Rate My Professor Baijnath Kaushik

Dr. Baij Nath Kaushik is Professor and Head of the School of Computer Science and Engineering at Shri Mata Vaishno Devi University (SMVDU), Katra, Jammu and Kashmir, India, a role he assumed in August 2021, having previously served as Head from July 2017 to August 2018, Associate Professor from April 2017 to April 2020, and Professor since April 2020. He possesses a Ph.D. in Computer Science and Engineering from the Indian Institute of Technology (Indian School of Mines), Dhanbad, awarded in 2016 with a thesis on performance evaluation of approximated artificial neural networks for reliability problems in complex networks; an M.Tech. in Information Technology from Guru Gobind Singh Indraprastha University, New Delhi in 2009; and a B.E. in Computer Science and Engineering from Nagpur University in 1997. Amassing over 22 years of teaching experience, his research specializations include artificial intelligence, machine learning, deep learning, data science, soft computing, computational intelligence, medical imaging, sentiment analysis, biomedical problems, disease prognosis such as COVID-19, Alzheimer’s, cancer and diabetes, handwritten script recognition for Dogra and Takri, Internet of Vehicles security, RFID authentication, intrusion detection systems, and precision agriculture.

Dr. Kaushik has supervised seven Ph.D. theses, six of which have been awarded as of 2024, covering topics like IoV security, suicidal ideation prediction, Alzheimer’s detection, anticancer drug response, and RFID authentication. He serves as Principal Investigator for the High-End Computing AI and Deep Learning Lab funded by the Jammu and Kashmir Higher Education Department (₹1.65 crore, 2021–2025) and Co-Principal Investigator for the Trans-disciplinary Research and Innovation Hub (₹1 crore). His patented innovations include "A Novel Machine Learning Based Data-driven Device for Precision Agriculture" (Patent No. 6323441) and "Digital Antibiotic Vials Auger Filling Machine" (UK Design Patent No. 6319100). Select publications encompass "A Hybrid Feature Selection and Ensemble Stacked Learning Models on Multi-Variant CVD Datasets for Effective Classification" (IEEE Access, 2024), "Machine Learning Techniques Using Deep Instinctive Encoder-Based Feature Extraction for Optimized Breast Cancer Detection" (Computers, Materials & Continua, 2024), "CTDN: An Improvised Stacked Hybrid Computational Approach for Anticancer Drug Response Prediction" (Computational Biology and Chemistry, 2023), "Performance Evaluation of Deep Dense Layer Neural Network for Diabetes Prediction" (Computers, Materials & Continua, 2023), and "Takri Touching Text Segmentation Using Statistical Approach" (Sādhanā, 2023). He has delivered over 20 invited talks on AI, machine learning, and data science at institutions including IIT Roorkee, Jammu University, and MIET Jammu. Awards include the Research Excellence Award 2023 from Vishwa Intellectual Property Conclave, Pune, alongside outstanding performance appraisals from SMVDU.