**About the Editors**

#### **Anwaar Ulhaq**

Dr Anwaar Ulhaq is serving as a senior lecturer and deputy leader, Machine Vision and Digital Health Research in the School of Computing, Mathematics and Engineering, Charles Sturt University, Australia. Anwaar holds a PhD (Artificial Intelligence) from Monash University, Australia. He has completed professional education in machine learning and artificial intelligence from the Massachusetts Institute of Technology (MIT). He has extensive teaching and research experience from reputed Australian universities, including Victoria University, Swinburne University of Technology, and Central Queensland University. He has also worked as a research fellow at the Institute for Sustainable Industries and Liveable Cities, Victoria University, Australia. His research interests include artificial creativity, deep learning, data analytics, and computer vision. He has published more than 60 peer-reviewed papers in reputed journals and conferences.

#### **Douglas Pinto Sampaio Gomes**

Dr. Douglas has a Bachelor's, Master's (USP—-Brazil), and Doctorate (Victoria University— Australia) in Electrical Engineering. Their past works involved applications in power distribution system protection such as optimization techniques for the deployment of monitoring devices and the application of machine learning for signal classification of faults. Dr. Douglas is published and has served as a reviewer in journals such as the *IEEE Transactions on Power Delivery* and *IEEE Transactions on Instrumentation and Measurement*. Their current works focus further on signal processing and machine learning with applications related to the fields of image classification, power system protection, and powerline communications. Recent papers contemplate the use of Deep Learning for tasks such as detecting and segmentation in medical and plant images, as well as the study of high-impedance faults in power distribution systems. At present, Dr. Douglas is employed as a Research Officer at Victoria University, Melbourne, working on building real-time devices for the detection of power system faults leading to fire ignition in vegetation. Building and deploying systems lead to experiences in developing hardware and software such as analog interfaces, signal processing in FPGAs, real-time services in digital signal processors (DSPs), and applications in microprocessors (ARM). Dr. Douglas's interests for collaboration remain in leveraging and deploying machine learning and signal processing solutions to devices addressing practical and impactful problems.
