Journal Articles

  1. Liu, K., Hashemkhani, S., Vivekanand, V.S., Xiong, F., Rubin, J. and Kubendran, R., 2023. BioNN: Bio-mimetic Neural Networks on Hardware using Nonlinear Multi-timescale Mixed-feedback Control for Neuromodulatory Bursting Rhythms. IEEE Journal on Emerging and Selected Topics in Circuits and Systems.
  2. Wan, W., Kubendran, R., Schaefer, C. et al. "A compute-in-memory chip based on resistive random-access memory." Nature 608, 504–512 (2022). https://doi.org/10.1038/s41586-022-04992-8.
  3. Richardson, C., Burke, H., Frabitore, Z., Segall, R., Moses-Hampton, M., Kubendran, R., Woeppel, K., Wasan, A.D. and Emerick, T., “Medical Device Development and Start-up Company Formation for Healthcare Entrepreneurs.”, Pain Medicine, p.pnac152, 2022.
  4. Gall, R., Akcakaya, M., Erdogmus, D., & Kubendran, R., "Corticomorphic Hybrid CNN-SNN Architecture for EEG-based Low-footprint Low-latency Auditory Attention Detection", Under Review, IEEE Pattern Analysis and Machine Intelligence (PAMI), submitted July 2022.
  5. Kim, C., Park, J., Ha, S., Akinin, A., Kubendran, R., Mercier, P.P., & Cauwenberghs, G. (2019). A 3 mm × 3 mm Fully Integrated Wireless Power Receiver and Neural Interface System-on-Chip. IEEE Trans Biomed Circuits Syst (TBioCAS), 13(6), 1736-1746.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TBCAS.2019.2943506.
  6. Kubendran, R., Lee, S., Mitra, S., & Yazicioglu, R.F. (2014). Error correction algorithm for high accuracy bio-impedance measurement in wearable healthcare applications. IEEE Trans Biomed Circuits Syst (TBioCAS), 8(2), 196-205.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TBCAS.2014.2310895.

Conference Papers

  1. Vijay Shankaran Vivekanand, Samarth Chopra, Shahin Hashemkhani, and Rajkumar Chinnakonda Kubendran. 2023. Robot Locomotion through Tunable Bursting Rhythms using Efficient Bio-mimetic Neural Networks on Loihi and Arduino Platforms. Presented at ACM ICONS '23. https://doi.org/10.1145/3589737.3605965
  2. Ahuja, H. and Kubendran, R., 2023, August. High-resolution Extreme-throughput Event-based Cameras using GALS Data-scanning Architecture. In Proceedings of the 2023 International Conference on Neuromorphic Systems (pp. 1-6).
  3. K. Liu, S. Hashemkhani, J. Rubin and R. Kubendran, “Neuromorphic Networks using Nonlinear Mixed-feedback Multi-timescale Bio-mimetic Neurons”, Accepted at IEEE International Symposium on Circuits and Systems (ISCAS), May 2023.
  4. V. Vivekanand, S. Hashemkhani, S. Priyaa and R. Kubendran, “Robot Locomotion Control using Central Pattern Generator with Non-linear Bio-mimetic Neurons”, Accepted at IEEE International Conference on Robotics and Automation (ICARA), Feb 2023.
  5. S. Priya, V. Vivekanand, and R. Kubendran, “Resource efficient low-latency Stereo Vision using Query-driven Dynamic Vision Sensor”, Accepted at IEEE International Conference on Robotics and Automation (ICARA), Feb 2023.
  6. K. Liu, V. Vivekanand and R. Kubendran, “Hardware Implementation of Neuromorphic Non-linear Mixed-feedback Multi-timescale Neurons on 180nm CMOS Technology”, Poster Presentation at IEEE International Conference on Emerging Electronics (ICEE), Dec 2022.
  7. A. De, H. Mohammad, Y. Wang, R. Kubendran, A. Das, A. Anantram, “DNA Origami based Electronic Memory Technology”, 2022 22nd IEEE International Conference on Nanotechnology (NANO), July 2022.
  8. Tang, S., Wang, K., Ogrey, S., Villazon, J., Khan, S., Paul, A., Ardolino, N., Kubendran, R. and Cauwenberghs, G., “Unity Human Eye Model for Gaze Tracking with a Query-Driven Dynamic Vision Sensor”, 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 2194-2198. July 2022.
  9. R. Kubendran, A. Paul and G. Cauwenberghs, "A 256x256 6.3pJ/pixel-event Query-driven Dynamic Vision Sensor with Energy-conserving Row-parallel Event Scanning," 2021 IEEE Custom Integrated Circuits Conference (CICC), 2021, pp. 1-2, doi: 10.1109/CICC51472.2021.9431446.
  10. Wan, W., Kubendran, R., Gao, B., Josbi, S., Raina, P., Wu, H., Cauwenberghs, G. and Wong, H.S.P. "A Voltage-Mode Sensing Scheme with Differential-Row Weight Mapping For Energy-Efficient RRAM-Based In-Memory Computing." In 2020 IEEE Symposium on VLSI Technology (pp. 1-2). doi: 10.1109/vlsitechnology18217.2020.9265066.
  11. Kubendran, R., Park, J., Sharma, R., Kim, C., Joshi, S., Cauwenberghs, G., & Ha, S. (2020). A 4.2-pJ/Conv 10-b Asynchronous ADC with Hybrid Two-Tier Level-Crossing Event Coding. In 2020 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE. doi: 10.1109/iscas45731.2020.9180458.
  12. Kubendran, R., Wan, W., Joshi, S., Wong, H.S.P., & Cauwenberghs, G. (2020). A 1.52 pJ/Spike Reconfigurable Multimodal Integrate-and-Fire Neuron Array Transceiver. In International Conference on Neuromorphic Systems 2020 (ICONS), (pp. 1-4). ACM. doi: 10.1145/3407197.3407209.
  13. Sengupta, J., Kubendran, R., Neftci, E., & Andreou, A. (2020). High-Speed, Real-Time, Spike-Based Object Tracking and Path Prediction on Google Edge TPU. In 2020 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), (pp. 134-135). IEEE. doi: 10.1109/aicas48895.2020.9073867.
  14. Wan, W., Kubendran, R., Eryilmaz, S.B., Zhang, W., Liao, Y., Wu, D., Deiss, S., Gao, B., Raina, P., Joshi, S., Wu, H., Cauwenberghs, G., & Wong, H.S.P. (2020). A 74 TMACS/W CMOS-RRAM Neurosynaptic Core with Dynamically Reconfigurable Dataflow and In-situ Transposable Weights for Probabilistic Graphical Models. In Digest of Technical Papers - IEEE International Solid-State Circuits Conference (ISSCC), 2020-February, (pp. 498-500). IEEE. doi: 10.1109/ISSCC19947.2020.9062979.
  15. Kim, C., Ha, S., Akinin, A., Park, J., Kubendran, R., Wang, H., Mercier, P.P., & Cauwenberghs, G. (2017). Design of miniaturized wireless power receivers for mm-sized implants. In 2017 IEEE Custom Integrated Circuits Conference (CICC), 2017-April, (pp. 1-8). IEEE. doi: 10.1109/cicc.2017.7993703.
  16. Kim, C., Park, J., Akinin, A., Ha, S., Kubendran, R., Hui Wang, Mercier, P.P., & Cauwenberghs, G. (2016). A fully integrated 144 MHz wireless-power-receiver-on-chip with an adaptive buck-boost regulating rectifier and low-loss H-Tree signal distribution. In 2016 IEEE Symposium on VLSI Circuits (VLSI-Circuits), 2016-September, (pp. 1-2). IEEE. doi: 10.1109/vlsic.2016.7573492.
  17. Kubendran, R.C., Sunyoung Kim, & Yazicioglu, R.F. (2013). Error correction algorithm for high accuracy bio-impedance measurement in wearable healthcare applications. In 2013 IEEE International Symposium on Circuits and Systems (ISCAS), (pp. 1292-1295). IEEE. doi: 10.1109/iscas.2013.6572090.
  18. Kubendran, R. (2012). Electromagnetic and Laplace domain analysis of memristance and associative learning using memristive synapses modeled in SPICE. In 2012 International Conference on Devices, Circuits and Systems (ICDCS), (pp. 622-626). IEEE. doi: 10.1109/icdcsyst.2012.6188646.
  19. Kubendran, R., Krishnan, H., Manola, B., John, S.W.M., Chappell, W.J., & Irazoqui, P.P. (2011). A generic miniature multi-feature programmable wireless powering headstage ASIC for implantable biomedical systems. In Conf Proc IEEE Eng Med Biol Soc (EMBS), 2011, (pp. 5617-5620). IEEE. doi: 10.1109/IEMBS.2011.6091359.

Patents

  1. Kubendran, R., Benosman, R. (2022). Neuromorphic Programmable Multiple Pathways Event-based Sensors.
  2. Akcakaya, M., Kubendran, R., Erdogmuz, D., Gall, R. (2022). Hybrid CNN-SNN Architecture for EEG-based Auditory Attention Detecion.
  3. Kubendran, R., Cui, T., & Woeppel, K. (2022). Pulse Generator for Bioresorbable Electrodes.
  4. Kubendran, R.C., & Cauwenberghs, G. (2021). Query Driven Image Sensing.
  5. Mostafa, H., Kubendran, R., & Cauwenberghs, G. (2021). Compute-in-memory architecture for neural networks.
  6. Kubendran, R.C., Wang, X., & Zhang, X. (2015). High accuracy measurement of on-chip component parameters.