Assoc. Prof. Lan Lin
Ball State University, USA
Dr. Lan Lin is an Associate Professor of Computer Science at Ball State University, USA. She earned her Ph.D. in Computer Science from the University of Tennessee at Knoxville. Prior to joining Ball State, she worked as a Research Scientist in the Software Quality Research Laboratory at the University of Tennessee. Her research has focused on rigorous software specification and testing methodologies, and has been generously funded by Lockheed Martin, Northrop Grumman, Rockwell Collins, Air Force Research Laboratory, and Ontario Systems (all through the S2ERC - NSF Security and Software Engineering Research Center), and also by NSF. Her S2ERC-funded project titled “Towards Scalable Modeling for Rigorous Software Specification and Testing” was selected to be published in the 2016 NSF Industry & University Cooperative Research Center Technological Breakthrough Compendium. Dr. Lin was appointed to be the S2ERC Director in July 2020 and served until the Center concluded in April 2022. She served as the Program Co-Chair for the 33rd International Conference on Software Engineering and Knowledge Engineering (SEKE 2021) and as the General Co-Chair for the 34th International Conference on Software Engineering and Knowledge Engineering (SEKE 2022). She also served on an NSF site visit team in 2022.
Assoc. Prof. Minoru Kuribayashi
Okayama University, Japan
Minoru Kuribayashi received B.E., M.E., and D.E degrees from Kobe University, Japan, in 1999, 2001, and 2004. He was a Research Associate and an Assistant Professor at Kobe University from 2002 to 2007 and from 2007 to 2015, respectively. Since 2015, he has been an Associate Professor in the Graduate School of Natural Science and Technology, Okayama University. His research interests include multimedia security, digital watermarking, cryptography, and coding theory. He serves as an associate editor of IEEE Signal Processing Letters, Journal of Information Security and Applications and IEICE. He is a chair of APSIPA TC of Multimedia Security and Forensics, and a TC member of IEEE SPS Information Forensics and Security. He received the Young Professionals Award from IEEE Kansai Section in 2014, and the Best Paper Award from IWDW 2015 and 2019. He is a senior member of IEEE and IEICE.
Assoc. Prof. Hovannes Kulhandjian
California State University, Fresno, USA
Hovannes Kulhandjian (Senior Member, IEEE) received the M.S. and Ph.D. degrees in electrical engineering from The State University of New York at Buffalo, Buffalo, NY, USA, in 2010 and 2014, respectively. From December 2014 to July 2015, he was an Associate Research Engineer with the Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA. He is currently an Associate Professor with the Department of Electrical and Computer Engineering, California State University, Fresno, Fresno, CA, USA. His current research interests include wireless communications and networking, with applications to underwater acoustic communications, visible light communications, and applied machine learning. He actively serves as a member of the Technical Program Committee for IEEE and ACM conferences, such as IEEE GLOBECOM, ICC, PIMRC, and ACM WUWNet, among others. He has served as a Guest Editor for IEEE ACCESS and MDPI Journals.
Speech Title: AI based Bridge and Road Inspection Framework using Drones
Abstract: In this talk, I will focus on our ongoing work on bridge and road inspection framework we developed using advanced machine learning and drones. It is not sufficient to do inspection using cameras, we plan to utilize infrared (IR) camera along with a high resolution optical camera. The IR camera can provide more details to the interior structural damages of a bridge compared to an optical camera that is more ideal for inspecting damages on the surface of a bridge. In addition to that our drone inspection system is equipped with computer on chip that runs Machine Learning algorithms that enables autonomous driving of the drone and taking images of the bridge or the road structure whenever it detects any damages. Instead of having a person operate the drone it will self-operate and carry out the inspection process on its own using advanced AI algorithms we are developing.
Iluminada Vivien R. Domingo
Polytechnic University of the Philippines, Philippines
Iluminada Vivien R. Domingo graduated from Polytechnic University of the Philippines, Philippines in 1986 with the degree Bachelor in Business Education *Magna Cum laude, and got her Master in Business Administration (MBA), an allied course of Information Technology, from the University of Santo Tomas, Manila, Philippines in 1990 and Doctor in Business Administration degree from Polytechnic University of the Philippines, in 2004. She started her teaching career in information technology at St. Paul University of Quezon City in 1987. Dr. Domingo has attended various training programs in information technology and taught various subjects in information technology between 1987 to 1989. Dr. Domingo then transferred to teach at Polytechnic University of the Philippines, College of Computer Management and Information Technology now College of Computer and Information Sciences from 1989 to the present, 2023. She holds a permanent position as Full Professor 6 in the College of Computer and Information Sciences, Polytechnic University of the Philippines. Dr. Domingo is the faculty researcher for the Bachelor in Information Technology course of the College of Computer and Information Sciences. Dr. Domingo has published various research papers indexed in scopus.com and in Commission on Higher Education (CHED) accredited journal in 2020.
Assoc. Prof. Mohd Faizal Abdollah
University Teknikal Malaysia Melaka, Malaysia
Associate Profesor Dr Mohd Faizal Abdollah is currently a senior lecturer in University Teknikal Malaysia Melaka. The research area more focuses on network security, malware detection and network management. In cybersecurity, Dr Mohd Faizal led the sub project under CMERP project with the collaboration with Cyber Security Malaysia. This project more focuses on malware detection, eradication and mitigation. Currently, involve in developing EDR together with the Cybersecurity Malaysia. Others than that, Dr Mohd Faizal also involve in various grant sponsor by Ministry of Education, Industrial grant and University grant such as Fundamental Grant for detecting botnet activity, Transdisciplinary Grant for detecting the inside threat, ISIF grant for botnet detection using graph theory. He also teaches UTeM course such as Information Technology and IT Security, Network Management and Administration, Advanced Scalable Network and also manage to produce various conference paper and journal in cybersecurity related field.