68 citations · 183 across the 9 of their papers we have counts for
9 papers
Explainable machine learning to enable high-throughput electrical conductivity optimization and discovery of doped conjugated polymers
Ji Wei Yoon, Adithya Kumar, Pawan Kumar +3
The combination of high-throughput experimentation techniques and machine learning (ML) has recently ushered in a new era of accelerated material discovery, enabling the identifica…
Quantile Online Learning for Semiconductor Failure Analysis
Bangjian Zhou, Pan Jieming, Maheswari Sivan +2
With high device integration density and evolving sophisticated device structures in semiconductor chips, detecting defects becomes elusive and complex. Conventionally, machine lea…
Towards deep generation of guided wave representations for composite materials
Mahindra Rautela, J. Senthilnath, Armin Huber +1
Laminated composite materials are widely used in most fields of engineering. Wave propagation analysis plays an essential role in understanding the short-duration transient respons…
An Efficient Approach with Dynamic Multi-Swarm of UAVs for Forest Firefighting
Josy John, K. Harikumar, J. Senthilnath +1
In this paper, the Multi-Swarm Cooperative Information-driven search and Divide and Conquer mitigation control (MSCIDC) approach is proposed for faster detection and mitigation of…
Metacognitive Decision Making Framework for Multi-UAV Target Search Without Communication
J. Senthilnath, K. Harikumar, S. Suresh
This paper presents a new Metacognitive Decision Making (MDM) framework inspired by human-like metacognitive principles. The MDM framework is incorporated in unmanned aerial vehicl…
DRBM-ClustNet: A Deep Restricted Boltzmann-Kohonen Architecture for Data Clustering
J. Senthilnath, Nagaraj G, Sumanth Simha C +4
A Bayesian Deep Restricted Boltzmann-Kohonen architecture for data clustering termed as DRBM-ClustNet is proposed. This core-clustering engine consists of a Deep Restricted Boltzma…
Inverse characterization of composites using guided waves and convolutional neural networks with dual-branch feature fusion
Mahindra Rautela, Armin Huber, J. Senthilnath +1
In this work, ultrasonic guided waves and a dual-branch version of convolutional neural networks are used to solve two different but related inverse problems, i.e., finding layup s…
Delamination prediction in composite panels using unsupervised-feature learning methods with wavelet-enhanced guided wave representations
Mahindra Rautela, J. Senthilnath, Ernesto Monaco +1
With the introduction of damage tolerance-based design philosophies, the demand for reliable and robust structural health monitoring (SHM) procedures for aerospace composite struct…
Identification of Helicopter Dynamics based on Flight Data using Nature Inspired Techniques
S. N. Omkar, Dheevatsa Mudigere, J Senthilnath +1
The complexity of helicopter flight dynamics makes modeling and helicopter system identification a very difficult task. Most of the traditional techniques require a model structure…