Nikhil Kurian

Dr Nikhil Kurian

Post Doctoral Researcher

Australian Institute for Machine Learning - Projects

Faculty of Sciences, Engineering and Technology

Dr. Nikhil Kurian is a postdoctoral researcher working on developing safe, fair, and trustworthy AI for medical image analysis. Previously, he was a senior AI researcher at Fujitsu Research of India Pvt Ltd (FRIPL). Dr Kurian completed his PhD from the Indian Institute of Technology, Bombay, in May 2023. His doctoral research focused on pioneering deep learning algorithms that automatically analyze cancerous tissue in biopsy and radiology images.

  • Appointments
    Date Position Institution name
    2022 - 2023 Senior Researcher Fujitsu Research India

  • Education
    Date Institution name Country Title
    Indian Institute of Technology Bombay India PhD
    Indian Institute of Technology Gandhinagar India Master of technology

  • Journals
    Year Citation
    2023 Patil, A., Diwakar, H., Sawant, J., Kurian, N. C., Yadav, S., Rane, S., . . . Sethi, A. (2023). Efficient quality control of whole slide pathology images with human-in-the-loop training. Journal of Pathology Informatics, 14, 100306.
    DOI
    2023 Verghese, G., Li, M., Liu, F., Lohan, A., Kurian, N. C., Meena, S., . . . Grigoriadis, A. (2023). Multiscale deep learning framework captures systemic immune features in lymph nodes predictive of triple negative breast cancer outcome in large‐scale studies. The Journal of Pathology, 260(4), 376-389.
    DOI
    2022 Kanse, A. S., Kurian, N. C., Aswani, H. P., Khan, Z., Gann, P. H., Rane, S., & Sethi, A. (2022). Cautious Artificial Intelligence Improves Outcomes and Trust by Flagging Outlier Cases. JCO Clinical Cancer Informatics, (6).
    DOI
    2021 Verma, R., Kumar, N., Patil, A., Kurian, N. C., Rane, S., Graham, S., . . . Sethi, A. (2021). MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge. IEEE Transactions on Medical Imaging, 40(12), 3413-3423.
    DOI
    2021 Cherian Kurian, N., Sethi, A., Reddy Konduru, A., Mahajan, A., & Rane, S. U. (2021). A 2021 update on cancer image analytics with deep learning. WIREs Data Mining and Knowledge Discovery, 11(4).
    DOI
    2020 Anand, D., Kurian, N. C., Dhage, S., Kumar, N., Rane, S., Gann, P. H., & Sethi, A. (2020). Deep Learning to Estimate Human Epidermal Growth Factor Receptor 2 Status from Hematoxylin and Eosin-Stained Breast Tissue Images. Journal of Pathology Informatics, 11(1), 19.
    DOI
    2017 Kurian, N. C., Patel, K., & George, N. V. (2017). Robust active noise control: An information theoretic learning approach. Applied Acoustics, 117, 180-184.
    DOI

  • Conference Papers
    Year Citation
    2023 Chandra, T., Nasser, S., Kurian, N., & Sethi, A. (2023). Improving Mitosis Detection via UNet-Based Adversarial Domain Homogenizer. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies. SCITEPRESS - Science and Technology Publications.
    DOI
    2023 Gupta, R., Nandgaonkar, S., Kurian, N., Bameta, T., Yadav, S., Kaushal, R., . . . Sethi, A. (2023). EGFR Mutation Prediction of Lung Biopsy Images Using Deep Learning. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies. SCITEPRESS - Science and Technology Publications.
    DOI
    2022 Kurian, N. C., Lehan, A., Verghese, G., Dharamshi, N., Meena, S., Li, M., . . . Sethi, A. (2022). Deep Multi-Scale U-Net Architecture and Label-Noise Robust Training Strategies for Histopathological Image Segmentation. In 2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE). IEEE.
    DOI
    2022 Kurian, N. C., Varsha, S., Bajpai, A., Patel, S., & Sethi, A. (2022). Improved Histology Image Classification under Label Noise Via Feature Aggregating Memory Banks. In 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). IEEE.
    DOI
    2021 Kurian, N. C., Singh, G., Hebbar, P., Kodate, S., Rane, S., & Sethi, A. (2021). Robust Classification of Histology Images Exploiting Adversarial Auto Encoders. In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE.
    DOI
    2021 Kurian, N. C., Meshram, P. S., Patil, A., Patel, S., & Sethi, A. (2021). Sample Specific Generalized Cross Entropy for Robust Histology Image Classification. In 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI). IEEE.
    DOI
    2021 Patil, A., Talha, M., Bhatia, A., Kurian, N. C., Mangale, S., Patel, S., & Sethi, A. (2021). Fast, Self Supervised, Fully Convolutional Color Normalization Of H&E Stained Images. In 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI). IEEE.
    DOI
    2020 Wilson, B., Kurian, N. C., Singh, A., & Sethi, A. (2020). Satellite-Derived Bathymetry Using Deep Convolutional Neural Network. In IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium. IEEE.
    DOI
    2016 Patel, K., Kurian, N. C., & George, N. V. (2016). Time frequency analysis: A sparse S transform approach. In 2016 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS). IEEE.
    DOI

  • Offices Held
    Date Office Name Institution Country
    2022 - 2023 Senior Applied Researcher Fujitsu Research India
  • Position: Post Doctoral Researcher
  • Phone: 83133733
  • Email: nikhil.kurian@adelaide.edu.au
  • Campus: North Terrace
  • Building: Australian Institute for Machine Learning, floor 2
  • Org Unit: Australian Institute for Machine Learning - Projects
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