Publications

JOURNAL PUBLICATIONS

  1. Srivatsav, M., Chakrabartty, S. & Thakur,C. S. Neuromorphic computing with aer using time-to-event-margin propagation (2023). arXiv:2304.13918
  2. Ramdas Nair, A., Nath, P. K., Chakrabartty, S., & Singh Thakur, C. (2023). Multiplierless In-filter Computing for tinyML Platforms. arXiv e-prints, arXiv-2304.
  3. Mangalwedhekar, R., Singh, N., Thakur, C.S. et al. Achieving nanoscale precision using neuromorphic localization microscopy. Nat. Nanotechnol. (2023). https://doi.org/10.1038/s41565-022-01291-1
  4. S. S. Yadav, R. Agarwal, K. Bharath, S. Rao and C. S. Thakur, “tinyRadar for Fitness: A Contactless Framework for Edge Computing,” in IEEE Transactions on Biomedical Circuits and Systems, doi: 10.1109/TBCAS.2023.3244240.
  5. P. Kumar, A. Nandi, S. Chakrabartty and C. S. Thakur, Bias-Scalable Near-Memory CMOS Analog Processor for Machine Learning” IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 10.1109/JETCAS.2023.3234570
  6. P. Kumar, A. Nandi, S. Chakrabartty and C. S. Thakur, “Process, Bias, and Temperature Scalable CMOS Analog Computing Circuits for Machine Learning,” in IEEE Transactions on Circuits and Systems I: Regular Papers, 2022, doi: 10.1109/TCSI.2022.3216287.
  7. Annamalai, L., & Thakur, C. S. (2022). Theroretical Insight into Batch Normalization: Data Dependant Auto-Tuning of Regularization Rate. arXiv preprint arXiv:2209.07587.
  8. S. C. G. Kiruba Daniel et al., “Handheld, Low-Cost, Aptamer-Based Sensing Device for Rapid SARS-CoV-2 RNA Detection Using Novelly Synthesized Gold Nanoparticles,” in IEEE Sensors Journal, vol. 22, no. 19, pp. 18437-18445, 1 Oct.1, 2022, doi: 10.1109/JSEN.2022.3196598.
  9. A. R. Nair, P. K. Nath, S. Chakrabartty and C. S. Thakur, “Multiplierless MP-Kernel Machine For Energy-Efficient Edge Devices,” in IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2022
  10. Singhal, U., Kalipatnapu, S., Majumder, S., Pabbisetty, V. V. L., Jandhyala, S., Singh, V., & Thakur, C. S. Generation of control signals using second-Nyquist zone technique for superconducting qubit devices. arXiv:2203.01523.
  11. L. Annamalai, V. Ramanathan, C.S. Thakur, “Event-LSTM: An Unsupervised and Asynchronous Learning-based Representation for Event-based Data“. in IEEE Robotics and Automation Letters.
  12. P. Kumar, K. Zhu, X. Gao, S. Wang, M. Lanza, C.S. Thakur, “Hybrid architecture based on two-dimensional memristor crossbar array and CMOS integrated circuit for edge computing“, npj 2D Materials and Applications, Nature. 
  13. A.R. Nair, S. Chakrabartty, C.S. Thakur, “In-filter Computing For Designing Ultra-light Acoustic Pattern Recognizers“, IEEE Internet of Things (IoT) Journal.
  14. T. Paul, A. Mukundan, K.K. Tiwari, A. Ghosh and C.S. Thakur, “Demonstration of intrinsic STDP learning capability in all-2D multi-state MoS2memory and its application in modelling neuromorphic speech recognition” 2D Materials, DOI:10.1088/2053-1583/ac210a.
  15. Lakshmi A., Chakraborty A., Thakur C. S., “EvAn: Neuromorphic Event-based Anomaly Detection“. Frontiers in Neuroscience. DOI:10.3389/fnins.2021.699003.
  16. A. Krishna, André van Schaik, C.S. Thakur, “FPGA Implementation of Particle Filters for Robotic Source Localization” IEEE Access.
  17. J. L. Molin, E. Niebur, R. Etienne-Cummings, C.S. Thakur, “A Neuromorphic Proto-Object Based Dynamic Visual Saliency Model with a Hybrid FPGA Implementation” IEEE Transactions on Biomedical Circuits and Systems, doi: 10.1109/TBCAS.2021.3089622.
  18. S. Gupta, S. Chakraborty, C. S. Thakur, “Neuromorphic Time-Multiplexed Reservoir Computing With On-the-Fly Weight Generation for Edge Devices“. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), doi: 10.1109/TNNLS.2021.3085165.
  19. Ying Xu, S.Afshar, R. Wang, G. Cohen, C. S. Thakur, T. J. Hamilton, A. van Schaik, “A Biologically Inspired Sound Localisation System Using a Silicon Cochlea Pair“.  Applied Sciences (MDPI).
  20. A.Krishna, D. Mittal, S.G. Virupaksha, A.R. Nair, R. Narayanan, C.S. Thakur, “Biomimetic FPGA-based Spatial Navigation Model with Grid cells and Place cells“. Neural Networks (Elsevier)
  21. A.R. Mangalore, C.S. Seelamantula, C.S. Thakur, “Neuromorphic Fringe Projection Profilometry” “Supplementary Paper“. IEEE Signal Processing Letters
  22. A. Krishna, S. Rudresh, V. Shaw, H. R. Sabbella, C. S. Seelamantula, C. S. Thakur, “Unlimited Dynamic Range Analog-to-Digital Conversion” . arXiv:1911.09371.
  23. Gupta S, Kumar P, Paul T, van Schaik A, Ghosh A, Thakur C S,  “Low Power, CMOS-MoS2 Memtransistor based Neuromorphic Hybrid Architecture for Wake-Up Systems“. Scientific Reports (Nature Group)
  24. Nazreen P.M., S. Chakrabartty S., Thakur C.S.  “Multiplierless and Sparse Machine Learning based on Margin Propagation Networks“. arXiv:1910.02304
  25. Zhang J, Newman J P, Thakur C. S., Wang X, Rattray J, R. Etienne-Cummings, M Wilson,  “A closed-loop all-electronic pixel-wise adaptive imaging system for high dynamic range video“. IEEE Transactions on Circuits and Systems I (TCAS-I)
  26. Tathagata Paul,  Tanweer Ahmed,  Krishna Kanhaiya Tiwari,  Chetan Singh Thakur,  Arindam Ghosh “A high-performance MoS2 synaptic device with floating gate engineering for Neuromorphic Computing“. 2D Material (IOP Science).
  27. Lakshmi A., Chakraborty A., Thakur C. S. Neuromorphic Vision: Sensors to Event-based Algorithms. Wiley -Wires Interdisciplinary Reviews: Data Mining and Knowledge Discovery, DOI:10.1002/widm.1310.
  28. Daniel S C G, Kumar A, Sivasakthi K, Thakur C. S.  Handheld, Low-Cost Electronic Device For Rapid, Real-Time Fluorescence-Based Detection Of Hg2+, Using Aptamer-Templated ZnO Quantum Dots. Sensors and Actuators B: Elsevier
  29. Thakur C. S., Jamal Molin, Gert Cauwenberghs, Giacomo Indiveri, Kundan Kumar, Ning Qiao, Johannes Schemmel, Runchun Wang, Elisabetta Chicca, Jennifer Olson Hasler, Jae-sun Seo, Shimeng Yu, Yu Cao, André van Schaik, Ralph Etienne-Cummings . Large-Scale Neuromorphic Spiking Array Processors: A quest to mimic the brain. Frontiers in Neuroscience.
  30. Wang, R., Thakur, C. S., van Schaik, A. An FPGA-based Massively Parallel Neuromorphic Cortex Simulator. Frontiers in Neuroscience.
  31. Ying Xu, Thakur, C. S., Hamilton, Wang, R., van Schaik, A. An FPGA Implementation of the CAR-FAC Cochlear Model. Frontiers in neuroscience
  32. Xiong T, Zhang J, C. Martinez-Rubio, Thakur, C. S., et al . An Unsupervised Compressed Sensing Algorithm for Multi-Channel Neural Recording and Spike Sorting. Transactions on Neural Systems & Rehabilitation Engineering
  33. Thakur, C. S., Wang, R., Hamilton, T. J., Tapson, J., R. Etienne-Cummings & van Schaik, A. An Analogue Neuromorphic Co-processor that Utilises Device Mismatch for Learning Applications.  IEEE Transactions on Circuits and Systems I (TCAS-I)
  34. Thakur, C. S., Afshar, S., Wang, R. M., Hamilton, T. J., Tapson, J., & van Schaik, A. Bayesian Estimation and Inference Using Stochastic Electronics. Frontiers in neuroscience.
  35. Thakur, C. S., Wang, R., Hamilton, T. J., Tapson, J.,& van Schaik, A. A Low Power Trainable Neuromorphic Integrated Circuit that is Tolerant to Device Mismatch. IEEE Transactions on Circuits and Systems I: Regular Papers, 63(2), 211-221.
  36. Wang, R., Thakur, C. S., et al.  A neuromorphic hardware architecture using the Neural Engineering Framework for pattern recognition. IEEE Transactions on Biomedical Circuit and System (TBioCAS).
  37. Afshar, S., Thakur, C. S., et al.  Turn Down that Noise: Synaptic Encoding of Afferent SNR in a Single Spiking Neuron. IEEE Transactions on Biomedical Circuits and Systems (TBioCAS).
  38. Thakur, C. S., Wang, R., Hamilton, T. J., Tapson, J.,& van Schaik, A. An Online Learning Algorithm for Neuromorphic Hardware Accelerators.
  39. Thakur, C. S., Wang, R. M., Afshar, S., Hamilton, T. J., Tapson, J. C., Shamma, S. A., & van Schaik, A. Sound stream segregation: a neuromorphic approach to solve the “cocktail party problem” in real-time. Frontiers in Neuroscience.

CONFERENCE PUBLICATIONS

  1.  H.R. Sabbella, A.R. Nair, V. Gumme, S.S. Yadav, S. Chakrabartty, C.S. Thakur, “An Always-On tinyML Acoustic Classifier for Ecological Applications,“ IEEE International Symposium on Circuits and Systems (ISCAS), 2022.
  2. S.S. Yadav, R. Agarwal, K. Bharath, S. Rao,  C.S. Thakur, “tinyRadar: mmWave Radar based Human Activity Classification for Edge Computing,“ IEEE International Symposium on Circuits and Systems (ISCAS), 2022.
  3. Y. Bethi, S. Narayanan, V. Rangan, A. Chakraborty,  C.S. Thakur, “Real-Time Object Detection and Localization in Compressive Sensed Video“. IEEE International Conference on Image Processing (ICIP), 2021.
  4. A. Krishna, C.S. Thakur, “Bayesian Source Localization using Stochastic Computation“. IEEE International Symposium on Circuits and Systems (ISCAS), 2021.
  5. A.B. Ayub, P.K. Nath, V.Rangan, C.S. Thakur, “FPGA based Compressive Sensing Framework for Video Compression on Edge Devices“. VLSI Design And Test (V-DAT), 2020
  6. A.T. Tharakan, D. Bhaskar, C.S. Thakur, “Implementation of Bayesian Fly Tracking Model using Analog Neuromorphic Circuits“. IEEE International Symposium on Circuits and Systems (ISCAS), 2020.
  7. Zhang J, Khalifa A, Spetalnick S, Milad A, Rattray J, Thakur C. S., A Eisape, R. Etienne-Cummings, “A Miniature Wireless Silicon-on-Insulator Image Sensor for Brain Fluorescence Imaging” IEEE Engineering in Medicine and Biology Society (EMBC), 2020.
  8. Vignesh Ramanathan, Pritesh Dwivedi, Katabathuni Bharath, Anirban Chakraborty, Chetan Singh Thakur, ” QUICKSAL: A small and sparse visual saliency model for efficient inference in resource constrained hardware ” 2020 Winter Conference on Applications of Computer Vision (WACV ’20)
  9. S. Narayanan, Y. Bethi,  Thakur, C. S, “A Compressive Sensing Video dataset using Pixel-wise coded exposure”  arXiv:1905.10054.
  10. A. G. Mahurkar, P. K. Pokala, C. S. Thakur, and C. S. Seelamantula, “SAMIR: Sparsity amplified iteratively-reweighted beamforming for high-resolution ultrasound imaging,”Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, 2019.
  11. P. Kumar, A. R. Nair, O. Chatterjee, T. Paul, A. Ghosh, S. Chakrabartty, C. S. Thakur, “Neuromorphic In-Memory Computing Framework using Memtransistor Cross-bar based Support Vector Machines.” IEEE Midwest Symposium on Circuits and Systems (MWSCAS), 2019.
  12. S. K. Gupta, K. Kumar, C. Seelamantula, Thakur C. S., “A Portable Ultrasound Imaging System Utilizing Deep Generative Learning-Based Compressive Sensing On Pre-Beamformed RF Signals” IEEE Engineering in Medicine and Biology Society (EMBC), 2019.
  13. Raghunath, K. P., Sagar, K. M., Gokulan, T., Kumar, K., Thakur, C. S. “ASIC Based LVDT Signal Conditioner for High-Accuracy Measurements.“  In International Symposium on VLSI Design and Test (pp. 385-397). Springer, Singapore. July, 2019.
  14. B. R. Pradhan, Y. Bethi, S. Narayanan, A. Chakraborty, Thakur, C. S, “n-HAR: A Neuromorphic Event-Based Human Activity Recognition System Using Memory Surfaces“. IEEE International Symposium on Circuits and Systems (ISCAS), 2019.
  15. A. Tripathi, M. Arabizadeh, S. Khandelwal, Thakur, C. S, “Analog Neuromorphic System based on Multi Input Floating Gate MOS Neuron Model“. IEEE International Symposium on Circuits and Systems (ISCAS), 2019.
  16. R. Sharma, S. Gupta, K. Kumar, P. Kumar, Thakur, C. S, “Real-Time Image Segmentation Using Neuromorphic Pixel Array“. IEEE International Symposium on Circuits and Systems (ISCAS), 2019.
  17. S.Gupta, P. Kumar, K. Kumar, S. Chakraborty, Thakur, C. S, “Low Power Neuromorphic Analog System based on Sub-Threshold Current Mode Circuits“.IEEE International Symposium on Circuits and Systems (ISCAS), 2019.
  18. Chakraborty S, P. Priyanka, Gupta S, Afshar S, Hamilton T, Thakur C S, “Neuromorphic Object Tracking Architecture Based on Compound Eye on FPGA” IEEE Midwest Symposium on Circuits and Systems (MWSCAS), 2018.
  19. T. Xiong, J. Rattray, J. Zhang, Thakur, C. S., S. Chin, T. Tran, R. Etienne-Cummings, “Spatiotemporal Compressed Sensing for Video Compression“ IEEE Midwest Symposium on Circuits and Systems (MWSCAS), 2017.
  20. Thakur, C. S., L. Molin, T. Xiong, J. Zhang, E. Niebur, R. Etienne-Cummings, “Neuromorphic Visual Saliency Implementation Using Stochastic Computation,” IEEE International Symposium on Circuits and Systems (ISCAS), 2017.
  21. L. Molin, A. Eisape, Thakur, C. S., V. Varghese, C. Brandli, R. Etienne-Cummings, “Low-power, low-mismatch, highly-dense, array of vlsimihalas-niebur neurons,“ IEEE International Symposium on Circuits and Systems (ISCAS), 2017.
  22. Thakur, C. S., L. Molin, R. Etienne-Cummings, “Real-time image segmentation using a spiking neuromorphic processor,” Information Sciences and Systems (CISS), 2017 51st Annual Conference on, IEEE, 2017.
  23. Thakur, C. S., L. Molin, A. V. Schaik, R. Etienne-Cummings, “Inference in Spiking Bayesian Neurons using Stochastic Computation,” Information Sciences and Systems (CISS), 2017 51st Annual Conference on, IEEE, 2017.
  24. Wang, R., Thakur, C. S., et al. (2016) A Stochastic Approach to STDP learning. IEEE International Symposium on Circuits and Systems (ISCAS 2016).
  25. Xu, Y, Thakur, C. S., et al. (2016) Electronic Cochlea: Car-FAC Model on FPGA. IEEE Biomedical Circuits and Systems Conference (BioCAS 2016).
  26. Wang, R., Thakur, C. S., et al. (2016) An SRAM-Based Implementation of a Convolutional Neural Network. IEEE Biomedical Circuits and Systems Conference (BioCAS 2016).
  27. Xu, Y., Thakur, C. S., et al. (2015) A Reconfigurable Mixed-signal Implementation of Neuromorphic ADC. IEEE Biomedical Circuits and Systems Conference (BioCAS).
  28. Wang, R., Thakur, C. S., et al. (2015) A compact aVLSI conductance-based silicon neuron. IEEE Biomedical Circuits and Systems Conference (BioCAS 2015).
  29. Thakur, C. S., et al. (2015) A neuromorphic hardware framework based on population coding. IEEE International Joint Conference on Neural Networks (IJCNN).
  30. Thakur, C. S., et al. (2014) FPGA Implementation of the CAR Model of Cochlea. IEEE International Symposium on Circuits and Systems (ISCAS).
  31. Thakur, C. S., Hamilton, T. J., Tapson, J.,& van Schaik, A. (2015) Bayesian inference in spiking networks using stochastic hardware. NeuroEng 2015: 8th Australasian Workshop on Computational Neuroscience and Neuromorphic Engineering.
  32. Wang, R. M., Thakur, C. S., Hamilton, T. J., Tapson, J., van Schaik, A. (2015) A Cognitive Computing Ecosystem using the Neural Engineering Framework. NeuroEng 2015: 8th Australasian Workshop on Computational Neuroscience and Neuromorphic Engineering.
  33. Thakur, C. S., Wright J., Hamilton, T. J., Tapson, J., van Schaik, A. (2014) Digital Implementation of CAR-FAC: a Neuromorphic Model of the Human Cochlea. NeuroEng 2014: 7th Australian Workshop on Computational Neuroscience.
  34. Thakur, C. S., van Schaik, A., Tapson, J., Hamilton, T. J. (2013) Implementation of ELM Using a Stochastic Digital Architecture. Proceedings of the 11th Biennial Engineering Mathematics and Applications Conference, EMAC-2013.

BOOK CHAPTERS

1. Chakrabartty, S., Raman, B., Thakur, C. S.  (2022), “Sensing-to-learn and Learning-to-sense: Principles for designing neuromorphic sensors“, Handbook of Neuroengineering , In: Thakor N.V. (eds) Handbook of Neuroengineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-2848-4_122-1.

PATENTS

  1. Thakur, C. S., Chakraborty, A., Narayanan, S., Pradhan, B. R., “Method and System for Recognizing Activities in Surrounding Environment for Controlling Navigation of Autonomous Vehicle”, IP is filed in India and USA .
  2. Thakur, C. S., Chakrabartty, S., Nair, A.R., “Method and System for Designing a Multiplierless Kernel Machine for Energy Efficient Edge Devices“,  Provisional Indian IP Filed.
  3. Thakur, C. S., Seelamantula C., Shaw V, Krishnan A.,  R. Sunil., “Unlimited Dynamic Range Analogue – to– Digital Converters”, Provisional Indian IP Filed.
  4. S C G Kiruba Daniel, Neeraja, Sabbella H. R., Thakur, C. S, “Method of Synthesis of Metal Nanoparticles with Reusable, Solid State Reducing Agent”,  Provisional Indian IP Filed, Patent Application No – 201941043597.
  5. Thakur, C. S., J. L. Molin, E. Niebur, R. Etienne-Cummings., “A Method and Device for Fast, Efficient Data Triaging in 360˚ Video/Image, or Video/Image Captured Using any Geometrical Optical Projections onto any Geometrical Shape of Imager Plane”, Provisional IP with JHU.
  6. Thakur, C. S., Hamilton, T. J., Tapson, J., & van Schaik, A., “A Neuromorphic Trainable Analog Block”, (2014) International PCT. Patent number AU2014904154/WO2016058055.

LIVE DEMO

  1. S.Narayanan, Y. Bethi, J. Lottiery, E.Niebur, R. Etienne-Cummings, Thakur, C. S, “Live Demonstration: Real-time Implementation of Proto-Object Based Visual Saliency Model”.IEEE International Symposium on Circuits and Systems (ISCAS), 2019.
  2. Wang, R. M., Thakur, C. S., Hamilton, T. J., Tapson, J., & van Schaik, A. (2015) DeepSouth: A Turn-key Solution for Large-Scale Neural Simulations. NeuroEng 2015: 8th Australasian Workshop on Computational Neuroscience and Neuromorphic Engineering.
  3. Thakur, C. S., Wright J., Hamilton, T. J., Tapson, J., & van Schaik, A. (2014) Live Demo: Digital Implementation of CAR-FAC: a Neuromorphic Model of the Human Cochlea. NeuroEng 2014: 7th Australian Workshop on Computational Neuroscience.
  4. Thakur, C. S., Wright J., Hamilton, T. J., Tapson, J., & van Schaik, A. (2014) Live Demo: FPGA Implementation of the CAR Model of Cochlea. IEEE International Symposium on Circuits and Systems (ISCAS).
  5. Xiong T, Zhang J, Thakur, C. S., et al. Live Demonstration: A Compact all-CMOS Spatiotemporal Compressed Sensing Video Camera IEEE International Symposium on Circuits and Systems (ISCAS, 2017).

 

BLOGS

  1. Chetan Singh Thakur, Neuromorphic CMOS-MoS2 based hybrid system for low power edge-computing Device and Materials Engineering.