Prof. KANNIMUTHU SUBRAMANIYAM
Karpagam College of Engineering, India
Title: Artificial Intelligence Approaches For Digital Manufacturing
Biography: Kannimuthu Subramanian is currently working as Professor in the Department of Computer Science and Engineering at Karpagam College of Engineering, Coimbatore, Tamil Nadu, India. He is also in In-Charge of the Center of Excellence in Algorithms. He is an IBM Certified Cybersecurity Analyst. He did Ph.D. in Computer Science and Engineering at Anna University, Chennai. He did his M.E (CSE) and B.Tech (IT) at Anna University, Chennai. He has more than 15 years of teaching and industrial experience. He is the recognized supervisor of Anna University, Chennai. Two Ph.D. candidate is completed their research under his guidance. He is now guiding 7 Ph.D. Research Scholars. He has published 50 research articles in various International Journals. He published 1 book on "Artificial Intelligence" and 3 Book Chapters (Scopus Indexed). He is acting as a mentor/consultant for DeepLearning.AI, MaxByte Technologies, and Dhanvi Info Tech, Coimbatore. He is an expert member of the AICTE Student learning Assessment Project (ASLAP). He has presented a number of papers in various National and International conferences. He has visited more than 70 Engineering colleges and delivered more than 120 Guest Lectures on various topics. He is the reviewer for 30 Journals and 3 Books. He has successfully completed the consultancy project through Industry-Institute Interaction for ZF Wind Power Antwerpen Ltd., Belgium. He has received funds from CSIR, DRDO, and ISRO to conduct workshops and seminars. He has completed more than 610 Certifications (41 Specializations and 4 Professional Certifications) in Coursera, Hackerrank, and NPTEL on various domains. He has guided a number of research-oriented as well as application-oriented projects organized by well-known companies like IBM. He is actively involved in setting up a lab for Cloud Computing, Big Data Analytics, Open Source Software, Internet Technologies, etc., His research interests include Artificial Intelligence, Data Structures, and Algorithms, Machine Learning, Big Data Analytics, and Machine Learning.
Assoc. Prof. He Chen, Hebei University of Technology, China
Title: Control Research for Underactuated Cranes with State Constraints
Abstract: Crane systems are widely used transportation tools in industrial production. However, due to the underactuated properties, less control inputs are used to dominate more degrees of freedom for cranes, which increases the control difficulty. Furthermore, since the working environment for cranes may be complex, various state constraints should be considered for the control design of cranes to ensure safety. Considering these factors, in this presentation, we propose three different kinds of control methods with state constraints to deal with different crane transportation issues. We also extend the proposed method to solve the state constraint control problem for a class of underactuated systems. Rigorous theoretical analysis and comprehensive experimental tests illustrate the proper performance of the proposed state constraint control method.
Biography: He Chen received a B.S. degree in automation and a Ph.D. degree in control science and engineering from Nankai University, Tianjin, China, in 2013 and 2018, respectively. He is currently an Associate Professor at the School of Artificial Intelligence, Hebei University of Technology, Tianjin, China. His research interests include control of underactuated systems (e.g., cranes) and motion planning of wheeled mobile robots. Dr. Chen is the recipient of the Outstanding Paper Award for the IEEE Transactions on Industrial Electronics in 2021. He serves as an Academic Editor for Mathematical Problems in Engineering and a Guest Editor for Actuators and Machines. He also serves as an Organizing Co-Chair for the 2022 7th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS 2022), a Regional Program Chair for the 2022 IEEE International Conference on Real-time Computing and Robotics (IEEE RCAR 2022), and a PC/TC member for several EI-indexed international conferences.
Research area: Underactuated systems, overhead cranes, state constraint control, trajectory planning
Assoc Prof. Chuanjun Zhao, Shanxi University of Finance and Economics, China
Title： Cross-domain sentiment classification
Abstract： Training data in a specific domain are often insufficient in the area of text sentiment classifications. Cross-domain sentiment classification (CDSC) is usually utilized to extend the application scope of transfer learning in text-based social media and effectively solve the problem of insufficient data marking in specific domains. Hence, this paper aims to propose a CDSC method via parameter transferring and attention sharing mechanism (PTASM), and the presented architecture includes the source domain network (SDN) and the target domain network (TDN). First, hierarchical attentional network with pre-training language model on training data, such as global vectors for word representation and bidirectional encoder representations from transformers (BERT), are constructed. The word and sentence levels of parameter-transferring mechanisms are introduced in the model transfer. Then, parameter transfer and fine-tuning techniques are adopted to transfer network parameters from SDN to TDN. Moreover, sentiment attention can serve as a bridge for sentiment transfer across different domains. Finally, word and sentence level attention mechanisms are introduced, and sentiment attention is shared from the two levels across domains. Extensive experiments show that the PTASM-BERT method achieves state-of-the-art results on Amazon review cross-domain datasets.
Biography: Chuanjun Zhao is an associate professor at the Shanxi University of Finance and Economics, a master tutor for computer application technology, and a member of the affective computing professional committee of the Chinese Information Society of China. His main research interests are data mining and natural language processing. He has published many papers in journals such as Information Science, Computer Speech and Language, Knowledge-based Systems, Computer Research and Development, and Journal of Software.
Research area: Data mining, artificial intelligence, natural language processing