Dr. Barnali Goswami

@mitwpu.edu.in

Assistant Professor, School of Computer Science, Faculty of Science
MIT World Peace University

Dr. Barnali Goswami


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https://researchid.co/barnaligoswami

EDUCATION

Ph.D. in Engineering

RESEARCH INTERESTS

Image Processing, Soft Computing
10

Scopus Publications

92

Scholar Citations

5

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • Freezing of USAID: a health crisis for India's transgender community
    Shashwat S Banerjee, Barnali Goswami Banerjee
    Lancet, 2025
  • Computer vision and machine-learning techniques for quantification and predictive modeling of intracellular anticancer drug delivery by nanocarriers
    Sanjay Goswami, Kshama D. Dhobale, Ravindra D. Wavhale, Barnali Goswami, Shashwat S. Banerjee
    Applied AI Letters, 2022
    The field of cancer nanomedicine has made significant progress, but its clinical translation is impeded by many challenges, such as the difficulty in analyzing intracellular anticancer drug release by the nanocarriers due to the lack of suitable tools. Here, we propose the development of an image‐based strategy involving machine learning (ML) to evaluate anticancer drug such as doxorubicin hydrochloride (DOX) released by a nanocarrier inside the HCT116 colon cancer cells and its subsequent intracellular accumulation. This technique combines fluorescent cell imaging with ML‐based image analysis to assess and quantify the delivery of DOX by nanoparticles within them. We show that DOX in HCT116 cells was higher for multifunctional CNT‐DOX‐Fe3O4 nanocarrier than free DOX, indicating efficient and steady release of DOX as well as superior retentive property of the nanocarrier. Initially (1 and 4 hours), the luminance intensity of DOX in the cell cytoplasm delivered by CNT‐DOX‐Fe3O4 nanocarrier was ~0.34 and ~0.42 times lesser than that of free DOX delivered normally. However, at 24 and 48 hours posttreatment, the luminance intensity of DOX for CNT‐DOX‐Fe3O4 nanocarrier was ~1.98 and ~1.92 times higher than that of free DOX. Furthermore, the luminance intensity of DOX for CNT‐DOX‐Fe3O4 in the whole cell was ~1.35 and ~1.62 times higher than that of free DOX at 24 and 48 hours, respectively. The high‐throughput nature of our image analysis workflow allowed us to automate the process of DOX retention analysis and enabled us to devise ML‐based modeling to predict the percentage of anticancer drug retention in cells. The development of models to automatically quantify and predict intracellular drug release in cancer cells could benefit personalized treatments by optimizing the design of nanocarriers.
  • A quantitative precipitation forecast model using convective-cloud tracking in satellite thermal infrared images and adaptive regression: a case study along East Coast of India
    Barnali Goswami, Gupinath Bhandari, Sanjay Goswami
    Modeling Earth Systems and Environment, 2021
    The current work addresses issues related to quantitative estimation of precipitation caused by convective clouds, using thermal infrared images, and adaptive regression modeling. The developed methodology has been implemented on the Indian sector during the period 22–25 October 2013. The importance of the developed methodology lies in the fact that the information obtained from it can facilitate further studies intended for the prediction of flood events. This study is the continuation of existing work of identification of convective clouds and the analysis of the Mesoscale Convective Systems (MCS). In the current work, forecast of rainfall in terms of millimeter has been proposed. The entire work has been carried out on thermal infrared (TIR) images obtained from geostationary satellites and the results have been validated by actual rainfall data measured by rain gauges. The results obtained from the developed methodology were found to be fairly close to actual values.
  • Mesoscale convective system tracking in satellite thermal infrared images
    Barnali Goswami, Gupinath Bhandari, Sanjay Goswami
    11th IEEE India Conference Emerging Trends and Innovation in Technology Indicon 2014, 2015
    In the field of meteorology, mesoscale convective systems are required to be distinguished, tracked, and their lifecycle to be observed, for precipitation forecasting. Mesoscale convective systems are easily identifiable from satellite infrared images. There are several existing techniques like temperature induced mean based cloud motion prediction model, for identification and tracking of cloud structures from a series of thermal infrared images. This technique has been previously implemented for tracking of single and then multiple cloud clusters. In this study, temperature induced mean based cloud motion prediction model has been deployed for tracking and predicting the motion of an entire convective system.
  • Temperature induced mean based cloud motion prediction model for multiple cloud clusters in satellite infrared images
    Barnali Goswami, Gupinath Bhandari, Sanjay Goswami
    Proceedings 4th International Conference on Emerging Applications of Information Technology Eait 2014, 2014
    Thermal infrared images are quite useful in detection of convective clouds for meteorological purposes. Several techniques are available for the detection and tracking of clouds in satellite thermal infrared images. Temperature induced mean based cloud motion prediction model is one of them. But so far, it has been implemented for tracking single cloud cluster. In the present work this model is extended and applied for tracking of multiple cloud clusters so that it can be utilized for weather nowcasting.
  • Convective Cloud Detection and Tracking from Series of Infrared Images
    Barnali Goswami, Gupinath Bhandari
    Journal of the Indian Society of Remote Sensing, 2013
    The most significant part of prediction of precipitation is the detection and identification of convective (cumulonimbus) clouds, also the tracking of cloud movement is important for identification of location of precipitation. A very simple methodology for detecting convective clouds and then tracking its movement from a series of infrared (IR) images is proposed in this paper. IR image is segmented using k-means clustering algorithm, which has been implemented using Euclidean, Manhattan and Mahalanobis distances and the results have been compared. Cloud clusters have been identified from segmented image and subsequently the large clusters were extracted. Center of Mass (CoM) was calculated for each selected cloud cluster and its position after every 30 min was predicted and compared with the actual values. If the predicted position deviates, the proposed models automatically adjusts itself, and the next prediction becomes closer to original values of position.
  • Development of irregular cloud cluster encapsulating structure from satellite infrared images
    33rd Asian Conference on Remote Sensing 2012 Acrs 2012, 2012
  • Temperature induced mean based cloud motion prediction model from satellite infrared images
    Barnali Goswami, Gupinath Bhandari
    2012 Annual IEEE India Conference Indicon 2012, 2012
    Detection and identification of convective clouds can be done from thermal infrared (TIR) images (10.5-12.5μm) as clouds are associated with extremely low temperature. Clouds can be tracked from a given sequence of satellite images, and becomes useful for weather now-casting. There are several models available for cloud motion prediction. Adjusted Mean Based Prediction (AMBP) Model is one of them. A modified model of AMBP, based on temperature, for cloud movement tracking has been proposed and presented in this paper for better prediction.
  • Fuzzy min-max neural network for satellite infrared image clustering
    Barnali Goswami, Gupinath Bhandari, Sanjay Goswami
    Proceedings 2012 3rd International Conference on Emerging Applications of Information Technology Eait 2012, 2012
    The process of estimation of precipitation from satellite images begins with the detection and identification of convective clouds. Clustering of the satellite infrared images is required in order to estimate the cloud cover area. In this paper a neuro-fuzzy technique in the form of unsupervised fuzzy minmax clustering neural (FMMCN) network has been implemented for clustering satellite infrared image. Each cluster is in the form of an n-dimensional hyperbox defined by minimum and maximum points and a fuzzy membership function. FMMCN suits this application area because it is completely unsupervised and hence, unlabeled data can be used with it. Also the number of clusters is not required to be mentioned at the beginning as it is calculated dynamically.
  • Automatically adjusting cloud movement prediction model from satellite infrared images
    Barnali Goswami, Gupinath Bhandari
    Proceedings 2011 Annual IEEE India Conference Engineering Sustainable Solutions Indicon 2011, 2011
    Tracking and predicting cloud movement is one the most important step in pluviometry. The purpose of this study is to develop a self adjusting technique to predict the movement of clouds from a series of infrared (IR) images. The first task is to identify clouds from the images. This is done by clustering the images using K-means algorithm. Clouds are identified from segmented image and the large clusters are extracted. Center of Mass (CoM) is calculated for each cloud cluster and its position after every 30 minutes is predicted. Whenever the original position deviates from the predicted values, the model automatically adjusts itself with the change and the next prediction becomes closer to original values of position.

RECENT SCHOLAR PUBLICATIONS

  • Drug storage container
    S CHAKRABORTY, DI MUTSUDDI, DRS HALDER, ...
    IN Patent 223,178 , 2026
    2026.0
  • Freezing of USAID: a health crisis for India's transgender community
    SS Banerjee, BG Banerjee
    The Lancet 405 (10492), 1813-1814 , 2025
    2025.0
    Citations: 1
  • Generative Artificial Intelligence: Revolution in the field of Oral Health Care
    BS Banerjee
    MIMER Medical Journal 9 (1), 22-24 , 2025
    2025.0
  • Society, Pedagogy, Politics: A Multidimensional Approach to COVID-19
    G Bhandari
    Jadavpur University Press , 2022
    2022.0
  • A COMPREHENSIVE ANALYSIS OF COVID-19 IN WEST BENGAL AND ITS QUALITATIVE IMPACT ON SOCIAL, MENTAL AND PHYSICAL HEALTH
    S Goswami, G Bhandari, B Goswami, S Banerjee
    Society, Pedagogy, Politics: A Multidimensional Approach to COVID-19, 214 , 2022
    2022.0
  • Hexalevel Grayscale Imaging and K-Means Clustering to Identify Cloud Types in Satellite Visible Range Images
    S Goswami, B Goswami, G Bhandari
    Proceedings of International Conference on Computational Intelligence and … , 2021
    2021.0
    Citations: 1
  • A quantitative precipitation forecast model using convective-cloud tracking in satellite thermal infrared images and adaptive regression: a case study along East Coast of India
    B Goswami, G Bhandari, S Goswami
    Modeling Earth Systems and Environment 7 (2), 1097-1105 , 2021
    2021.0
    Citations: 5
  • Anti-Cancer Drug Delivery Modeling in Nanomedicine with Combinatorial Image Analysis and Non-Linear Regression
    S GOSWAMI, K DHOBALE, R WAVHALE, B GOSWAMI, S BANERJEE
    Authorea Preprints , 2021
    2021.0
  • Computer vision and machine‐learning techniques for quantification and predictive modeling of intracellular anticancer drug delivery by nanocarriers
    S Goswami, KD Dhobale, RD Wavhale, B Goswami, SS Banerjee
    Applied AI Letters, e50 , 2021
    2021.0
    Citations: 6
  • Mesoscale convective system tracking in satellite thermal infrared images
    B Goswami, G Bhandari, S Goswami
    2014 Annual IEEE India Conference (INDICON), 1-4 , 2014
    2014.0
    Citations: 4
  • Temperature Induced Mean Based Cloud Motion Prediction Model for Multiple Cloud Clusters in Satellite Infrared Images
    B Goswami, G Bhandari, S Goswami
    Emerging Applications of Information Technology (EAIT), 2014 Fourth … , 2014
    2014.0
    Citations: 6
  • Convective cloud detection and tracking from series of infrared images
    B Goswami, G Bhandari
    Journal of the Indian Society of Remote Sensing 41 (2), 291-299 , 2013
    2013.0
    Citations: 18
  • Application of General Fuzzy Min-Max Neural Network for the Clustering of Satellite Thermal Infrared Images
    B Goswami, G Bhandari
    4th International Conference on Technical and Managerial Innovation in … , 2013
    2013.0
  • Temperature Induced Mean Based Cloud Motion Prediction Model from Satellite Infrared Images
    B Goswami, G Bhandari
    India Conference (INDICON), 2012 Annual IEEE, 719-723 , 2012
    2012.0
    Citations: 5
  • Fuzzy min-max neural network for satellite infrared image clustering
    B Goswami, G Bhandari, S Goswami
    2012 Third International Conference on Emerging Applications of Information … , 2012
    2012.0
    Citations: 12
  • Development of irregular cloud cluster encapsulating structure from satellite infrared images
    B Goswami, G Bhandari
    Proceedings of the 33rd Asian Conference on Remote Sensing (ACRS-2012 … , 2012
    2012.0
    Citations: 5
  • Automatically adjusting cloud movement prediction model from satellite infrared images
    B Goswami, G Bhandari
    2011 Annual IEEE India Conference, 1-4 , 2011
    2011.0
    Citations: 19
  • Cloud Motion Prediction using Mean Path Adjustment Method from Satellite Infrared Images
    B Goswami, G Bhandari
    CALCON 2011, organized by IEEE Kolkata Section,, 313-316 , 2011
    2011.0
    Citations: 5
  • Near Real-Time Detection of Heavy Rain Clouds from IR Image for Estimation of Precipitation
    B Goswami, G Bhandari
    3rd International Conference on Water & Flood Management (ICWFM 2011) 1, 277-281 , 2011
    2011.0
    Citations: 5
  • Comparison of Three Distances In K-Means Clustering On Satellite Imagery
    B Goswami, S Goswami

MOST CITED SCHOLAR PUBLICATIONS

  • Automatically adjusting cloud movement prediction model from satellite infrared images
    B Goswami, G Bhandari
    2011 Annual IEEE India Conference, 1-4 , 2011
    2011.0
    Citations: 19
  • Convective cloud detection and tracking from series of infrared images
    B Goswami, G Bhandari
    Journal of the Indian Society of Remote Sensing 41 (2), 291-299 , 2013
    2013.0
    Citations: 18
  • Fuzzy min-max neural network for satellite infrared image clustering
    B Goswami, G Bhandari, S Goswami
    2012 Third International Conference on Emerging Applications of Information … , 2012
    2012.0
    Citations: 12
  • Computer vision and machine‐learning techniques for quantification and predictive modeling of intracellular anticancer drug delivery by nanocarriers
    S Goswami, KD Dhobale, RD Wavhale, B Goswami, SS Banerjee
    Applied AI Letters, e50 , 2021
    2021.0
    Citations: 6
  • Temperature Induced Mean Based Cloud Motion Prediction Model for Multiple Cloud Clusters in Satellite Infrared Images
    B Goswami, G Bhandari, S Goswami
    Emerging Applications of Information Technology (EAIT), 2014 Fourth … , 2014
    2014.0
    Citations: 6
  • A quantitative precipitation forecast model using convective-cloud tracking in satellite thermal infrared images and adaptive regression: a case study along East Coast of India
    B Goswami, G Bhandari, S Goswami
    Modeling Earth Systems and Environment 7 (2), 1097-1105 , 2021
    2021.0
    Citations: 5
  • Temperature Induced Mean Based Cloud Motion Prediction Model from Satellite Infrared Images
    B Goswami, G Bhandari
    India Conference (INDICON), 2012 Annual IEEE, 719-723 , 2012
    2012.0
    Citations: 5
  • Development of irregular cloud cluster encapsulating structure from satellite infrared images
    B Goswami, G Bhandari
    Proceedings of the 33rd Asian Conference on Remote Sensing (ACRS-2012 … , 2012
    2012.0
    Citations: 5
  • Cloud Motion Prediction using Mean Path Adjustment Method from Satellite Infrared Images
    B Goswami, G Bhandari
    CALCON 2011, organized by IEEE Kolkata Section,, 313-316 , 2011
    2011.0
    Citations: 5
  • Near Real-Time Detection of Heavy Rain Clouds from IR Image for Estimation of Precipitation
    B Goswami, G Bhandari
    3rd International Conference on Water & Flood Management (ICWFM 2011) 1, 277-281 , 2011
    2011.0
    Citations: 5
  • Mesoscale convective system tracking in satellite thermal infrared images
    B Goswami, G Bhandari, S Goswami
    2014 Annual IEEE India Conference (INDICON), 1-4 , 2014
    2014.0
    Citations: 4
  • Freezing of USAID: a health crisis for India's transgender community
    SS Banerjee, BG Banerjee
    The Lancet 405 (10492), 1813-1814 , 2025
    2025.0
    Citations: 1
  • Hexalevel Grayscale Imaging and K-Means Clustering to Identify Cloud Types in Satellite Visible Range Images
    S Goswami, B Goswami, G Bhandari
    Proceedings of International Conference on Computational Intelligence and … , 2021
    2021.0
    Citations: 1
  • Drug storage container
    S CHAKRABORTY, DI MUTSUDDI, DRS HALDER, ...
    IN Patent 223,178 , 2026
    2026.0
  • Generative Artificial Intelligence: Revolution in the field of Oral Health Care
    BS Banerjee
    MIMER Medical Journal 9 (1), 22-24 , 2025
    2025.0
  • Society, Pedagogy, Politics: A Multidimensional Approach to COVID-19
    G Bhandari
    Jadavpur University Press , 2022
    2022.0
  • A COMPREHENSIVE ANALYSIS OF COVID-19 IN WEST BENGAL AND ITS QUALITATIVE IMPACT ON SOCIAL, MENTAL AND PHYSICAL HEALTH
    S Goswami, G Bhandari, B Goswami, S Banerjee
    Society, Pedagogy, Politics: A Multidimensional Approach to COVID-19, 214 , 2022
    2022.0
  • Anti-Cancer Drug Delivery Modeling in Nanomedicine with Combinatorial Image Analysis and Non-Linear Regression
    S GOSWAMI, K DHOBALE, R WAVHALE, B GOSWAMI, S BANERJEE
    Authorea Preprints , 2021
    2021.0
  • Application of General Fuzzy Min-Max Neural Network for the Clustering of Satellite Thermal Infrared Images
    B Goswami, G Bhandari
    4th International Conference on Technical and Managerial Innovation in … , 2013
    2013.0
  • Comparison of Three Distances In K-Means Clustering On Satellite Imagery
    B Goswami, S Goswami