Ananya Bhattacharjee

@sitpune.edu.in

Assistant Professor, AIML
Symbiosis Institute of Technology Pune

Ananya Bhattacharjee
Ms. Ananya Bhattacharjee holds a B.Tech degree in Electronics and Telecommunication (2015) under Gauhati University and MTech degree in Electronics and Communication (2018) from North Eastern Regional Institute of Science and Technology (NERIST), Arunachal Pradesh. She has submitted her Ph.D. thesis at NIT Silchar, Assam for Ph.D. degree award. She has four years of teaching experience as teaching assistant at NIT Silchar, Assam. She has more than 10 research publications in reputable journals such as IEEE transactions, springer etc. and IEEE conferences, including both national and international. She has 4 SCI publications in her credit. She is passionate about AI, Deep Learning, Machine Learning, Data Science, Data Visualization, Computer Vision and Medical Imaging. She is dedicated to leveraging her expertise to equip students with the skills needed to excel in these rapidly evolving fields. She is in Automation and Artificial Intelligence cohort and Healthcare domain.

EDUCATION

B.Tech: under Gauhati University, 2015 (Electronics and Telecommunication)
M.Tech: NERIST, Arunachal Pradesh, 2018 (Electronics and Communication)
PhD: NIT Silchar

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Vision and Pattern Recognition, Cancer Research, Artificial Intelligence, Signal Processing

FUTURE PROJECTS

Explainable AI


Applications Invited
183

Scholar Citations

7

Scholar h-index

7

Scholar i10-index

RECENT SCHOLAR PUBLICATIONS

  • Clinical and Regulatory Considerations
    H Das Purkayastha, M Pokhrel, A Bhattacharjee, A Bhattacharjee, ...
    Pathogenesis and Treatment of Solar Radiation Induced Skin Cancer: Advances … , 2026
    2026.0
  • Artificial Intelligence and NanotechnologyIntegrated Recent Applications in Early Lung Cancer Detection and Therapy
    A Bhattacharjee, NRG Biswas, A Bhattacharjee, R Murugan, RP Swain, ...
    Nanomaterials in Biological Milieu: Biomedical Applications and … , 2025
    2025.0
  • Classification of Lung Cancer Using Ensemble Deep Neural Network Through Computed Tomography Images
    PS Cindy, A Bhattacharjee, R Murugan, RK Karsh
    2024 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES … , 2024
    2024.0
  • random forest classifier for binary classification of lung
    A Bhattacharjee, PS Cindy, R Murugan, T Goel
    Proceedings of the International Conference on Signal Processing and … , 2024
    2024.0
  • PEDNet: Preprocessed Ensembled Deep Network for Diagnosis of Epilepsy Seizures Using EEG Image Representations
    R Murugan, DNK Pandiri, A Bhattacharjee, S Yadav, T Goel
    Mind, Brain, and Consciousness Conference, 187-197 , 2023
    2023.0
  • Automated lung nodule segmentation using federated learning through ct images
    A Bhattacharjee, R Murugan, T Goel
    2023 8th International conference on robotics and automation engineering … , 2023
    2023.0
    Citations: 3
  • A multi-class deep learning model for early lung cancer and chronic kidney disease detection using computed tomography images
    A Bhattacharjee, S Rabea, A Bhattacharjee, EB Elkaeed, R Murugan, ...
    Frontiers in Oncology 13, 1193746 , 2023
    2023.0
    Citations: 54
  • Implementation of different u-net architectures for segmentation of lung cancer ct images
    PS Cindy, A Bhattacharjee, R Murugan, RK Karsh, T Goel
    2023 International Conference on Artificial Intelligence and Applications … , 2023
    2023.0
    Citations: 3
  • Pulmonary nodule segmentation framework based on fine-tuned and pretrained deep neural network using CT images
    A Bhattacharjee, R Murugan, T Goel, S Mirjalili
    IEEE Transactions on Radiation and Plasma Medical Sciences 7 (4), 394-409 , 2023
    2023.0
    Citations: 22
  • A powerful Transfer learning technique for multiclass classification of lung cancer CT images
    A Bhattacharjee, K Shankar, R Murugan, T Goel
    2022 International Conference on Engineering and Emerging Technologies … , 2022
    2022.0
    Citations: 12
  • Ada-GridRF: a fast and automated adaptive boost based grid search optimized random forest ensemble model for lung cancer detection
    A Bhattacharjee, R Murugan, B Soni, T Goel
    Physical and Engineering Sciences in Medicine 45 (3), 981-994 , 2022
    2022.0
    Citations: 20
  • A hybrid approach for lung cancer diagnosis using optimized random forest classification and K-means visualization algorithm
    A Bhattacharjee, R Murugan, T Goel
    Health and Technology 12 (4), 787-800 , 2022
    2022.0
    Citations: 38
  • Semantic segmentation of lungs using a modified U-Net architecture through limited Computed Tomography images
    A Bhattacharjee, R Murugan, T Goel, B Soni
    2021 Advanced Communication Technologies and Signal Processing (ACTS), 1-6 , 2021
    2021.0
    Citations: 11
  • Neural network–based computer-aided lung cancer detection
    A Bhattacharjee, R Murugan, S Majumder, T Goel
    Research on Biomedical Engineering 37 (4), 657-671 , 2021
    2021.0
    Citations: 4
  • Automated computer-aided lung cancer detection system
    A Bhattacharjee, S Majumder
    Advances in Communication, Devices and Networking: Proceedings of ICCDN 2018 … , 2019
    2019.0
    Citations: 16
  • Clinical and Regulatory Considerations 19
    HD Purkayastha, M Pokhrel, A Bhattacharjee, A Bhattacharjee, RK Sahu, ...
    Pathogenesis and Treatment of Solar Radiation Induced Skin Cancer: Advances … , 0

MOST CITED SCHOLAR PUBLICATIONS

  • A multi-class deep learning model for early lung cancer and chronic kidney disease detection using computed tomography images
    A Bhattacharjee, S Rabea, A Bhattacharjee, EB Elkaeed, R Murugan, ...
    Frontiers in Oncology 13, 1193746 , 2023
    2023.0
    Citations: 54
  • A hybrid approach for lung cancer diagnosis using optimized random forest classification and K-means visualization algorithm
    A Bhattacharjee, R Murugan, T Goel
    Health and Technology 12 (4), 787-800 , 2022
    2022.0
    Citations: 38
  • Pulmonary nodule segmentation framework based on fine-tuned and pretrained deep neural network using CT images
    A Bhattacharjee, R Murugan, T Goel, S Mirjalili
    IEEE Transactions on Radiation and Plasma Medical Sciences 7 (4), 394-409 , 2023
    2023.0
    Citations: 22
  • Ada-GridRF: a fast and automated adaptive boost based grid search optimized random forest ensemble model for lung cancer detection
    A Bhattacharjee, R Murugan, B Soni, T Goel
    Physical and Engineering Sciences in Medicine 45 (3), 981-994 , 2022
    2022.0
    Citations: 20
  • Automated computer-aided lung cancer detection system
    A Bhattacharjee, S Majumder
    Advances in Communication, Devices and Networking: Proceedings of ICCDN 2018 … , 2019
    2019.0
    Citations: 16
  • A powerful Transfer learning technique for multiclass classification of lung cancer CT images
    A Bhattacharjee, K Shankar, R Murugan, T Goel
    2022 International Conference on Engineering and Emerging Technologies … , 2022
    2022.0
    Citations: 12
  • Semantic segmentation of lungs using a modified U-Net architecture through limited Computed Tomography images
    A Bhattacharjee, R Murugan, T Goel, B Soni
    2021 Advanced Communication Technologies and Signal Processing (ACTS), 1-6 , 2021
    2021.0
    Citations: 11
  • Neural network–based computer-aided lung cancer detection
    A Bhattacharjee, R Murugan, S Majumder, T Goel
    Research on Biomedical Engineering 37 (4), 657-671 , 2021
    2021.0
    Citations: 4
  • Automated lung nodule segmentation using federated learning through ct images
    A Bhattacharjee, R Murugan, T Goel
    2023 8th International conference on robotics and automation engineering … , 2023
    2023.0
    Citations: 3
  • Implementation of different u-net architectures for segmentation of lung cancer ct images
    PS Cindy, A Bhattacharjee, R Murugan, RK Karsh, T Goel
    2023 International Conference on Artificial Intelligence and Applications … , 2023
    2023.0
    Citations: 3
  • Clinical and Regulatory Considerations
    H Das Purkayastha, M Pokhrel, A Bhattacharjee, A Bhattacharjee, ...
    Pathogenesis and Treatment of Solar Radiation Induced Skin Cancer: Advances … , 2026
    2026.0
  • Artificial Intelligence and NanotechnologyIntegrated Recent Applications in Early Lung Cancer Detection and Therapy
    A Bhattacharjee, NRG Biswas, A Bhattacharjee, R Murugan, RP Swain, ...
    Nanomaterials in Biological Milieu: Biomedical Applications and … , 2025
    2025.0
  • Classification of Lung Cancer Using Ensemble Deep Neural Network Through Computed Tomography Images
    PS Cindy, A Bhattacharjee, R Murugan, RK Karsh
    2024 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES … , 2024
    2024.0
  • random forest classifier for binary classification of lung
    A Bhattacharjee, PS Cindy, R Murugan, T Goel
    Proceedings of the International Conference on Signal Processing and … , 2024
    2024.0
  • PEDNet: Preprocessed Ensembled Deep Network for Diagnosis of Epilepsy Seizures Using EEG Image Representations
    R Murugan, DNK Pandiri, A Bhattacharjee, S Yadav, T Goel
    Mind, Brain, and Consciousness Conference, 187-197 , 2023
    2023.0
  • Clinical and Regulatory Considerations 19
    HD Purkayastha, M Pokhrel, A Bhattacharjee, A Bhattacharjee, RK Sahu, ...
    Pathogenesis and Treatment of Solar Radiation Induced Skin Cancer: Advances … , 0

Publications

1. A. Bhattacharjee, R. Murugan, T. Goel and S. Mirjalili, ”Pulmonary Nodule Segmentation Framework Based on Fine-Tuned and Pretrained Deep Neural Network Using CT Images,” in IEEE Transactions on Radiation and Plasma Medical Sciences, vol. 7, no. 4, pp. 394-409, April 2023, doi:10.1109/ (SCI, Q1 journal, Impact Factor: 4.6).
2. A. Bhattacharjee, R. Murugan, B. Soni, and T. Goel, “Ada-GridRF: A fast and automated adaptive boost based grid search optimized random forest ensemble model for lung cancer detection,” Physical and Engineering Sciences in Med, pp. 1–14, 2022, doi: 10.1007/s13246-022-01150-2 (SCI, Q1 journal, Impact Factor: 2.4).
3. A. Bhattacharjee, R. Murugan and T. Goel, “A hybrid approach for lung cancer diagnosis using optimized random forest classification and K-means visualization algorithm,” Health Technol. vol. 12, pp. 787–800, 2022, doi:10.1007/s12553-022-00679-2 (SCI, Q2 journal, Impact Factor: 3.1).
4. A. Bhattacharjee, S. Rabea, A. Bhattacharjee, E. B. Elkaeed, R. Murugan, H. M. R. M. Selim, R. K. Sahu, G. A. Shazly, and M. M. Salem Bekhit, “A multi-class deep learning model for early lung cancer and chronic kidney disease detection using computed tomography images,” Frontiers in Oncology, vol. 13, p. 1193746, 2023 (SCI Journal, Q2 Journal, Impact factor = 3.5).
5. A. Bhattacharjee, R. Murugan, S. Majumder, and T. Goel “Neural network–based computer-aided lung cancer detection,” Research on Biomedical Engineering, vol. 37, pp. 657–671, 20

Industry, Institute, or Organisation Collaboration

Torrens University Australia
Al-Azhar University, Cairo, Egypt
AlMaarefa University, Riyadh, Saudi Arabia
King Saud University, Riyadh, Saudi Arabia