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As spiking-based deep learning inference applications are increasing in embedded systems, these systems tend to integrate neuromorphic accelerators such as $\mu$Brain to improve energy efficiency. We propose a $\mu$Brain-based scalable…
With the remarkable progress that technology has made, the need for processing data near the sensors at the edge has increased dramatically. The electronic systems used in these applications must process data continuously, in real-time, and…
Biological data mainly comprises of Deoxyribonucleic acid (DNA) and protein sequences. These are the biomolecules which are present in all cells of human beings. Due to the self-replicating property of DNA, it is a key constitute of genetic…
This paper describes a new asynchronous algorithm and implementation for the problem of k-mer counting (KC), which concerns quantifying the frequency of length k substrings in a DNA sequence. This operation is common to many computational…
With conventional silicon-based computing approaching its physical and efficiency limits, biocomputing emerges as a promising alternative. This approach utilises biomaterials such as DNA and neurons as an interesting alternative to data…
Accurate genome sequencing can improve our understanding of biology and the genetic basis of disease. The standard approach for generating DNA sequences from PacBio instruments relies on HMM-based models. Here, we introduce Distilled…
A system-on-chip (SoC) photonic-electronic linear-algebra accelerator with the features of wavelength-division-multiplexing (WDM) based broadband photodetections and high-dimensional matrix-inversion operations fabricated in advanced…
DNA nanotechnology promises to provide controllable self-assembly on the nanoscale, allowing for the design of static structures, dynamic machines and computational architectures. In this article I review the state-of-the art of DNA…
In this paper, we present the design of a Deoxyribonucleic Acid (DNA) shearing system based on unique acoustic waves generated using a phased-array Fresnel Lens transducer. Four 90-degree sector-transducers are used to build a circular…
A wide range of Internet of Things (IoT) applications require powerful, energy-efficient and flexible end-nodes to acquire data from multiple sources, process and distill the sensed data through near-sensor data analytics algorithms, and…
Segmenting biomarkers in medical images is crucial for various biotech applications. Despite advances, Transformer and CNN based methods often struggle with variations in staining and morphology, limiting feature extraction. In medical…
In order to protect the security of network data, a high speed chip module for encrypting and decrypting of network data packet is designed. The chip module is oriented for internet information security SOC (System on Chip) design. During…
On-chip communication infrastructure is a central component of modern systems-on-chip (SoCs), and it continues to gain importance as the number of cores, the heterogeneity of components, and the on-chip and off-chip bandwidth continue to…
The broad energy response, low electronic read noise, and good energy resolution have made X-ray Charge-Coupled Devices (CCDs) an obvious choice for developing soft X-ray astronomical instruments over the last half century. They also come…
The need to execute Deep Neural Networks (DNNs) at low latency and low power at the edge has spurred the development of new heterogeneous Systems-on-Chips (SoCs) encapsulating a diverse set of hardware accelerators. How to optimally map a…
With recent high-throughput technology we can synthesize large heterogeneous collections of DNA structures, and also read them all out precisely in a single procedure. Can we use these tools, not only to do things faster, but also to devise…
With ever increasing research on magnetic nano systems it is shown to have great potential in the areas of magnetic storage, biosensing, magnetoresistive insulation etc. In the field of biosensing specifically Spin Valve sensors coupled…
Reference-guided DNA sequencing and alignment is an important process in computational molecular biology. The amount of DNA data grows very fast, and many new genomes are waiting to be sequenced while millions of private genomes need to be…
Convolutional Neural Networks (CNNs) exhibit remarkable performance in various machine learning tasks. As sensor-equipped Internet of Things (IoT) devices permeate into every aspect of modern life, the ability to execute CNN inference, a…
Along with the breakthrough of convolutional neural networks, learning-based segmentation has emerged in many research works. Most of them are based on supervised learning, requiring plenty of annotated data; however, to support…