Chandan Chakraborty, Ph.D

Designation:        Professor, Computer Science and Engineering
Phone Number:  +91 33 66251986 (Direct Line), EPBX Extn. - 986
Email Address:   chandan 'at'
Area of Interest:
  • Machine Learning
  • AI in Education
  • AI in Healthcare
  • Pattern Recognition
  • Statistics & Data Science
  • Biomedical Image Analysis
  • Python & R Programming

  • ISCA Young Scientist Award from Hon'ble President of India Dr APJ Abdul Kalam
  • DAE-Young Scientist Research Award, Dept. of Atomic Energy, Govt. of India
  • DST Fast Track Young Scientist Award
  • IBM Faculty Award, New York, USA
  • Outstanding Faculty Award by Venus International Foundation, India
  • IBM-Shared University Research Award, New York, USA
  • Highly Cited Research Award by Elsevier
  • BIRAC-SRISTI Gandhian Young Technological Innovation Award
  • US Patent : Method and system for detection of oral sub-mucous fibrosis using microscopic image analysis of oral biopsy samples [Granted: US2010/0111398A1]
  • US Patent : Method and system for analyzing breast carcinoma using microscopic image analysis of fine needle aspirates [Granted: US2010/0111397A1]
  • Indian Patent: PathoQuant: A portable system for microscopic image acquisition under low-resource framework for histological evaluation [TEMP/E-1/15578/2017-KOL]
  • Indian Patent: Immunohistochemical Scope [Ref No:201831002938/2018-KOL}
  • LWSNet - a novel deep-learning architecture to segregate Covid-19 and pneumonia from x-ray imagery by A Lasker, M Ghosh, SM Obaidullah, C Chakraborty & K Roy,Multimedia Tools and Applications 82(14)(2023)
  • Application of Machine Learning and Deep Learning Techniques for COVID-19 Screening Using Radiological Imaging: A Comprehensive Review by A Lasker, SM Obaidullah, C Chakraborty & K Roy, SN Computer Science 4(1): 65(2023)
  • Automated recognition of optical image based potato leaf blight diseases using deep learning by KK Chakraborty, R Mukherjee, C Chakroborty, K Bora,Physiological and Molecular Plant Pathology, 117 (2022)
  • HscoreNet: A Deep network for estrogen and progesterone scoring using breast IHC images by M Saha, I Arun, R Ahmed, S Chatterjee, C Chakraborty,Pattern Recognition(2020)
  • Her2Net: A Deep Framework for Semantic Segmentation and Classification of Cell Membranes and Nuclei in Breast Cancer Evaluation by M Saha,C Chakraborty,IEEE Transactions on Image Processing, 27(5): 2189-2200 (2018)
  • Efficient Deep Learning Model for Mitosis Detection using Breast Histopathology Images by M Saha, C Chakraborty, R. Daniel,Computerized Medical Imaging and Graphics, 64: 29-40(2018)
  • "Omics" in oral cancer: New approaches for biomarker discovery by V Rai, R Mukherjee, AK. Ghosh, A Routray, C Chakraborty,Archives of Oral Biology, 87: 15-34 (2018)
  • Serum-based diagnostic prediction of oral submucous fibrosis using FTIR spectrometry by V Rai, R Mukherjee, A Routray, AK Ghosh, S Roy, BPaul Ghosh, PB Mandal, S Bose, C Chakraborty,Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 15;189:322-329 (2017)
  • Fuzzy spectral clustering for automated delineation of chronic wound region using digital images by DM Dhane, M Maiti, T Mungle, C Bar, A Achar, M Kolekar, C Chakraborty,Computers in Biology and Medicine (Elsevier), 89:551-560 (2017)
  • Automated characterization and counting of Ki-67 protein for breast cancer prognosis: A quantitative immunohistochemistry approach by T Mungle, S Tewary, I Arun, B Basak, S Agarwal, R Ahmed, S Chatterjee, A K Maity, C Chakraborty,Computer Methods & Programs in Biomedicine (Elsevier), (2017)139:149-161. doi: 10.1016/j.cmpb.2016.11.002
  • An Advanced Deep Learning Approach for Ki-67 Stained Hotspot Detection and Proliferation Rate Scoring for Prognostic Evaluation of Breast Cancer by M Saha, C Chakraborty, I Arun, R Ahmed, S Chatterjee,Scientific Reports - (Nature), article no. 3213, doi:10.1038/s41598-017-03405-5, (2017).
  • SmartIHC-Analyzer: Smartphone assisted microscopic image analytics for automated Ki-67 quantification in breast cancer evaluation by S Tewary, I Arun, R Ahmed, S Chatterjee, C Chakraborty,Analytical Methods (RSC Pub.), 43 DOI: 10.1039/C7AY02302B (2017)
  • Computational Approach for Mitotic Cell Detection and its Application in Oral Squamous Cell Carcinoma by DK Das, P Mitra, C Chakraborty, S Chatterjee, AK Maiti, S Bose, Multidimensional Systems and Signal Processing (Springer), 28(3) 1031-1050 (2017)
  • MRF-ANN: A Machine Learning Approach for Automated ER Scoring of Breast Cancer Immunohistochemical Images by T Mungle, S Tewary, DK Das, I Arun, B Basak, S Agarwal, R Ahmed, S Chatterjee, C Chakraborty, Journal of Microscopy (Willey), 267(2):117-129 (2017)
  • Imprint Cytology-based Breast Malignancy Screening: An Efficient Nuclei Segmentation Technique by M Saha, I Arun, R Ahmed, S Chatterjee, C Chakraborty, Journal of Microscopy (Willey),268(2):155-171 (2017)
  • Automated Identification of Normoblast Cell from Human Peripheral Blood Smear Image by D Das, AK Maiti, C Chakraborty,Journal of Microscopy (Willey),269(3):310-320 (2017)
  • Near-set based mucin segmentation in histopathology images for detecting mucinous carcinoma by S Banerjee, M Saha, I Arun, B Basak, S Agawal, R Ahmed, S Chatterjee, LB Mahanta, C Chakraborty,Journal of Medical Systems (Springer), 41(9):144 (2017)