Dr KALA K U | AI in Agriculture | Outstanding Scientist Award
ASSISTANT PROFESSOR AT JAIN UNIVERSITY, INDIA
Dr. Kala K U is a dedicated and experienced college professor and researcher specializing in computer science and artificial intelligence. With a PhD in Computer Science and Engineering from Pondicherry University, India, and over four years of teaching experience, Dr. Kala has made significant contributions to the field of deep learning and machine learning.
Education:
PhD in Computer Science and Engineering, Pondicherry University, India (2017-2021). Master of Computer Applications, University of Calicut, Kerala, India (2009-2012). Bachelor of Information Technology, University of Calicut, Kerala, India (2005-2008)
Research Contributions:
Proposed a 2D-GRU model for individual attention to every context. Developed DTW based 2D-GRU model for solving temporal pattern matching problem. Introduced Multi-Gated GRU (M-GRU) model for modeling the effect of each category of contexts individually. Proposed a Two Phase-Attention mechanism for incorporating user intentions. Utilized bidirectional training approach for considering both past and future contexts.
Awards and Achievements:
Best Researcher Award, Global Awards on Artificial Intelligence and Robotics (AIR2022). Best Presenter Award, International Conference on Emerging Smart Computing and Informatics (ICESCI 2020)
Experience:
Assistant Professor, University Institute of Engineering and Technology, Guru Nanak University, Telangana, India. Assistant Professor, School of Computer Applications, Lovely Professional University, Punjab, India. Junior Research Fellow, Department of Computer Science, Pondicherry University, Puducherry, India. Assistant Professor on Contract, Department of Computer Applications, Sree Keralavarma College, Thrissur, Kerala, India. Assistant Professor, Department of Master of Computer Applications, Institute of Management and Technology, Thrissur, Kerala, India.
Research Focus: AI in Agriculture
Specializes in AI in Agriculture, focusing on developing advanced algorithms and deep learning models for analyzing agricultural data to enhance crop yield, disease detection, and pest management.