Exploiting analogue OxRAM conductance modulation for contrast enhancement application
A. Kumar, S. S. Bezugam, B. Hudec, T-H. Hou, and M. Suri. Electronics Letters 56, no. 12 (2020): 594-597
CV
Education
- Doctor of Philosophy (PhD) in Electrical and Computer Engineering, University of California Santa Barbara (UCSB), Sep 2022 - Present
- GPA: 4.0/4.0
- Advisor: Prof. Dmitri Strukov
- Research Group: Strukov Research Group
- Master of Science (Research) in Electrical Engineering, Indian Institute of Technology Delhi (IITD), Jul 2019 - Jun 2022
- GPA: 9.70/10
- Advisor: Prof. Manan Suri
- Research Group: NVM and Neuromorphic Hardware Research Group
- Bachelor of Technology in Electronics and Communication Engineering, Jawaharlal Nehru Technological University Hyderabad (JNTUH), Jul 2014 - May 2018
- First Class with Distinction
Work Experience
- Graduate Student Researcher, Sep 2022 - Present
- University of California Santa Barbara
- Research: Device-aware neuromorphic computing, RRAM modeling, spiking neural networks
- Supervisor: Prof. Dmitri Strukov
- Graduate Teaching Assistant, Fall 2022
- University of California Santa Barbara
- Course: ECE/CS 153A/253 - HW/SW Interface/Embedded Systems
- Supervisor: Prof. Forrest Brewer
- Duties: Built question bank; conducted and graded assignments
- Research Assistant, May 2022 - Oct 2022
- Western Sydney University, Penrith, Australia
- Research Area: Meta-learning for neuromorphic networks
- Research Group: International Centre for Neuromorphic Systems (ICNS)
- Supervisor: Dr. Saeed Afshar
- Graduate Student Researcher, Jul 2019 - Jun 2022
- Indian Institute of Technology Delhi
- Thesis: Incorporating Non Ideal Technology Attributes in Neuromorphic Network Simulations
- Supervisor: Prof. Manan Suri
- Graduate Teaching Assistant, Spring 2020, Fall 2021
- Indian Institute of Technology Delhi
- Course: ELL201 - Digital Electronics
- Supervisor: Prof. Manan Suri
- Duties: Built question bank; conducted and graded assignments for a class of 100+ students
- Research Assistant, Jun 2018 - Jun 2019
- Indian Institute of Technology Delhi
- Research Area: Neuromorphic Applications
- Research Group: NVM and Neuromorphic Hardware Research Group
- Supervisor: Prof. Manan Suri
Skills
- Programming Languages: Python, C, Embedded C, Java, Verilog
- Tools: MATLAB, Xilinx FPGA tools, Cadence, Synopsys, Proteus, ModelSim
- Hardware Platforms: FPGA, Intel Loihi neuromorphic platform, Resource-constrained embedded/edge platforms
- Frameworks: TensorFlow, PyTorch, SPICE simulation tools
Awards & Honors
- INAE Innovative Student Project Award (Master’s Thesis), 2022
- IEEE VLSID Fellowship Award, Jan 2020
Academic Service
- Graduate Student Affairs PTC Contract Workgroup Co-Chair, UCSB, 2023 - Present
- Co-chairing a workgroup drafting 2025 Graduate Student Researcher and Teaching Assistant contracts
- Reviewer for:
- Conferences: CVPR Event Vision Workshop 2021, IEEE Sensors (2021-2024), IEEE MWCAS 2022, IEEE AICAS (2023-2024), IEEE NANO 2023, IEEE ISCAS 2024
- Journals: IEEE TCAS-II Express Briefs, Nature Communications, Neural Networks
- Mentor, KMIT AI/ML Club
Professional Memberships
- IEEE (Institute of Electrical and Electronics Engineers)
- ACM (Association for Computing Machinery)
- INAE (Indian National Academy of Engineering)
Publications
Efficient Video Summarization Framework using EEG and Eye-tracking Signals
S. S. Bezugam, S. Majumdar, C. Ralekar, and T. K. Gandhi. arXiv preprint arXiv:2101.11249 (2021). (Under Review)
Fully Unsupervised Spike-Rate-Dependent Plasticity Learning With Oxide Based Memory Devices
M. Kumar, S. S. Bezugam, S. Khan and M. Suri, "Fully Unsupervised Spike-Rate-Dependent Plasticity Learning With Oxide- Based Memory Devices," in IEEE Transactions on Electron Devices, vol. 68, no. 7, pp. 3346-3352, July 2021, doi: 10.1109/TED.2021.3077346.
2D Histogram based Region Proposal (H2RP) Algorithm for Neuromorphic Vision Sensors
Medya, R., Bezugam, S.S., Bane, D. and Suri, M., 2021, July. 2D Histogram based Region Proposal (H2RP) Algorithm for Neuromorphic Vision Sensors. In International Conference on Neuromorphic Systems 2021 (pp. 1-6). , doi: 10.1145/3477145.3477263.
An adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation
A. Shaban, S. S. Bezugam, and M. Suri. Nature Communications 12, no. 1 (2021): 1-11.
Neuromorphic Recurrent Spiking Neural Networks for EMG Gesture Classification and Low Power Implementation on Loihi
S. S. Bezugam, A. Shaban, and M. Suri. arXiv preprint arXiv:2206.02061 (2022). 2023 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2023.
RRAM Based On-Sensor Visual Data Preprocessing for Efficient Image Classification
A. Kumar, S. S. Bezugam. 2023 Device Research Conference (DRC). IEEE, 2023.
CMOS-PCM Based Artificial Thermosensory Neuron for Bio-Inspired Sensing
M. Kumar, S. S. Bezugam, M. Kumar, and M. Suri. 2023 IEEE 23rd International Conference on Nanotechnology (NANO). IEEE, 2023.
ReRAM-Based NeoHebbian Synapses for Faster Training-Time-to-Accuracy Neuromorphic Hardware
T. Bhattacharya*, S.S. Bezugam*, S. Pande*, E. Wlazlak, and D. Strukov. International Electron Devices Meeting (IEDM) (2023) (pp. 1-4)
Spike frequency adaptation: bridging neural models and neuromorphic applications
C. Ganguly*, S. S. Bezugam*, E. Abs, M. Payvand and M. Suri. Communications Engineering 3(1), 22, (2024).
Quantized Context Based LIF Neurons for Recurrent Spiking Neural Networks in 45nm
S. S. Bezugam*, Y. Wu*, J. Yoo*, D. Strukov, and B. Kim. Neuro-Inspired Computational Elements Conference 2024.
RRAM based processing-in-memory for efficient intelligent vision tasks at the edge
A. Kumar and S. S. Bezugam. Memories – Materials, Devices, Circuits and Systems (Elsevier) 2024.
Controlling ReRAM’s Switching Characteristics with Shadow Memory for Continual Learning
S. S. Bezugam, T. Bhattacharya, H. Petschenig, S. Choi, G. Hutchinson, G. Pedretti, X. Sheng, J. Ignowski, T. Van Vaerenbergh, R. Beausoleil, R. Legenstein, and D. Strukov. IEEE International Memory Workshop (IMW) 2025.
SpiceXpanse: A Scalable, Automated Framework for Efficient Parameter Optimization and Modeling of RRAM Circuits
S. S. Bezugam*, S. Choi, S. Menzel, and D. B. Strukov. IEEE Nanotechnology Materials and Devices Conference (NMDC) (2025) — Accepted.