Have a Question about JIIT?
Chat with VIDYA
+91-9999912862+91-9999962128
searchImportant Announcements:
PhD Admission Result-Odd Sem 2026Click HereRegistration instructions & other details 1st year (UG & PG Programs) to report as per Admission Letter issued.View HereList of Hostellers - 1st Year (as on 28 July)View HereCareer OpeningsApply

Academic Experts

Jiddu Krishnan OP

Biography

Jiddu Krishnan O P is a Ph.D. Scholar in the Department of Computer Science and Engineering at 
the National Institute of Technology Silchar, India, where he has submitted his thesis. He obtained his 
B.Tech. in Computer Science from Vellore Institute of Technology (VIT), Vellore, followed by an 
M.Tech. in Computer Science from the College of Engineering Trivandrum (CET). He qualified both 
the GATE (2018) and UGC-NET (2019) examinations. His doctoral research focuses on the develop
ment of artificial intelligence and deep learning methodologies for automated pulmonary nodule de
tection, segmentation, diagnosis, and characterization from computed tomography (CT) images. 
His research interests encompass medical image analysis, computer vision, explainable artificial intel
ligence, trustworthy machine learning, and healthcare analytics. His work involves the development of 
novel deep learning architectures, hybrid radiomic models, calibration techniques, explainability 
frameworks, and reproducible AI pipelines for clinical decision support.

Areas of Interest
  • Medical Image Analysis
  • Artificial Intelligence & Deep Learning
  • Computer Vision
  • Explainable and Trustworthy AI
  • Healthcare Data Analytics
Publications

J. Krishnan O. P. and P. Roy, "Structured Residual Attention for Pulmonary Nodule Detection: A Candidate-Based 3D Detector with Hard-Negative Mining," Pattern Analysis and Applications, Springer, 2026.  

J. Krishnan O. P. and P. Roy, "Enhanced Pulmonary Nodule Segmentation via Radial-Attention U-Net with Delaunay TV Regularisation," Engineering Research Express, vol. 7, 2025.  

J. Krishnan O. P. and P. Roy, "Hybrid Radiomic–HOG Ensemble Model for Accurate Pulmonary Nodule Diagnosis," Biomedical Physics & Engineering Express, vol. 11, 2025.  

J. Krishnan O. P. and P. Roy, "A Survey on Lung Cancer Diagnosis Using Deep Learning Techniques," CRC Press, 2024.  

J. Krishnan O. P. and P. Roy, "WatershedSE-UNet: A Hybrid Deep Learning and Morphological Approach for Lung Nodule Segmentation in CT Scans," Proceedings of the 3rd International Conference on Microwave, Optical and Communication Engineering, 2025.