Dr. Sanjay Kumar (Postdoc@ University of Edinburgh, Scotland, UK & Ph.D. IIT Indore)
DST-Scientist (Inspire)
Department of Electronics Engineering, Indian Institute of Technology (ISM)) Dhanbad.
Trusted Areas of Research (but not limited):
Non-volatile Memories, Memristor Crossbar Array Devices, and Systems, Transition Metal Oxides (TMOs), Physical and Analytical Modelling of Memristor/ReRAM Devices,
2D Materials, Neuromorphic Computing, In-memory Computation, Artificial Synapses, Advanced Memory Technology for Human Bionic Visual Systems
Micro/Nano Fabrication Processes, MEMS-based Capacitive Transducers, and Biological Sensors.
Honours/Awards:
Department of Science and Technology (DST) Inspire Faculty Award. (March 2024).
Science and Engineering Research Board (SERB) National Postdoc Fellowship (NPDF) award. (February 2024).
Department of Science and Technology (DST) PhD Inspire fellowship award. (May 2018-Feb 2023).
1st Rank (Gold Medalist) in Rajasthan Technical University (M.Tech (Nanotechnology)).
Received the prestigious “IEEE NTC Best Chapter Award 2021" by the IEEE Nanotechnology Council (NTC).
Received the prestigious “Darrel Chong Student Activity Award 2022-Bronze" by the IEEE NTC.
Brief Biography:
Currently, I am working as a DST Scientist (Inspire) of Electronics Engineering at the Department of Electronics Engineering, Indian Institute of Technology (Indian School of Mines) (IIT(ISM)) Dhanbad, Jharkhand, India. Before joining IIT (ISM) Dhanbad, I worked as a Postdoctoral Researcher at the Centre for Electronics Frontiers, School of Engineering, University of Edinburgh, Scotland, UK under the supervision of Prof. Themis Prodromakis. I completed my Ph.D. degree at Hybrid Nanodevice Research Group (HNRG) of the Department of Electrical Engineering, Indian Institute of Technology Indore (IIT Indore), India in February 2023 under the supervision of Prof. Shaibal Mukherjee and Prof. Ajay Agarwal (Department of Electrical Engineering, IIT Jodhpur). My research interests include in-memory computation, Resistive Random Access Memory (ReRAM), Memristor Devices and Systems, Neuromorphic Computation, Physical/Analytical Modelling of Memristor/ReRAM Devices, Artificial Synapses, and Capacitive Transducers.
Key Highlights for My Ph.D. Research Work: During my Ph.D., I have developed wafer-scale Y2O3-based memristive crossbar arrays sizes of (15×12) and (30×25) with superior switching stability, high endurance, and retention characteristics, high device yield (>90%), ultralow values of coefficient of variability for device-to-device (D2D) and cycle-to-cycle (C2C), multilevel current programming functionality, random alphabet writing capability, synaptic leaning with potentiation and depression processes, and spike time-dependent plasticity (STDP) as analogous to the Hebbian learning rules which are similar to the functionality the real human brain, for the first time in the literature.