PARVATHY S. KURUP

Experienced Assistant Professor with a strong background in computer science and engineering, specializing in artificial intelligence and machine learning. Proven track record of contributing to curriculum development and delivery, ensuring students receive a comprehensive education in these cutting-edge fields. A dedicated learner, adept at quickly adapting to new technologies and environments. Possessing extensive academic knowledge and hands-on experience in machine learning, robotics, and data mining. Proficient in programming languages such as Java and skilled in utilizing Python for machine learning applications. Demonstrates excellent data analysis and interpretation abilities. Enthusiastic about providing academic advisement to students, ensuring their success in their educational journey.

• A Secure And Efficient Student Performance Prediction System Based on Blockchain and Data Mining Technologies, Dr. S. V. Annlin Jeba, Blockchain Intelligent Systems: Protocols, Applications and Approaches for Future Generation Computing, CRC Press (Taylor & Francis Group), U.S.A., https://doi.org/10.1201/9781003313441
• Analysis and Result Prediction for Indian Premier League Using Machine Learning Algorithms, Dr. S. V. Annlin Jeba, Advances in Digital Marketing in the Era of Artificial Intelligence Case Studies and Data Analysis for Business Problem Solving, CRC Press (Taylor & Francis Group), U.S.A., https://doi.org/10.1201/9781003450443
• Predicting student academic performance using a Hybrid Regression model and K-means Clustering, Proceedings of National Conference on Artificial Intelligence and Cognitive Computing, Federal Institute of Science And Technology, Angamaly
• E - Learning Platform for Autism Spectrum Disorder, Irfan Ahammed H, Merrissa Ann Thomas, International Conference on Data Science, Artificial Intelligence & Machine Learning (ICDSAIML), Mazharul Uloom College, Ambur, Tamilnadu
• Determining an Efficient Classification Algorithm to Predict Student's Future Academic Performance, RTACT 22, SBCE, National conference on Recent Trends in Advanced Computing Technologies
• Predicting Student Performance Using Hybrid Regression and Clustering: A Deep Learning Approach, RTACT 21, SBCE, National conference on Recent Trends in Advanced Computing Technologies, 978-93-5473-994-1
• FACE IMAGE SYNTHESIS, Department of Computer Science & Engineering Amal Jyothi College of Engineering, Kanjirapally, KSCSTE (Kerala State Council For Science, Technology & Environment)

• MATHEMATICAL FOUNDATION FOR MACHINE LEARNING, AICTE - ATAL SPONSORED ONLINE FACULTY DEVELOPMENT PROGRAM, 11/01/21
• Research Foundations & Perspectives of Data Science and Deep Learning, Faculty Development Program, 02/01/24, Vidya Academy of Science and Technology, Thrissur
• DATA ANALYTICS, Faculty Development Programme, 02/01/23, Department of Computer Science and Engineering, Sree Buddha College of Engineering, Pattoor
• Faculty Induction Programme, 01/01/23, IQAC, Sree Buddha College of Engineering, Pattoor
• Research and Publication Awareness, Online FDP, 02/01/24, Department of Artificial Intelligence & Machine Learning, Mahaguru Institute of Technology, Kattanam, Kayamkulam
• EMERGEINNOVATE: Empowering Faculty for Entrepreneurial Research Development, Online Faculty Entrepreneurship Development Programme (FEDP/FDP), 04/01/24, IEDC MahaguruTech in association with IIC MahaguruTech

PATENT

Air Quality Testing IoT Device

The device consists of sensors for detecting pollutants like PM 2.5, VOCs, CO2, and humidity, a micro controller for processing data, and a wireless module for IoTconnectivity. This device is particularly useful in homes, office, schools, and other indoor spaces to ensure a healthy living and working environment.

I do hereby declare that the above information are true and correct to the best of my knowledge.