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Dr. Dolly Das
Assistant Professor
Profile Summary
Dr. Dolly Das is an Assistant Professor in the Data Science Cluster at the School of Computer Science, UPES, Dehradun.
She holds a Ph.D. from the National Institute of Technology Silchar, where her research focused on developing deep learning-based systems using medical imaging, particularly chest X-ray images, for early detection of COVID-19.
Her expertise spans Machine Learning, Deep Learning, Medical Image Processing, and Adversarial Networks, with a strong focus on advancing healthcare diagnostics through intelligent computational techniques.
Work Experience
Dr. Dolly Das worked as a Software Engineer at Brahmaputra Innovations Private Limited, Guwahati, in 2017.
She has served as an Assistant Professor at Dibrugarh University and Bennett University, and as an Online Educator and Project Trainer at NIELIT, MeitY, Government of India.
Since June 2025, she has been serving as an Assistant Professor at UPES, contributing to teaching, research, and academic development.
Education
Ph.D., National Institute of Technology Silchar.
Research Interests
Deep Learning, Machine Learning, Medical Image Processing, Adversarial Networks.
Teaching Philosophy
Dr. Dolly Das believes in creating a supportive, inclusive, and engaging learning environment that encourages students to reach their full potential.
She integrates practical knowledge with critical thinking, enabling students to apply theoretical concepts to real-world challenges.
Her teaching approach emphasizes hands-on learning, case studies, project-based methods, and active classroom participation.
Courses Taught
Advanced Database Management System, Programming with C, Problem Solving, Cloud Computing, System Software, Information Technology, Multimedia, Software Project Management, Fundamentals of Java.
Awards and Achievements
Details to be updated.
Scholarly Activities
Dr. Dolly Das has an extensive publication record in reputed international journals and conferences in the areas of healthcare AI and machine learning.
Her research includes COVID-19 detection using chest X-ray images, diabetic retinopathy diagnosis, AI-based healthcare systems, and cybersecurity in IoT.
She has published in journals such as International Journal of Imaging Systems and Technology and Multimedia Tools and Applications, and has presented at IEEE conferences including CONIT, INCET, ASIANCON, and ICCCS.
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