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Kumar Chandar S

Associate Professor / School of Business & Management · CHRIST (Deemed to be University)

https://researchid.co/kumarchandar
@christuniversity.in
43Scopus Publications
667Google Scholar Citations
11Google Scholar h-index
13Google Scholar i10-index

Research Interests

Strategic Management Artificial Intelligence Computational Finance Text Analytics in Finance HR Analytics Marketing Analytics Innovation & Creativity Soft Computing Natural Computing

Biography

Dr S. Kumar Chandar is working as an Associate Professor in School of Business & Management – CHRIST (Deemed to be University), Bangalore having 20 years in wide variety of technical, managerial and teaching roles. He completed PhD in the field of Artificial Neural Networks & PhD in Marketing Management & submitted DSc in Computer Science (Computational Finance). He has published and presented over 40 research papers (15 Scopus Indexed & 5 Web of Science Indexed) in International and National Journals in the area of Computer Science and Management. He is an AIMA certified Accredited Management Teacher in the Area of Information Technology, SMFI certified Strategic Management Teacher and completed ITIL V3 Foundation-level certificate in Service Management. He is actively involved in various professional bodies like NHRD, CSI, ISTE, AIMA and ACS.

Education

Master of Computer Applications Master of Business Administration PhD (Computer Science - Artificial Intelligence) PhD (Management)

Recent Scopus Publications

  1. Climate Change and Rainfall Variability in Goa: A Hybrid LSTM-Autoencoder based Predictive Approach
    Proceedings of the 2026 International Conference on AI Driven Smart Systems and Ubiquitous Computing Icauc 2026, 2026
  2. Enhancing Crude Oil Price Prediction with Neural Network Models
    Lecture Notes in Networks and Systems, 2026
  3. Predicting Crude Oil Futures using Feed Forward Neural Networks and Technical Indicators: A Comparative Study on WTI and Brent
    Proceedings of the 2026 International Conference on AI Driven Smart Systems and Ubiquitous Computing Icauc 2026, 2026
  4. Intelligent Analytical Framework to Improve Customer Retention in the SaaS Industry
    Smart Innovation Systems and Technologies, 2026
  5. A Machine Learning Approach to Crude Oil Price Prediction Using Support Vector Machine (SVM)
    Lecture Notes in Networks and Systems, 2026

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