Dr. Varsha Atul Shukre

Profile

Dr. Varsha Atul Shukre is committed to a student-centric and experiential teaching philosophy that integrates theoretical knowledge with practical applications in data science and emerging technologies. Her motivation lies in inspiring innovation, analytical thinking, and ethical responsibility among learners. With extensive academic, research, and leadership experience, she actively contributes to curriculum development, interdisciplinary learning, and student mentorship. As a Program Head of B.Sc Data Science and Big Data Analytics program at MIT-WPU, she aligns her efforts with the university’s vision by fostering an inclusive, industry-relevant learning environment that prepares students to become skilled professionals and responsible contributors to society.

Educational Qualifications: M.Sc. NET Ph.D. (Electronics) from Savitribai Phule Pune University.

Areas of Expertise: Embedded System Design, Optoelectronics, Internet of Things, Machine Learning

Teaching Experience: 13 Years

Industry / Research Experience: 1 Year

Publications and Research Work:

Design and Development of Colorimetry-Based Optical Soil pH Meter (2025) Developed an optical soil pH measurement system using colorimetry techniques to enable accurate and rapid soil health assessment for precision agriculture. Published in Grenze International Journal of Engineering & Technology (GIJET).

AI-Based Data-Centric Machine Learning Framework for IoT Analytics in Precision Agriculture(2025) Proposed an AI-driven machine learning framework integrated with IoT for high-performance agricultural analytics, improving decision-making in precision farming. Published in Acta Scientiae (Q2 Journal).

Multispectral Sensor with Machine Learning for Tomato Classification (2026) Designed a multispectral sensing system combined with CIE Tristimulus colorimetry and machine learning to classify organic and non-organic tomatoes, published in Organic Agriculture.

Soil Health Analysis and Nutrient Prediction Using Machine Learning (2023) Developed a machine learning-based system for automatic prediction of soil macro- and micronutrients, presented at the International Conference on Information Science and Applications (Springer).

Patents in Optical Sensing and Spectral Analysis (2023–2025) Design Patent (2023): Portable device for holding samples under test (Indian Design Patent No. 388967-001). Patent Application (2025): Compact Wireless Spectral Sensor System with Real-Time Color and Ambient Analysis for advanced sensing applications.

Subjects Taught: Digital Electronics, Embedded System Design, Microprocessor, Computer Organization, Data Science Fundamentals etc