Assistant Professor, Department of Computer Science
International Workshop Interactive Systems & Information Society Technologies (InterSys2024) is a joint event held by BITS Pilani (Dubai Campus), ITMO University (St. Petersburg, Russia), Novosibirsk State Technical University (Novosibirsk, Russia) , Jinan Institute of Supercomputing Technology (Shandong, China), and Federal University of Paraná (UFPR, Curitiba, Brazil) on May
16-17, 2024 as a part of the International Conference Internet and Modern Society (IMS-2024). This year, we plan to have the workshop in face-to-face mode. The objective of the InterSys2024 workshop is to engage in comprehensive discussions addressing challenges and opportunities within the realm of developing interactive technologies in the digital environment. The focus is on exploring and dissecting the complexities associated with the advancement ofof advancing interactive systems across various sectors, including science, education, healthcare, business, public administration, and civil society.
Special Session Organizers
Dr. Elakkiya R
Department of Computer Science, Birla Institute of Technology & Science Pilani, Dubai Campus, Dubai, United Arab Emirates
Email: elakkiya@dubai.bits-pilani.ac.in, elaelakkiyaceg@gmail.com
Profile: Homepage | Google Scholar | ORCID
Dr. J. Angel Arul Jothi
Department of Computer Science, Birla Institute of Technology & Science Pilani, Dubai Campus,Dubai, United Arab Emirates
Email: angeljothi@dubai.bits-pilani.ac.in
Profile: Homepage | Google Scholar
About The Session
The purpose of the special session "Generative Artificial Intelligence for Text" is to provide a lively platform for the examination and debate of current developments, difficulties, and uses in the developing field of generative AI that are particularly relevant to text-based data. This session encourages scholars, practitioners, and industry experts to share ideas and contribute to the developing field of AI-driven text generation, with an emphasis on promoting collaboration and knowledge exchange. Natural language processing (NLP), the newest text generation models such as GPT and BERT, sentiment analysis, opinion mining, language translation, and the crucial elements of explainability and ethical issues in AI text creation are just a few of the many topics of interest.
Beyond theoretical considerations, the special session will include real-world applications of generative text models. The goal of the session is to present practical applications and illustrate the observable effects of AI-driven text generation in a variety of fields, from content creation to the building of sophisticated chatbots. The organizers are dedicated to establishing an inclusive environment that fosters multidisciplinary communication and cooperation as the area develops quickly. It is intended for this special session to serve as a hub for cutting-edge techniques, applications, and approaches, all aimed at collaboratively influencing the direction of AI-driven text generation.
Related Topics but not limited to:
1. Text Generation Models for Natural Language Processing (NLP) (e.g., GPT, BERT)
2. Language Translation and Multilingual Models
3. Sentiment Analysis and Opinion Mining
4. Text Generation: Explainability and Interpretability
5. Applications of Generative Text Models (e.g., chatbots, content creation)
6. Ethical Issues in AI Text Generation
Paper Submission
Manuscripts should conform to the IEEE template/format. All manuscripts to be considered for publication must be submitted by the deadline through the SETCMS, while selecting the “SSI: GenAIText” from the topic-box.
Call for Book Chapters
Green Machine Learning and Big Data for Smart Grids: Practices and Applications
A book edited by Elsevier Book Series in "Advances in Intelligent Energy Systems"
Scope of the Book:
The main goal of this book is to provide the most relevant information on bringing the green machine learning concepts using big data techniques in smart grid applications to academicians, researchers, and for those from industry who wish to know more about the solutions for complex real-time problems. The Green Machine Learning and Big Data for Smart Grids book will concentrate more on the operational aspects of smart grids and certainly the only book that will discuss the combined analytics, algorithmic and operational concerns into a coherent picture of the Smart Grid practices and applications.
This edited book aims to bring together cutting-edge research, innovative theories, practical insights, and emerging trends related to Machine Learning and Big Data for Smart Grids and Renewable Energy. We encourage contributions that offer novel perspectives, address current challenges, and provide valuable contributions to the academic and professional community.
Topics of interest include, but are not limited to:
Important Dates:
Abstract Submission: 15 August 2023
Abstract Acceptance: 30 August 2023
Full Chapter Submission: 30 October 2023
Chapter Acceptance: 15 November 2023
Final Chapter Submission: 30 November 2024
Submission:
All submissions must be original and should not have been published or under review elsewhere. Kindly submit your chapter by Email: submitmanuscript365@gmail.com With the subject line "Book Chapter for Green ML and Big Data".
Publication:
The book edited will be published by Elsevier Book Series in "Advances in Intelligent Energy Systems" and will be indexed by Scopus and offered to Web of Science and Thomson Reuters. No publication fee applicable for this call for book chapter.
Editors of the Book:
All inquiries about submissions should be emailed to elakkiya@dubai.bits-pilani.ac.in
Objectives and Scope
This special session aims to examine the revolutionary developments and ramifications of large language models (LLMs) in several research and innovation domains. Recent advances in LLMs, like GPT-3.5, have completely changed how we create, interpret, and comprehend natural language, opening up intriguing new possibilities for research, business, and society in general. This session will examine LLMs' current uses, difficulties, and possible future directions, demonstrating how they might support and improve the sessions featuring reviewed material from the leading conference.
Due to their capacity to produce writing that resembles that of a person, comprehend complicated linguistic patterns, and carry out a variety of tasks related to natural language processing, big language models have attracted much interest in recent years. Massive training data sets and cutting-edge deep learning architectures have allowed LLMs to outperform earlier benchmarks in tasks including sentiment analysis, question-answering, machine translation, and question-answering. Additionally, they have the potential to advance cutting-edge study and innovation in a variety of fields.
Subtopics
The topics include, but are not limited to:
Paper publications
Important Dates