Associate Professor | GSFC University Vadodara Gujarat | India
Dr. Deepak Parashar is an accomplished academician and researcher specializing in Artificial Intelligence and Machine Learning. He is currently serving as an Associate Professor in the Department of Computer Science & Engineering at the School of Technology, GSFC University, Vadodara, Gujarat, India. With over 14 years of academic and research experience, Dr. Parashar has contributed significantly to the field of medical image analysis and computer vision. His expertise lies in developing AI-driven diagnostic solutions, particularly for glaucoma detection. Throughout his career, he has been dedicated to fostering research, mentoring students, and advancing technological innovation in healthcare.
Profile
Scopus
Education
Dr. Parashar holds a Ph.D. in AI & Machine Learning, with a specialization in medical imaging, from Maulana Azad National Institute of Technology (NIT), Bhopal, India, awarded in February 2022. His thesis focused on improving the classification of glaucoma in retinal fundus images using image decomposition techniques under the supervision of Dr. D. K. Agrawal. He completed his M.Tech. from SGSITS Indore in 2011 and earned his B.E. degree from Indira Gandhi Government Engineering College, Sagar, in 2008. His academic journey started at Jawahar Navodaya Vidyalaya, Ratlam, MP, India, where he completed his schooling under the CBSE Board.
Experience
Dr. Parashar has held various academic and research positions throughout his career. Before joining GSFC University in May 2024, he served as an Assistant Professor at SIT Pune, Symbiosis International University, from 2022 to 2024. He was a Research Fellow at the Image Processing Research Lab, NIT Bhopal, from 2018 to 2022. Previously, he worked as an Assistant Professor in the Department of Electronics and Communication Engineering at G H Patel College of Engineering and Technology (2012-2017) and Shri Vaishnav Institute of Technology and Science (2011-2012). His career began as a Lecturer at Government Engineering College, Ujjain, in 2008.
Research Interests
Dr. Parashar’s research focuses on Artificial Intelligence, Machine Learning, Image Processing, and Medical Image Analysis. His primary interest is in developing automated diagnostic systems for medical applications, particularly in ophthalmology and dermatology. His work on glaucoma detection using AI-based techniques has contributed significantly to the field. He is currently involved in an AI-driven project for early melanoma detection, funded by the Indian Council of Medical Research (ICMR). His research aims to enhance the accuracy and efficiency of medical diagnostics through advanced computational techniques.
Awards and Achievements
Dr. Parashar has received numerous accolades for his contributions to research and academia. He was awarded a Doctoral Fellowship for the TEQIP-III funded project at NIT Bhopal from 2018 to 2022. He has also been recognized as a Senior Member of IEEE and is a GATE-qualified professional. Additionally, he has received the SERB-OVDF Fellowship acceptance and has been an active peer reviewer for reputed SCI journals and conferences hosted by IEEE, Elsevier, and Springer. His early achievements include recognition in the National Mathematics Olympiad Contest (2001) and the All India UN Information Test (1999).
Publications
Dr. Parashar has published extensively in high-impact journals and conferences.
“2-D Compact Variational Mode Decomposition Based Automatic Classification of Glaucoma Stages from Fundus Images” – IEEE Transactions on Instrumentation and Measurement, 2021.
“Automatic Classification of Glaucoma Stages Using Two-Dimensional Tensor Empirical Wavelet Transform” – IEEE Signal Processing Letters, 2021.
“Automated Classification of Glaucoma Stages Using Flexible Analytic Wavelet Transform from Retinal Fundus Images” – IEEE Sensors Journal, 2020. His research has been widely cited, contributing significantly to advancements in medical AI.
Conclusion
Dr. Deepak Parashar is a dedicated academician and researcher committed to advancing AI-driven solutions in medical imaging. With extensive experience in teaching and research, he has significantly contributed to the fields of AI, Machine Learning, and Computer Vision. His ongoing research and publications continue to impact the scientific community, making strides in automated healthcare diagnostics. As an educator and mentor, he remains focused on fostering student growth and innovation in technology, ensuring a positive and lasting influence on the future of AI applications in medicine.