Dr. SREEDHAR KOLLEM

Shaik, Z. B., Peddakrishna, S., & Kollem, S. (2026). “Hierarchical traffic state fusion for infrastructure assisted vehicle speed regulation of Autonomous Electric Vehicles.” International Journal of Computational Intelligence Systems (Springer, SCI-Q2, IF: 4.0). DOI: 10.1007/s44196-026-01656-7.

Vidyabharathi, D., Basha, D. K., Kollem, S., & Mohan, E. (2027). “Automatic diabetic retinopathy classification using probabilistic spiking heterogeneous dynamic graph network with hyperbolic sine optimizer.” Biomedical Signal Processing and Control, 131, 111592 (Elsevier, SCI-Q2, IF: 5.7). DOI: 10.1016/j.bspc.2026.111592.

Sanjeev, B., Deepika, G., Kollem, S., Perugu, G., Kate, C., & Rani, P. (2026). “Privacy preserving federated learning for brain tumor segmentation using multi-institutional MRI data.” Scientific Reports (Springer Nature, SCI-Q1, IF: 4.9). DOI: 10.1038/s41598-026-69042-z.

Suganya, R., Leo Joseph, L. M. I., & Kollem, S. (2026). “Advanced cell balancing strategies for scalable lithium-ion battery management in electric vehicles.” Journal of the National Science Foundation of Sri Lanka, 54(2) (National Science Foundation of Sri Lanka, SCI-Q3, IF: 0.7). DOI: 10.4038/jnsfsr.v54i2.12687.

Assudani, P. J., Anny Leema, A., Balakrishnan, P., Kollem, S., Pachlor, R., López-Linares Román, K., Oliver, I. M., Haick, H., & Bhaiyya, M. (2026). “AI-driven transfer learning for medical imaging and sensor-based healthcare.” Archives of Computational Methods in Engineering (Springer, SCI-Q1, IF: 12.9). DOI: 10.1007/s11831-026-10667-8.

Kollem, S., Peddakrishna, S., Kumar, S., & Baronia, A. (2026). “A hybrid GAN-PDE framework with diffusion-guided residual attention for MRI brain image denoising.” Computational Biology and Chemistry, 124(Pt 2), 109243 (Elsevier, SCI-Q1, IF: 3.4). DOI: 10.1016/j.compbiolchem.2026.109243.

Krishnaveni, T., & Kollem, S. (2026). “A systematic review of transformer-enhanced UNet architectures for 3D medical image segmentation: Trends, challenges, and the ATD-TᵣEEv framework.” Computational Biology and Chemistry, 124(Pt 1), 109084 (Elsevier, SCI-Q1, IF: 3.1). DOI: 10.1016/j.compbiolchem.2026.109084.

Krishnaveni, T., & Kollem, S. (2026). “A heuristic-inspired spatial ViT-based adaptive 3D efficient Unet++ module for volumetric brain tumour segmentation model with 3D brain images.” Biomedical Signal Processing and Control, 122, 110403 (Elsevier, SCI-Q2, IF: 4.9). DOI: 10.1016/j.bspc.2026.110403.

Suganya, R., Leo Joseph, L. M. I., & Kollem, S. (2026). “Evaluating lithium-ion battery characteristics under various load conditions using MATLAB/Simulink.” National Academy Science Letters (Springer, SCI-Q3, IF: 1.3). DOI: 10.1007/s40009-026-01985-3.

Ramaraju, B., Janapati, R., & Kollem, S. (2026). “An optimal feature integration with adaptive hybrid deep learning network for human brain activity interpretation during yoga and meditation using EEG signals.” Iranian Journal of Science and Technology, Transactions of Electrical Engineering (Springer, SCI-Q4, IF: 1.4). DOI: 10.1007/s40998-026-01066-7.

Chandrasekhar, N., Peddakrishna, S., & Kollem, S. (2026). “Enhancing performance evaluation and ensemble methodology for early detection of heart disease with SHAP analysis.” Evolutionary Intelligence, 19(2) (Springer, ESCI-Q3, IF: 2.6). DOI: 10.1007/s12065-026-01164-9.

Panaganti, N., & Kollem, S. (2026). “An intelligent medical image denoising approach based on region-vision transformer-based adaptive mobile-unet++ with Kalman filter for improved clinical diagnosis.” International Journal of Computational Intelligence Systems, 19(1) (Springer, SCI-Q2, IF: 3.0). DOI: 10.1007/s44196-025-01125-7.

Suganya, R., Leo Joseph, L. M. I., & Kollem, S. (2026). “A real-time learning-assisted charging strategy for lithium-ion batteries in electric vehicles.” International Journal of Electrochemical Science, 21(1), 101259 (Elsevier, SCI-Q3, IF: 2.4). DOI: 10.1016/j.ijoes.2025.101259.

Assudani, P. J., Bhurgy, A. S., Kollem, S., Bhurgy, B. S., Ahmad, M. O., Kulkarni, M. B., & Bhaiyya, M. (2025). “Artificial intelligence and machine learning in infectious disease diagnostics: A comprehensive review of applications, challenges, and future directions.” Microchemical Journal, 218, 115802 (Elsevier, SCI-Q1, IF: 5.1). DOI: 10.1016/j.microc.2025.115802.

Suganya, R., Joseph, L. M. I. L., & Kollem, S. (2025). “Integration of 5G and 4G Communication in battery management systems for Electric Vehicles: A cloud-based architecture for enhanced performance and analytics.” Internet Technology Letters, 8(5) (Wiley, ESCI-Q4, IF: 0.5). DOI: 10.1002/itl2.70112.

Mounika, G., Kollem, S., & Samala, S. (2025). “Investigating brain tumor classification using MRI: A scientometric analysis of selected articles from 2015 to 2024.” Neuroradiology, 67(10), 2635–2672 (Springer, SCI-Q2, IF: 2.6). DOI: 10.1007/s00234-025-03685-z.

Kumar, S., Aravinth, S. S., Kollem, S., Kumar, M., Naveed, Q. N., Mubarakali, A., Bhattacherjee, A., & Emma, A. F. (2025). “Spatial attention-guided pre-trained networks for accurate identification of crop diseases.” Scientific Reports, 15(1), 23213 (Springer Nature, SCI-Q1, IF: 3.9). DOI: 10.1038/s41598-025-08004-3

Sekar, G., Rajasekaran, A. S., Kollem, S., & Chapa, B. P. (2025). “Distended pixel replacement method for enhancing visual quality of low-light images.” Signal, Image and Video Processing, 19(3) (Springer, SCI-Q3, IF: 2.1). DOI: 10.1007/s11760-024-03787-w.

Chandrasekhar, N., Canavoy Narahari, S., Kollem, S., Peddakrishna, S., Penchala, A., & Prasad Chapa, B. (2025). “Heart abnormality classification using ECG and PCG recordings with novel PJM-DJRNN.” Results in Engineering, 25, 104032 (Elsevier, ESCI-Q1, IF: 6.0). DOI: 10.1016/j.rineng.2025.104032

Suganya, R., Joseph, L. M. I. L., & Kollem, S. (2024). “Understanding lithium-ion battery management systems in electric vehicles: Environmental and health impacts, comparative study, and future trends: A review.” Results in Engineering, 24, 103047 (Elsevier, ESCI-Q1, IF: 6.0). DOI: 10.1016/j.rineng.2024.103047.

Jayakumar, D., Krishnaiah, M., Kollem, S., Peddakrishna, S., Chandrasekhar, N., & Thirupathi, M. (2024). “Emergency vehicle classification using combined temporal and spectral audio features with machine learning algorithms.” Electronics, 13(19), 3873 (MDPI, SCI-Q2, IF: 2.6). DOI: 10.3390/electronics13193873.

Kollem, S., Sirigiri, C., & Peddakrishna, S. (2024). “A novel hybrid deep CNN model for breast cancer classification using Lipschitz-based image augmentation and recursive feature elimination.” Biomedical Signal Processing and Control, 95, 106406 (Elsevier, SCI-Q1, IF: 5.1). DOI: 10.1016/j.bspc.2024.106406.

Naresh, M., Nagaraju, V. S., Kollem, S., Kumar, J., & Peddakrishna, S. (2024). “Non-invasive glucose prediction and classification using NIR technology with machine learning.” Heliyon, 10(7), e28720 (Elsevier, SCI-Q1, IF: 4.0). DOI: 10.1016/j.heliyon.2024.e28720.

Kollem, S. (2024). “A fast computational technique based on a novel tangent sigmoid anisotropic diffusion function for image-denoising.” Soft Computing, 28(11–12), 7501–7526 (Springer, SCI-Q2, IF: 4.1). DOI: 10.1007/s00500-024-09628-9. Sreedhar Resume3 2026(3)

Kollem, S. (2024). “An efficient method for MRI brain tumor tissue segmentation and classification using an optimized support vector machine.” Multimedia Tools and Applications, 83(26), 68487–68519 (Springer, SCI-Q2, IF: 3.6). DOI: 10.1007/s11042-024-18233-9.

Sreejith, S., Leo Joseph, L. M. I., Kollem, S., Vijumon, V. T., & Ajayan, J. (2023). “Biodegradable sensors: A comprehensive review.” Measurement: Journal of the International Measurement Confederation, 219, 113261 (Elsevier, SCI-Q1, IF: 5.6). DOI: 10.1016/j.measurement.2023.113261. Sreedhar Resume3 2026(3)

Kollem, S., Prasad, C. R., Ajayan, J., Sreejith, S., Joseph, L. L., & Krishna, P. (2023). “Segmentation of brain MRI images using multi-kernel FCM EHO method.” Current Medical Imaging Reviews (Bentham Science/Elsevier, SCI-Q3, IF: 1.5). DOI: 10.2174/1573405620666230822114029.

Kollem, S., Reddy, K. R., Prasad, C. R., Chakraborty, A., Ajayan, J., Sreejith, S., Bhattacharya, S., Joseph, L. M. I. L., & Janapati, R. (2023). “AlexNet-NDTL: Classification of MRI brain tumor images using modified AlexNet with deep transfer learning and Lipschitz-based data augmentation.” International Journal of Imaging Systems and Technology, 33(4), 1306–1322 (Wiley, SCI-Q2, IF: 3.3). DOI: 10.1002/ima.22870.

Kollem, S., Reddy, K. R., & Rao, D. S. (2023). “A novel diffusivity function-based image denoising for MRI medical images.” Multimedia Tools and Applications, 82(21), 32057–32089 (Springer, SCI-Q2, IF: 3.6). DOI: 10.1007/s11042-023-14457-3.

Ajayan, J., Mohankumar, P., Nirmal, D., Joseph, L. M. I. L., Bhattacharya, S., Sreejith, S., Kollem, S., Rebelli, S., Tayal, S., & Mounika, B. (2023). “Ferroelectric Field Effect Transistors (FeFETs): Advancements, challenges and exciting prospects for next generation Non-Volatile Memory (NVM) applications.” Materials Today Communications, 35, 105591 (Elsevier, SCI-Q2, IF: 3.8). DOI: 10.1016/j.mtcomm.2023.105591.

Bhattacharya, S., Hussain, M. I., Ajayan, J., Tayal, S., Joseph, L. M. I. L., Kollem, S., Desai, U., Ahmed, S. M., & Janapati, R. (2023). “Analysis of read speed latency in 6T-SRAM cell using multi-layered graphene nanoribbon and Cu based nano-interconnects for high performance memory circuit design.” ETRI Journal, 45(5), 910–921 (Wiley, SCI-Q4, IF: 1.622). DOI: 10.4218/etrij.2022-0068.

Sreejith, S., Ajayan, J., Kollem, S., & Sivasankari, B. (2022). “A comprehensive review on thin film amorphous silicon solar cells.” Silicon, 14(14), 8277–8293 (Springer, SCI-Q3, IF: 2.670). DOI: 10.1007/s12633-021-01644-w.

Bhattacharya, S., Ajayan, J., Nirmal, D., Tayal, S., Kollem, S., & Joseph, L. M. I. L. (2022). “Investigation on DC/RF performance of LG = 19 nm heterogeneous integrated Ga0.15In0.85As/InAs/Ga0.15In0.85As composite channel InP HEMT on silicon substrate for future beyond 5G and quantum computing applications.” Silicon, 14(15), 9581–9588 (Springer, SCI-Q3, IF: 2.670). DOI: 10.1007/s12633-022-01719-2.

Kollem, S., Prasad, C. R., Ajayan, J., Malathy, V., & Subbarao, A. (2023). “Brain tumor MRI image segmentation using an optimized multi-kernel FCM method with a pre-processing stage.” Multimedia Tools and Applications, 82(14), 20741–20770 (Springer, SCI-Q2, IF: 3.6). DOI: 10.1007/s11042-022-14045-x.

Kollem, S., Ramalinga Reddy, K., Srinivasa Rao, D., Rajendra Prasad, C., Malathy, V., Ajayan, J., & Muchahary, D. (2022). “Image denoising for magnetic resonance imaging medical images using improved generalized cross-validation based on the diffusivity function.” International Journal of Imaging Systems and Technology, 32(4), 1263–1285 (Wiley, SCI-Q2, IF: 3.3). DOI: 10.1002/ima.22681.

Janapati, R., Dalal, V., Sengupta, R., Desai, U., Raja Shekar, P. V., & Kollem, S. (2022). “Towards a more theory-driven BCI using source reconstructed dynamics of EEG time-series.” Nano LIFE, 12(02) (World Scientific, SCI-Q4, IF: 1.23). DOI: 10.1142/S1793984422500052.

Kollem, S., Reddy, K. R., & Rao, D. S. (2021). “Improved partial differential equation-based total variation approach to non-subsampled contourlet transform for medical image denoising.” Multimedia Tools and Applications, 80(2), 2663–2689 (Springer, SCI-Q2, IF: 2.757). DOI: 10.1007/s11042-020-09745-1.

Kollem, S., Reddy, K. R., & Rao, D. S. (2021). “An optimized SVM based possibilistic fuzzy c-means clustering algorithm for tumor segmentation.” Multimedia Tools and Applications, 80(1), 409–437 (Springer, SCI-Q2, IF: 2.757). DOI: 10.1007/s11042-020-09675-y.

Muchahary, D., Priyanka, K., Ram, L. S., Prahitha, A., & Kollem, S. (2021). “Performance enhancement through optimization of metal oxide electron transport layer in hybrid solar cell.” Optik, 248, 168102 (Elsevier, SCI-Q3, IF: 2.443). DOI: 10.1016/j.ijleo.2021.168102.

Kollem, S., Rama Linga Reddy, K., & Srinivasa Rao, D. (2020). “Modified transform-based gamma correction for MRI tumor image denoising and segmentation by optimized histon-based elephant herding algorithm.” International Journal of Imaging Systems and Technology, 30(4), 1271–1293 (Wiley, SCI-Q2, IF: 2.0). DOI: 10.1002/ima.22429.

Kollem, S., Reddy, K. R. L., & Rao, D. S. (2019). “Denoising and segmentation of MR images using fourth order non-linear adaptive PDE and new convergent clustering.” International Journal of Imaging Systems and Technology, 29(3), 195–209 (Wiley, SCI-Q2, IF: 2.117). DOI: 10.1002/ima.22302.

Baronia, A., Gupta, S., Kollem, S., Agarwal, V., & Chakaraborty, A. (2026). “Enhancement of performance by the utilization of one-dimensional OCDMA codes in a three-dimensional system.” Journal of Optical Communications (De Gruyter, Scopus-Q1). DOI: 10.1515/joc-2026-0236.

Chandrasekhar, N., Samineni, P., & Kollem, S. (2026). “RNN-GRU hybrid deep learning framework for heart disease prediction.” Engineering Review, 46(1), 1–18 (Scopus-Q3). DOI: 10.30765/er.2434.

Dharanikota, R., & Kollem, S. (2026). “Advancement in cardiac MRI segmentation using deep learning architectures, training strategies, and clinical applications.” SN Computer Science, 7(6) (Springer, Scopus-Q1). DOI: 10.1007/s42979-026-05178-z.

Panaganti, N., & Kollem, S. (2026). “A brief survey of medical image denoising: Past methodologies and challenges, future research trends.” Annals of Data Science, 1–44 (Springer, Scopus-Q1). DOI: 10.1007/s40745-026-00693-5.

Manohar, V., & Kollem, S. (2026). “AfroNet: A Cross-Attention Enhanced U-Net for Breast Cancer Image Segmentation.” Journal of Image and Graphics, 14(1) (Scopus-Q2). DOI: 10.18178/joig.14.1.1-14.

Dustakar, S. R., Kollem, S., & Ahmad, S. M. K. M. (2026). “Graph Attention and Contrastive Learning for Enhanced Spatio-temporal Human Activity Recognition.” International Journal of Intelligent Engineering & Systems, 19(2) (Scopus-Q1). DOI: 10.22266/ijies2026.0228.30.

Kollem, S., Reddy, K. R. L., & Rao, D. S. (2019). “A review of image denoising and segmentation methods based on medical images.” International Journal of Machine Learning and Computing, 9(3), 288–295 (Scopus-Q1). DOI: 0.18178/ijmlc.2019.9.3.800.

Kollem, S., Reddy, K. R. L., & Rao, D. S. (2018). “Image denoising by using modified SGHP algorithm.” International Journal of Electrical and Computer Engineering, 8(2), 971 (Scopus-Q1). DOI: 10.11591/ijece.v8i1.

Interests

Research Areas

Student Supervision

Key Publications

Research Projects/Patents

Awards & Achievements

World’s Top 2% Scientist

World’s Top 2% Scientist

Vice Chancellor’s Annual Performance Appraisal Award

Vice Chancellor’s Annual Performance Appraisal Award

Hotshot Researcher of the Academic Year

Distinguished Consistent Researcher Award

High Achiever – Maximum SCI Publications Award