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.
Prof.
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.