Dr. Neeraj Baghel
Asst. Professor, SCSET
Bennett University
(The Times Group)
Dr. Neeraj Baghel is currently affiliated with Bennett University (The Times Group) and served as a Senior Research Fellow at the Computer Vision and Biometric Lab (CVBL), IIIT Allahabad. He brings rich expertise in Computer Vision, Deep Learning, and AI-driven solutions. Previously, he worked as a Junior Research Fellow at IIIT-SriCity, where he contributed to the DRDO Young Scientist Laboratory, Chennai, developing a cutting-edge computer vision algorithm for transforming NT2DT images. In another JRF role at the Centre for Advanced Studies (CAS), he significantly contributed to the development of an intelligent stethoscope designed for early detection of cardiac and pulmonary diseases, with a strong emphasis on biomedical applications.
Dr. Baghel's research interests include Artificial Intelligence, Computer Vision, Image & Video Processing, and their practical applications across healthcare and other real-world domains. He has authored and co-authored several research publications, reviewed for leading international journals and conferences, and filed a patent for one of his innovative inventions. Through his interdisciplinary research and innovation, Dr. Neeraj Baghel continues to advance the frontiers of AI and Computer Vision in both academic and industrial contexts.
Technical Skills:
-Programming Language: Python, C#, .Net, MYSQL.
-IDE: Pycharm, Anaconda, Matlab, Visual Studio.
-Library: Tensorflow, Keras, PyTorch and OpenCV.
Research: Super-Resolution, Intelligent Stethoscope, Image Transformation, Video Summarization.
Resources: Datasets, IEEE Resources, SCIE Journals, Etc.
J1) Automatic Diagnosis of Multi-Cardiovascular Diseases from PCG Signals using DCNN, CMPB (2020) [Q1-SCI-7.027].
J2) ALSDNET: Automatic Lungs Sound Diagnosis Network from Pulmonary Signals” NCAA (2021) [Q1-SCI-5.606].
J3) 1D-FHRNet: Automatic Diagnosis of Fetal Acidosis from FHR Signals”, BSPC (2022). [Q2-SCI-5.076].
P1) Automatic Detection of Lungs Disease using ML from Respiratory Sound” IP:202011009043, Published.
Developed Intelligent Stethoscope for Early Medical Diagnosis of Heart, Lung and Prenatal Health