Richa Vij - Computer science and engineering - Best Researcher Award
IIT Jammu - India
👩‍🏫 ACADEMIC AND RESEARCH LEADER
Richa Vij is an Assistant Professor in the Department of Computer Science and Engineering at the Government College of Engineering and Technology, Jammu. With a focus on retinal imaging and artificial intelligence, she brings significant experience in developing innovative computational models aimed at diagnosing systemic diseases like diabetic retinopathy and Alzheimer's. Her academic contributions, both as a professor and researcher, have made her a prominent figure in the field of AI-powered medical diagnostics.
đź’» PROJECT ASSOCIATE AT IIT JAMMU
As a Project Associate-II for a DRDO project at IIT Jammu, Richa works on cutting-edge computer science projects that contribute to national development. Her role involves harnessing deep learning and AI methodologies for real-world applications, reflecting her commitment to both academic advancement and practical innovation.
đź“š PUBLISHED AUTHOR IN AI AND HEALTHCARE
Richa Vij has authored multiple impactful publications in high-profile journals such as Metabolic Brain Disease and Computers and Electrical Engineering. Her research has focused on leveraging deep learning techniques to advance the early detection of diseases like Alzheimer's and diabetic retinopathy, contributing significantly to medical imaging and AI diagnostic systems.
🔬 PIONEERING RETINAL DISEASE DIAGNOSIS
Her Ph.D. research at SMVDU, Katra, under the supervision of Dr. Sakshi Arora, centers on using hybrid deep transfer learning-based algorithms to analyze retinal images for systemic disease detection. This work aims to enhance the performance of segmentation and classification models, positioning her research at the intersection of healthcare and advanced AI technologies.
đź“Š INNOVATIVE M.TECH RESEARCH
Richa’s M.Tech dissertation focused on "Robust Human Face Tracking and Recognition in Video Frames." By developing a novel face recognition model using the AdaBoost algorithm and K-means clustering, she addressed key challenges in face recognition, such as pose variation and occlusion, further showcasing her expertise in machine learning and pattern recognition.
🧠FOCUS ON DIABETIC RETINOPATHY AND ALZHEIMER’S
Her work is particularly influential in the early diagnosis of Diabetic Retinopathy and Alzheimer’s disease through retinal imaging. By utilizing AI-based models for retinal vessel segmentation, her contributions are paving the way for improved diagnostic frameworks, with potential applications in clinical environments for early and accurate disease detection.
🌟 COMMITMENT TO AI-DRIVEN HEALTHCARE
Richa’s dedication to advancing AI-driven healthcare solutions is reflected in her ongoing research and teaching. She strives to bridge the gap between technology and healthcare by developing intelligent systems that can assist practitioners in diagnosing complex diseases, ultimately contributing to better patient outcomes and more efficient clinical workflows.
NOTABLE PUBLICATION
Title: A systematic review on diabetic retinopathy detection using deep learning techniques
Authors: R. Vij, S. Arora
Journal: Archives of Computational Methods in Engineering
Year: 2023
Title: A novel deep transfer learning based computerized diagnostic Systems for Multi-class imbalanced diabetic retinopathy severity classification
Authors: R. Vij, S. Arora
Journal: Multimedia Tools and Applications
Year: 2023
Title: Computer vision with deep learning techniques for neurodegenerative diseases analysis using neuroimaging: a survey
Authors: R. Vij, S. Arora
Journal: International Conference on Innovative Computing and Communications
Year: 2022
Title: A systematic survey of advances in retinal imaging modalities for Alzheimer’s disease diagnosis
Authors: R. Vij, S. Arora
Journal: Metabolic Brain Disease
Year: 2022
Title: A survey on various face detecting and tracking techniques in video sequences
Authors: R. Vij, B. Kaushik
Journal: 2019 International Conference on Intelligent Computing and Control Systems
Year: 2019