

Priyadarshini Panda, Abhronil Sengupta and Kaushik Roy, 2016, "Conditional deep learning for energy-efficient and enhanced pattern recognition", pp. 475--480

Priyadarshini Panda, Abhronil Sengupta, Syed Shakib Sarwar, Gopalakrishnan Srinivasan, Swagath Venkataramani, Anand Raghunathan and Kaushik Roy, 2016, "Cross-layer approximations for neuromorphic computing: from devices to circuits and systems", pp. 98

Yong Shim, Abhronil Sengupta and Kaushik Roy, 2016, "Low-power approximate convolution computing unit with domain-wall motion based spin-memristor for image processing applications", pp. 21

Abhronil Sengupta, Priyadarshini Panda, Anand Raghunathan and Kaushik Roy, 2016, "Neuromorphic computing enabled by spin-transfer torque devices", pp. 32--37

Bing Han, Abhronil Sengupta and Kaushik Roy, 2016, "On the energy benefits of spiking deep neural networks: A case study", pp. 971--976

Abhronil Sengupta, Karthik Yogendra, Deliang Fan and Kaushik Roy, 2016, "Prospects of efficient neural computing with arrays of magneto-metallic neurons and synapses", pp. 115--120

Abhronil Sengupta, Karthik Yogendra and Kaushik Roy, 2016, "Spintronic devices for ultra-low power neuromorphic computation (Special session paper)", pp. 922--925

Abhronil Sengupta, Bing Han and Kaushik Roy, 2016, "Toward a spintronic deep learning spiking neural processor", pp. 544--547

Abhronil Sengupta, Akhilesh Jaiswal and Kaushik Roy, 2016, "True random number generation using voltage controlled spin-dice", pp. 1--2

Abhronil Sengupta and Kaushik Roy, 2015, "Spin-transfer torque magnetic neuron for low power neuromorphic computing", pp. 1--7

Tathagata Chakraborti, Abhronil Sengupta, Abhishek Midya, Amit Konar and Somnath Sengupta, 2013, "3-D model assisted facial error concealment technique using regenerative particle filter based tracking", pp. 1--6

Abstracts

Abhronil Sengupta, Yong Shim and Kaushik Roy, 2018, "Stochastic Switching of Nanomagnets for Post-CMOS Computing", Bulletin of the American Physical Society

• ACM Distinguished Speaker, 2024 - 2027

• Purdue Engineering 38 by 38 award, 2024

• ARO Early Career Award, 2024

• IEEE Electron Devices Society (EDS) Early Career Award, IEEE, 2023

• NSF CAREER Award, 2023

• IEEE Circuits and Systems (CAS) Society Outstanding Young Author Award, IEEE, 2019

• Best Paper Award at the 2018 IEEE Workshop on Signal Processing Systems (SiPS), 2018

• Schmidt Science Fellows Award nominee, Purdue University, 2017

• Bilsland Dissertation Fellowship, Purdue University, 2017

• Michael and Katherine Birck Fellowship, Purdue University, 2013 - 2015

• T.P. Saha Memorial Gold Medal, D.Mukhopadhyay Memorial and S.Deb Memorial Gold Medals, Jadavpur University, 2013

• WISE Fellowship, DAAD (German Academic Exchange Service), 2012

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