Mr. Subin Sahayam M

Assistant Professor of Computer Science and Engineering


Mr. Subin Sahayam M


Mr. Subin Sahayam M joined SNU Chennai as an Assistant Professor in the Department of Computer Science and Engineering on 16th June 2023. 

He completed his B.E from UCEN Nagercoil in 2015 and M.E from SSN College of Engineering, Chennai in 2017. He has submitted his Ph.D. thesis from IIITDM Kancheepuram in 2023 where he was also a Teaching Assistant in the department of Computer Science and Engineering. He has been a teaching assistant for Data Structures and Algorithms, C Programming, Object Oriented Programming, Pattern Recognition, Deep Learning, Data Science for Engineers, Database Management System, and Computer Network courses and laboratories.

Educational Qualifications 

  • 2023(Thesis Submitted) – Ph.D./CSE – IIITDM Kancheepuram
  • 2017 – M.E./CSE – SSN College of Engineering, Chennai 
  • 2015 – B.E./CSE – UCEN Nagercoil

 Research Areas

  • Medical Image Processing
  • Deep Learning
  • Machine Learning
  • Bioinformatics

Work Experience:

S. No Designation Department University/Institute Period 
1. Assistant Professor CSE SNU, Chennai June 2023 – Present 
2. Teaching Assistant CSE IIITDM Kancheepuram Jan 2018 – Dec 2022 

Journal Publications

  1. Adepu, A. K., Sahayam, S., Jayaraman, U., & Arramraju, R. (2023). Melanoma classification from dermatoscopy images using knowledge distillation for highly imbalanced data. Computers in Biology and Medicine154, 106571. (SCI, 2023, IF: 6.698) 
  2. Jacob, S. G., Sulaiman, M. M. B. A., Bennet, B., Vijayaraghavan, R., Sahayam, S., Thiviyakalyani, N., … & Hameed, T. (2022). A graphical approach for outlier detection in gene–protein mapping of cognitive ailments: an insight into neurodegenerative disorders. Network Modeling Analysis in Health Informatics and Bioinformatics, 11(1), 22. (Scopus, 2022) 
  3. Sahayam, S., Nenavath, R., Jayaraman, U., & Prakash, S. (2022). Brain tumor segmentation using a hybrid multi resolution U-Net with residual dual attention and deep supervision on MR images. Biomedical Signal Processing and Control, 78, 103939. (SCIE, 2022, IF: 5.076) 


  1. Adepu, A. K., Sahayam, S., Arramraju, R., & Jayaraman, U. (2022, November). A Study on an Ensemble Model for Automatic Classification of Melanoma from Dermoscopy Images. In International Conference on Computer Vision and Image Processing (pp. 637-651). Cham: Springer Nature Switzerland. 
  2. Sahayam, S., Silambarasan, J., & Jayaraman, U. (2021, December). Detection of Cataract from Fundus Images Using Deep Transfer Learning. In International Conference on Computer Vision and Image Processing (pp. 175-186). Cham: Springer International Publishing.
  3. Sahayam, S., Jayaraman, U., & Teja, B. (2021). Multi-class glioma classification from MRI images using 3d convolutional neural networks. In Computer Vision and Image Processing: 5th International Conference, CVIP 2020, Prayagraj, India, December 4-6, 2020, Revised Selected Papers, Part I 5 (pp. 327-337). Springer Singapore. 
  4. Sahayam, S., Abirami, A., & Jayaraman, U. (2020, December). A Novel Modified U-shaped 3-D Capsule Network (MUDCap3) for Stroke Lesion Segmentation from Brain MRI. In 2020 IEEE 4th Conference on Information & Communication Technology (CICT) (pp. 1-6). IEEE. (Best Paper Award) 
  5. Sahayam, S., Krishna, N. H., & Jayaraman, U. (2019, October). Brain Tumor Segmentation on MRI Images by Voxel Classification Using Neural Networks, and Patient Survival Prediction. In International MICCAI Brainlesion Workshop (pp. 284-294). Cham: Springer International Publishing. 


  1. Sahayam, S., Zakkam, J., & Jayaraman, U. (2023). Can we learn better with hard samples? arXiv preprint arXiv:2304.03486. 
  2. Charan, D. S., Nadipineni, H., Sahayam, S., & Jayaraman, U. (2020). Method to classify skin lesions using dermoscopic images. arXiv preprint arXiv:2008.09418. 

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