Keynote Speakers

Prof. Jitender Kumar Chhabra

Computer Engineering Department, National Institute of Technology, India

Research Area：SOFTWARE ENGINEERING, SOFT COMPUTING, AI & ML for S/w Engg, DATA CLUSTERING

Brief introduction: Dr.Jitender Kumar Chhabra, Professor, Department of Computer Engineering, National Institute of Technology, Kurukshetra INDIA, has been working in the area of software engineering, soft computing and data clustering for the last 25 years and has published more than 160 papers in reputed journals and conferences. He has also got 4 patents granted, 5 patents published and 6 copyrights to his credit. He has guided 6 PhDs and 4 are in progress. He has been invited to present his research work in more than 10 countries. He is a reviewer for many reputed journals like IEEE Transactions, ACM Transactions, Applied Soft Computing, ESWA, NCAA and many other reputed journals of IEEE, Sciencedirect, Springer, Wiley etc. He has delivered more than 25 keynote addresses, chaired more than 30 sessions in reputed international conferences and workshops and delivered more than 50 expert talks at various Universities and Institutes. He has also completed a research project for Government of India in the area of secure storage.
Prof. Chhabra has always been a topper throughout his career. He completed his B Tech as 2nd Topper and M Tech as Gold Medallist, both in Computer Engineering and completed his PhD in the area of Software Engineering. He has worked in collaboration with many multinational IT companies like IBM, Hewlett-Packard (HP) and Tata Consultancy Services (TCS). He has also authored three international books. He is the first recipient of the Best Teacher Award of NIT Kurukshetra. In addition, he has been awarded with many recognitions like Sir Isaac Newton Scientific Award, Best Educator Award, Bharat Vikas Award, Outstanding Educational Achievement, 21st Century Award for Achievement, Outstanding Intellectual of 21stCentury etc.

Speech Title: Efficient Software Fault Prediction Using Intelligent Feature-Modelling and Computing

Abstract: The IT Industry is one of the fastest growing sectors in the world and most of the work of the IT companies are towards accurate software development and fast maintenance subsequently. Ever growing need for automation and the increasing complexity of multi-disciplinary systems have increased the focus of the IT Industry toward producing good quality software. Identification of fault-prone components can be extremely useful to ensure the quality of the software and thus software fault prediction (SFP) is a promising area for researchers as well as developers. SFP is primarily done by identifying those software characteristics that can lead to fault-proneness. Such characteristics and data need to be captured as well as modeled efficiently, instead of using datasets as a black box. Similarly, intelligent pre-processing and computing over the applicable features can help in getting highly accurate predictions. Various soft computing and machine learning techniques are being used in the literature for predicting faulty software components. Such components can be given more attention during testing as well as the maintenance phase, and thus a better quality product can be developed. This keynote address will provide insight into the intelligent modeling of the features followed by computing using Artificial Intelligence and Machine Learning, to predict fault-prone components of software. It is worth mentioning that the techniques discussed in the talk can be highly useful for predictions in different engineering and analytical models, as proper data modeling and suitable processing as per feature characteristics are keys to success for a prediction model

A.Prof. Cui Wei

School of Shipping Economics and Management/Dalian Maritime University, China

Introduction: Cui Wei, post doctoral fellow of Wuhan University Business Administration Mobile Station, associate professor of the School of Shipping Economics and Management of Dalian Maritime University, review expert of the Ministry of Education funded projects, review expert of the Ministry of Education's Degree and Graduate Education Development Center, decision consulting expert of the social science think tank of the Liaoning Provincial Party Committee, expert on the "Internet plus" direction of the Dalian municipal government think tank, information review expert of the Liaoning Provincial Department of Education, special researcher of Dalian Social Science Union, review expert of Dalian science and technology and financial projects.

Speech Title: The governance value of data assets throughout their entire lifecycle

Abstract: We will discuss the value of data and its governance system, including the current challenges of data ownership and application, discussing the value of data from the perspective of business needs, defining business models with data, and reconstructing business systems.