Dr. Sachin Naik

Bio

Dr. Sachin A. Naik has is an accomplished academic with over 25 years of teaching experience in computer science and Applications. Currently serving as an Associate Professor at MIT World Peace University, Pune, he holds a Ph.D. in Computer Studies from Symbiosis International University, specializing in handwritten mathematical expression recognition. His research interests encompass areas like machine learning, speech recognition, mathematical expression recognition, and image processing, with multiple publications in reputed journals and international conferences. Dr. Naik has guided 2 Ph.D. candidates successfully. He has received awards for his research and has been an active resource person for workshops and academic programs.

Educational Qualifications : M.Sc. (CS), Ph.D. (CS)-Symbiosis International University, Pune.

Areas of Expertise : Data Science, Machine Learning, Pattern Recognition.

Teaching Experience : 25+ years.

Publications and Research Work

Naik, S. (2026, March). Multimodal speech emotion recognition: Deep learning approaches for vocal sentiment analysis. In AIP Conference Proceedings (Vol. 3386, No. 1, p. 020022). AIP Publishing LLC.

Naik, S., (2026, March). Sign language recognition using LSTM. In AIP Conference Proceedings (Vol. 3386, No. 1, p. 020009). AIP Publishing LLC.

Naik, S. (2026). Enhanced Prediction of Chronic Kidney Disease using XGBoost Machine Learning Model. International Journal of Statistics in Medical Research, 15, 109–120. https://doi.org/10.6000/1929-6029.2026.15.10

Naik, S. A. (2026)., Developing an automated script for detecting design pattern in software project using Python. In The Future of Business and Society (pp. 283-291). CRC Press.

S. A., Naik, S. A. (2025). Data-driven insights: exploring the influence of enterprise resource planning systems on managerial decision processes. International Journal of Business Process Integration and Management, 12(2), 179-192.

Naik, S. A. (2025). Online handwritten physics expression recognition using a CRNN-LSTM approach. Journal of Computer Science, 21(3), 263–272.

Naik, S. A. (2024). A CNN-KNN Based Recognition of Online Handwritten Symbols within Physics Expressions Using Contour-Based Bounding Box (CBBS) Segmentation Technique. Journal of Computer Science 20 (7), 783-792.

Subjects Taught : Data Analysis using Python, Principles of Deep Learning, Digital Image Processing.

Research Profiles and Links

Scopus ID : https://www.scopus.com/authid/detail.uri?authorId=56735448200

Google Scholar : https://www.scopus.com/authid/detail.uri?authorId=56735448200

ORCID : https://www.scopus.com/authid/detail.uri?authorId=56735448200