**About the Editors**

**Gai-Ge Wang** is an associate professor at the Ocean University of China, China. His publications have been cited over 9600 times (Google Scholar). His latest Google h-index and i10-index are 52 and 106, respectively. Fifteen and sixty-six papers are selected as Highly Cited Papers by Web of Science, and Scopus (as of October 2021), respectively. He was selected as one of "2021 Highly Cited Researchers" by Clarivate. He was selected as one of "2020 Highly Cited Chinese Researchers" in computer science and technology by Elsevier. He was selected as World's Top 2% Scientists 2020, ranked 3840 in 2019, and ranked 88,554 in career-long citation impact. One of his papers was selected as for the "100 Most Influential International Academic Papers in China". Another of his papers ranks 1 in the selection of the latest high-impact publications in computer science by Chinese researchers from Springer Nature in 2019. He is a senior member of SAISE, SCIEI, a member of IEEE, IEEE CIS, and ISMOST. He served as Editorial Advisory Board Member of *Communications in Computational and Applied Mathematics* (*CCAM*), Associate Editor of *IJCISIM*, an Editorial Board Member of *IEEE/CAA Journal of Automatica Sinica*, *Mathematics*, *IJBIC*, *Karbala Int J of Modern Science*, and the *Journal of AIS*. He served as Guest Editor for many journals including *Mathematics*, *IJBIC*, *FGCS*, *Memetic Computing* and *Operational Research*. His research interests are swarm intelligence, evolutionary computation, and big data optimization.

**Amir H. Alavi** is an Assistant Professor in the Department of Civil and Environmental Engineering, and holds a courtesy appointment in the Department of Bioengineering at the University of Pittsburgh. Prior to joining Pitt, Dr. Alavi was an Assistant Professor of Civil Engineering at the University of Missouri. Dr. Alavi is the director of the Pitt's Intelligent Structural Monitoring and Response Testing (iSMaRT) Laboratory, which focuses on integrating sensing, energy harvesting, material, and computational technologies to build a new generation of multifunctional structural health monitoring systems. Dr. Alavi's multidisciplinary research involves advancing the knowledge and technology required to create multifunctional architected material and structural systems with self-diagnostic and self-powering capabilities for a broad range of sensing and monitoring applications. His research goal is to harness the power of these technologies enhanced by engineering informatics for tackling problems in the fields of civil infrastructure, construction, aerospace, and biomedical engineering. Dr. Alavi's original and seminal contributions to developing and deploying advanced machine learning and bio-inspired computational techniques have established a road map for their broad applications in various engineering domains. Dr. Alavi has authored 8 books and nearly 200 publications in archival journals, book chapters, and conference proceedings. He has received a number of award certificates for his journal articles. He is among the Google Scholar 200 Most Cited Authors in Civil Engineering, Web of Science ESI's World Top 1% Scientific Minds in 2018, and Stanford University list of Top 1% Scientists in the World in 2020.
