Mathematics Webinar | Deep Neural Networks and their Future Direction
26 Sep 2024, 08:40 PM (EST)
Deep Learning, Artificial Intelligence, Optimization, Computer Vision, Reinforcement Learning, Generative Adversarial Network, Meta Heuristic
Welcome from the Chair
We provide an MDPI forum for researchers to discuss today’s research trends. The rapid advancements in artificial intelligence, especially in the past few decades, have profoundly impacted our lives, businesses, and industries. Among these advancements, ChatGPT and other large language models have become particularly influential. This MDPI webinar aims to explore these cutting-edge developments in AI, with a special focus on deep learning methodologies.
We are honored to invite three distinguished researchers, each of whom has made significant contributions to the field. Their presentations will cover the following critical topics: The optimization of deep learning; Reinforcement learning; Generative adversarial networks (GANs).
Join us to gain insights into the latest progress in computer science and to discuss how these innovative technologies are shaping our world today.
Date: 26 September 2024 at 8:40 pm EST | 27 September 2024 at 9:40 am CST Asia
Webinar ID: 814 7573 4914
Webinar Secretariat: journal.webinar@mdpi.com
Event Chair
Junzo Watada (Life Senior Member, IEEE) was born in 1945. He received B.Sc. and M.Sc. degrees in electrical engineering from Osaka City University (now Osaka Metropolitan University), Osaka, Japan, and his Ph.D. degree from Osaka Prefecture University (now Osaka Metropolitan University), Sakai, Japan, in 1983. Until March 2016, when he retired, he was a Professor in management engineering, knowledge engineering, and soft computing with the Graduate School of Information, Production, and Systems, Waseda University, Kitakyushu, Japan. He is currently a Professor Emeritus of Waseda University, and has been since 2016. He has also been a Full Professor with the Department of Computer and Information Sciences, Universiti Teknologi Petronas, Malaysia, since 2016. His research interests include deep learning, image processing, big data analytics, and soft computing. He is a Life Fellow of the Japan Society for Fuzzy Theory and Intelligent Informatics and the Bio-Medical Fuzzy System Association. He has also been the President of the Forum of Interdisciplinary Mathematics, based in India, since 2019, and of the International Society of Management Engineers since 2003.
Keynote Speakers
Department of Computer Science, The University of Memphis, TN, USA
Generative Adversarial Networks
Arunava Roy received his Ph.D. degree from the Department of Applied Mathematics, Indian School of Mines, Dhanbad. He is currently a Research Assistant Professor with The University of Memphis, TN, USA. Previously, he was a Researcher in the Department of Computer Science at Universiti Teknologi Petronas, Malaysia, and in the Department of Industrial and Systems Engineering at the National University of Singapore, Singapore. Prior to this, he was a Post-doctoral Fellow in the Department of Computer Science at The University of Memphis. His research interests include web software reliability, cyber security, algorithm design and analysis, data structure, and statistical and mathematical modeling.
Lebuhraya Ipoh-Lumut Teronoh Perak, Universiti Teknologi Petronas, Malaysia
Reinforcement Learning in Computer Vision: Innovations and Future Directions
Usman Ahmad Usmani was born in Aligarh, India, in April 1993. He is currently pursuing his Ph.D. degree in computer science at Univeriti Teknologi Petronas, Malaysia. He worked as a Research Assistant with IIT Kanpur and as a Researcher at Massey University, New Zealand. He has built up a social network named Zamber that has been published in around 14 national newspapers. His research interests include artificial intelligence, computer vision, computer security, wearable sensors, and cloud computing.
Computer and Information Sciences Department, Universiti Technologi PETRONAS, Seri Iskandar, Malaysia
Overview of Meta-Heuristic Approach for Optimization of Deep Learning Neural Network
Pradeep S. Naulia received his master’s degree in finance with a specialization in quantitative finance. He is currently pursuing his Ph.D. degree at the Universiti Teknologi Petronas. He has been researching deep learning optimization using metaheuristic and fuzzy methods. In the industry, he has more than 15 years of experience as a data science leader in international arenas such as the USA, China, Malaysia, and Singapore. His research interests include video analytics using deep learning and algorithm design and analysis.
Webinar Recording
The webinar was hosted via Zoom and required registration to attend. The full recording can be found below. In order to learn about future webinars, you can sign up to our newsletter by clicking “Subscribe” at the top of the page.
Program
Speaker/Presentation |
Time in EST |
Time in CST Asia |
Prof. Dr. Junzo Watada |
08:40pm - 08:50pm |
09:40am - 09:50am |
Dr. Arunava Roy |
08:50pm - 09:15pm |
09:50am - 10:15am |
Mr. Usman M Usmani |
09:15pm - 09:40pm |
10:15am - 10:40am |
Mr. Pradeep Naulia |
09:40pm - 10:05pm |
10:40am - 11:05am |
Q&A |
10:05pm - 10:30pm |
11:05am - 11:30am |
Prof. Dr. Junzo Watada |
10:30pm - 10:40pm |
11:30am - 11:40am |
Relevant Specials Issues
"Neural Networks and Their Applications"
Special Issue Editor: Prof. Dr. Mario Muñoz Organero
Manuscript submission deadline: 30 November 2024
"Advances in Fuzzy Logic and Artificial Neural Networks"
Special Issue Editor: Prof. Dr. Francisco Rodrigues Lima Junior
Manuscript submission deadline: 30 November 2024
Special Issue Editors: Dr. Huakun Huang, Dr. Chunhua Su and Dr. Zhuotao Lian
Manuscript submission deadline: 1 March 2025
"Deep Neural Networks: Theory, Algorithms and Applications"
Special Issue Editors: Prof. Dr. Osslan Osiris Vergara Villegas, Prof. Dr. Vianey Guadalupe Cruz Sánchez
and Prof. Dr. Vicente García
Manuscript submission deadline: 31 March 2025