34 citations · 153 across the 43 of their papers we have counts for
44 papers
Sensing to Intelligence: Principles for Neuromorphic Circuits and Systems
Saptarshi Maiti, Chetan Singh Thakur
Neuromorphic engineering began with the idea that the physical behavior of a system could itself be used for computation, taking inspiration from the way nervous systems sense, ada…
Programmable Silicon Retina on Pixel Processor Array
Maciej Lewandowski, Prince Philip, Alexandre Marcireau +3
Standard dynamic vision sensors approximate retinal processing by detecting temporal contrast changes, offering high speed and high dynamic range. In this work, we explore whether…
3D-Image Reconstruction using MIMO-SAR FMCW Radar
Ayush Jha, Dhanireddy Chandrika, Chandra Sekhar Seelamantula +1
With the advancement of millimeter-wave radar technology, Synthetic Aperture Radar (SAR) imaging at millimeter-wave frequencies has gained significant attention in both academic re…
EventSSEG: Event-driven Self-Supervised Segmentation with Probabilistic Attention
Lakshmi Annamalai, Chetan Singh Thakur
Road segmentation is pivotal for autonomous vehicles, yet achieving low latency and low compute solutions using frame based cameras remains a challenge. Event cameras offer a promi…
HOMI: Ultra-Fast EdgeAI platform for Event Cameras
Shankaranarayanan H, Satyapreet Singh Yadav, Adithya Krishna +3
Event cameras offer significant advantages for edge robotics applications due to their asynchronous operation and sparse, event-driven output, making them well-suited for tasks req…
When Routers, Switches and Interconnects Compute: A processing-in-interconnect Paradigm for Scalable Neuromorphic AI
Madhuvanthi Srivatsav, Chiranjib Bhattacharyya, Shantanu Chakrabartty +1
Routing, switching, and the interconnect fabric are essential components in implementing large-scale neuromorphic computing architectures. While this fabric plays only a supporting…
Higher-Order Neuromorphic Ising Machines -- Autoencoders and Fowler-Nordheim Annealers are all you need for Scalability
Faiek Ahsan, Saptarshi Maiti, Zihao Chen +8
We report a higher-order neuromorphic Ising machine that exhibits superior scalability compared to architectures based on quadratization, while also achieving state-of-the-art qual…
Neural Signal Compression using RAMAN tinyML Accelerator for BCI Applications
Adithya Krishna, Sohan Debnath, Madhuvanthi Srivatsav +3
High-quality, multi-channel neural recording is indispensable for neuroscience research and clinical applications. Large-scale brain recordings often produce vast amounts of data t…
Enhancing Celestial Imaging: High Dynamic Range with Neuromorphic Cameras
Satyapreet Singh Yadav, Nirupam Roy, Chetan Singh Thakur
Conventional frame-based cameras often struggle with limited dynamic range, leading to saturation and loss of detail when capturing scenes with significant brightness variations. N…
Neuromorphic Cameras in Astronomy: Unveiling the Future of Celestial Imaging Beyond Conventional Limits
Satyapreet Singh Yadav, Bikram Pradhan, Kenil Rajendrabhai Ajudiya +4
To deepen our understanding of optical astronomy, we must advance imaging technology to overcome conventional frame-based cameras' limited dynamic range and temporal resolution. Ou…
Neuromorphic Retina: An FPGA-based Emulator
Prince Philip, Pallab Kumar Nath, Kapil Jainwal +2
Implementing accurate models of the retina is a challenging task, particularly in the context of creating visual prosthetics and devices. Notwithstanding the presence of diverse ar…
KALAM: toolKit for Automating high-Level synthesis of Analog computing systeMs
Ankita Nandi, Krishil Gandhi, Mahendra Pratap Singh +2
Diverse computing paradigms have emerged to meet the growing needs for intelligent energy-efficient systems. The Margin Propagation (MP) framework, being one such initiative in the…
Low-latency machine learning FPGA accelerator for multi-qubit-state discrimination
Pradeep Kumar Gautam, Shantharam Kalipatnapu, Shankaranarayanan H +4
Measuring a qubit state is a fundamental yet error-prone operation in quantum computing. These errors can arise from various sources, such as crosstalk, spontaneous state transitio…
Margin Propagation based XOR-SAT Solvers for Decoding of LDPC Codes
Ankita Nandi, Shantanu Chakrabartty, Chetan Singh Thakur
Decoding of Low-Density Parity Check (LDPC) codes can be viewed as a special case of XOR-SAT problems, for which low-computational complexity bit-flipping algorithms have been prop…
EventF2S: Asynchronous and Sparse Spiking AER Framework using Neuromorphic-Friendly Algorithm
Lakshmi Annamalai, Chetan Singh Thakur
Bio-inspired Address Event Representation (AER) sensors have attracted significant popularity owing to their low power consumption, high sparsity, and high temporal resolution. Spi…
RAMAN: A Re-configurable and Sparse tinyML Accelerator for Inference on Edge
Adithya Krishna, Srikanth Rohit Nudurupati, Chandana D G +4
Deep Neural Network (DNN) based inference at the edge is challenging as these compute and data-intensive algorithms need to be implemented at low cost and low power while meeting t…
Neuromorphic Computing with AER using Time-to-Event-Margin Propagation
Madhuvanthi Srivatsav R, Shantanu Chakrabartty, Chetan Singh Thakur
Address-Event-Representation (AER) is a spike-routing protocol that allows the scaling of neuromorphic and spiking neural network (SNN) architectures to a size that is comparable t…
Multiplierless In-filter Computing for tinyML Platforms
Abhishek Ramdas Nair, Pallab Kumar Nath, Shantanu Chakrabartty +1
Wildlife conservation using continuous monitoring of environmental factors and biomedical classification, which generate a vast amount of sensor data, is a challenge due to limited…
Process, Bias and Temperature Scalable CMOS Analog Computing Circuits for Machine Learning
Pratik Kumar, Ankita Nandi, Shantanu Chakrabartty +1
Analog computing is attractive compared to digital computing due to its potential for achieving higher computational density and higher energy efficiency. However, unlike digital c…
SQ-CARS: A Scalable Quantum Control and Readout System
Ujjawal Singhal, Shantharam Kalipatnapu, Pradeep Kumar Gautam +5
Qubits are the basic building blocks of a quantum processor which require electromagnetic pulses in giga hertz frequency range and latency in nanoseconds for control and readout. I…
Bias-Scalable Near-Memory CMOS Analog Processor for Machine Learning
Pratik Kumar, Ankita Nandi, Shantanu Chakrabartty +1
Bias-scalable analog computing is attractive for implementing machine learning (ML) processors with distinct power-performance specifications. For instance, ML implementations for…
In-filter Computing For Designing Ultra-light Acoustic Pattern Recognizers
Abhishek Ramdas Nair, Shantanu Chakrabartty, Chetan Singh Thakur
We present a novel in-filter computing framework that can be used for designing ultra-light acoustic classifiers for use in smart internet-of-things (IoTs). Unlike a conventional a…
Multiplierless MP-Kernel Machine For Energy-efficient Edge Devices
Abhishek Ramdas Nair, Pallab Kumar Nath, Shantanu Chakrabartty +1
We present a novel framework for designing multiplierless kernel machines that can be used on resource-constrained platforms like intelligent edge devices. The framework uses a pie…
Event-LSTM: An Unsupervised and Asynchronous Learning-based Representation for Event-based Data
Lakshmi Annamalai, Vignesh Ramanathan, Chetan Singh Thakur
Event cameras are activity-driven bio-inspired vision sensors, thereby resulting in advantages such as sparsity,high temporal resolution, low latency, and power consumption. Given…