Raveendra Pilli | Image Processing | Best Researcher Award Posted on 01/02/202501/02/2025 by sciencefather Mr. Raveendra Pilli | Image Processing | Best Researcher Award He mentored B.Tech. projects focused on the early detection of Alzheimer’s Disease. One project involved utilizing multi-modality neuroimaging techniques, where MRI and PET images were collected from the OASIS database, preprocessed, and robust features were extracted for classification. MATLAB and the SPM-12 toolbox were used for this task. Another project focused on the early detection of Alzheimer’s Disease using deep learning networks, where an MRI dataset from the ADNI database was collected, preprocessed, and the performance was compared with baseline algorithms. For this project, he used MATLAB and Python. NIT-Silchar, India Profile Googlescholar linkedin Education A dedicated research scholar with a Ph.D. in Electronics and Communication Engineering from the National Institute of Technology Silchar (Thesis Submitted, CGPA 9.0), specializing in brain age prediction and early detection of neurological disorders using neuroimaging modalities. With extensive teaching experience, a strong passion for research, and a proven ability to develop engaging curricula, deliver effective lectures, and guide students toward academic success, I am committed to contributing to the field through research, publications, and presentations. My academic journey includes an M.Tech. from JNTU Kakinada (76.00%, 2011) and a B.Tech. from JNTU Hyderabad (65.00%, 2007), along with a strong foundational background in science, having completed 10+2 (MPC) with 89.00% in 2003 and SSC with 78.00% in 2001. Work experience He worked as a Junior Research Fellow at the National Institute of Technology, Silchar, Assam, from July 2021 to June 2023, where he assisted professors with course delivery for Basic Electronics, conducted laboratory sessions, graded assignments, and provided office hours for student support. From July 2023 to December 2024, he served as a Senior Research Fellow at the same institute, taking on additional responsibilities, including mentoring B.Tech. projects and assisting with Digital Signal Processing laboratory duties. Prior to his research roles, he was an Assistant Professor at SRK College of Engineering and Technology, Vijayawada, Andhra Pradesh, where he taught courses such as Networks Theory, Digital Signal Processing, RVSP, SS, and LICA. He utilized innovative teaching methods, including active learning techniques, to enhance student engagement and learning outcomes. He also mentored undergraduate research projects in image processing and received positive student evaluations for his teaching effectiveness. Publication Multimodal neuroimaging based Alzheimer’s disease diagnosis using evolutionary RVFL classifier T Goel, R Sharma, M Tanveer, PN Suganthan, K Maji, R Pilli IEEE Journal of Biomedical and Health Informatics Association of white matter volume with brain age classification using deep learning network and region wise analysis R Pilli, T Goel, R Murugan, M Tanveer Engineering Applications of Artificial Intelligence 125, 106596 Kernel Ridge Regression-based Randomized Network for Brain Age Classification and Estimation R Pilli, T Goel, R Murugan, M Tanveer, PN Suganthan IEEE Transactions on Cognitive and Developmental Systems Investigating White Matter Abnormalities Associated with Schizophrenia Using Deep Learning Model and Voxel-Based Morphometry T Goel, SA Varaprasad, M Tanveer, R Pilli Brain Sciences 13 (2), 267 Brain Age Estimation of Alzheimer’s and Parkinson’s Affected Individuals Using Self-Attention Based Convolutional Neural Network R Pilli, T Goel, R Murugan, M Tanveer International Conference on Pattern Recognition, 81-96 Brain Age Estimation Using Universum Learning-Based Kernel Random Vector Functional Link Regression Network R Pilli, T Goel, R Murugan, M Tanveer Cognitive Computation 16 (6), 3186-3199
Mr. Raveendra Pilli | Image Processing | Best Researcher Award He mentored B.Tech. projects focused on the early detection of Alzheimer’s Disease. One project involved utilizing multi-modality neuroimaging techniques, where MRI and PET images were collected from the OASIS database, preprocessed, and robust features were extracted for classification. MATLAB and the SPM-12 toolbox were used for this task. Another project focused on the early detection of Alzheimer’s Disease using deep learning networks, where an MRI dataset from the ADNI database was collected, preprocessed, and the performance was compared with baseline algorithms. For this project, he used MATLAB and Python. NIT-Silchar, India Profile Googlescholar linkedin Education A dedicated research scholar with a Ph.D. in Electronics and Communication Engineering from the National Institute of Technology Silchar (Thesis Submitted, CGPA 9.0), specializing in brain age prediction and early detection of neurological disorders using neuroimaging modalities. With extensive teaching experience, a strong passion for research, and a proven ability to develop engaging curricula, deliver effective lectures, and guide students toward academic success, I am committed to contributing to the field through research, publications, and presentations. My academic journey includes an M.Tech. from JNTU Kakinada (76.00%, 2011) and a B.Tech. from JNTU Hyderabad (65.00%, 2007), along with a strong foundational background in science, having completed 10+2 (MPC) with 89.00% in 2003 and SSC with 78.00% in 2001. Work experience He worked as a Junior Research Fellow at the National Institute of Technology, Silchar, Assam, from July 2021 to June 2023, where he assisted professors with course delivery for Basic Electronics, conducted laboratory sessions, graded assignments, and provided office hours for student support. From July 2023 to December 2024, he served as a Senior Research Fellow at the same institute, taking on additional responsibilities, including mentoring B.Tech. projects and assisting with Digital Signal Processing laboratory duties. Prior to his research roles, he was an Assistant Professor at SRK College of Engineering and Technology, Vijayawada, Andhra Pradesh, where he taught courses such as Networks Theory, Digital Signal Processing, RVSP, SS, and LICA. He utilized innovative teaching methods, including active learning techniques, to enhance student engagement and learning outcomes. He also mentored undergraduate research projects in image processing and received positive student evaluations for his teaching effectiveness. Publication Multimodal neuroimaging based Alzheimer’s disease diagnosis using evolutionary RVFL classifier T Goel, R Sharma, M Tanveer, PN Suganthan, K Maji, R Pilli IEEE Journal of Biomedical and Health Informatics Association of white matter volume with brain age classification using deep learning network and region wise analysis R Pilli, T Goel, R Murugan, M Tanveer Engineering Applications of Artificial Intelligence 125, 106596 Kernel Ridge Regression-based Randomized Network for Brain Age Classification and Estimation R Pilli, T Goel, R Murugan, M Tanveer, PN Suganthan IEEE Transactions on Cognitive and Developmental Systems Investigating White Matter Abnormalities Associated with Schizophrenia Using Deep Learning Model and Voxel-Based Morphometry T Goel, SA Varaprasad, M Tanveer, R Pilli Brain Sciences 13 (2), 267 Brain Age Estimation of Alzheimer’s and Parkinson’s Affected Individuals Using Self-Attention Based Convolutional Neural Network R Pilli, T Goel, R Murugan, M Tanveer International Conference on Pattern Recognition, 81-96 Brain Age Estimation Using Universum Learning-Based Kernel Random Vector Functional Link Regression Network R Pilli, T Goel, R Murugan, M Tanveer Cognitive Computation 16 (6), 3186-3199