讲座内容：Unlocking the Power of Deep Sequence Modeling: Advancements in Temporal Data Analysis and Prediction （解锁深度序列建模的力量：时间序列数据分析与预测的最新进展）
讲座人：Hamido Fujita教授
讲座时间：11月12日 14:00-16:00
腾讯会议：409-8117-7679
Abstract：
In the domain of artificial intelligence, deep learning techniques have made remarkable progress, particularly in sequential data tasks such as natural language processing and time-series forecasting. However, conventional deep learning models often struggle with capturing long-range dependencies and accurately modeling complex temporal relationships in sequential data. To address this challenge, Deep Sequence Modeling has emerged as an advanced approach. The core idea behind Deep Sequence Modeling is to leverage deep learning architectures specifically designed to better capture temporal dynamics and long-term dependencies in sequential data. By incorporating techniques such as recurrent neural networks (RNNs), transformers, and attention mechanisms, Deep Sequence Modeling enhances the model’s ability to understand and predict complex patterns over time. This approach not only improves the accuracy of predictions but also increases the model’s flexibility in handling a wide range of sequential tasks, offering significant improvements over traditional methods in processing sequential data. Moreover, it can efficiently adapt to various types of sequence lengths, making it suitable for tasks across different domains, from speech recognition to financial forecasting.
Short Bio：
He is Executive Chairman of i-SOMET Incorporated Association, Japan, and Distinguished Professor at Iwate Prefectural University, Japan, he is also Research Professor at University of Granada, Spain. He is Highly Cited Researcher in CrossField for the year 2019 and in Computer Science for the year 2020, 2021 and 2022, by Clarivate Analytics. He received Doctor Honoris Causa from Óbuda University, Budapest, Hungary, in 2013 and received Doctor Honoris Causa from Timisoara Technical University, Timisoara, Romania, in 2018, and a title of Honorary Professor from Óbuda University, in 2011. He is Distinguished Research Professor at the University of Granada, and Adjunct Professor with Taipei Technical University, Taiwan, Harbin Engineering University, China and others. He supervised Ph.D. students jointly with the University of Laval, Quebec City, QC, Canada; University of Technology Sydney; Oregon State University, Corvallis, OR, USA; University of Paris 1 Pantheon-Sorbonne, Paris, France; and University of Genoa, Italy. Dr. Fujita is the recipient of the Honorary Scholar Award from the University of Technology Sydney, in 2012. He was the Editor-in-Chief for Knowledge-Based Systems (Elsevier) (2005- 2019) and then Emeritus Editor of Knowledge-Based Systems in 2020~. Since 2020 he is currently the Editor-in-Chief of Applied Intelligence (Springer) and the Editor-inChief of International Journal of Healthcare Management (Taylor & Francis). He headed a number of projects including intelligent HCI, a project related to mental cloning for healthcare systems as an intelligent user interface between human-users and computers, and SCOPE project on virtual doctor systems for medical applications. He collaborated with several research projects in Europe, and recently he is collaborating in OLIMPIA project supported by Tuscany region on Therapeutic monitoring of Parkison disease. He has published more than 400 articles mainly in high impact factor journals.
