deshan@workstation ~/portfolio % cat about.txt

I’m currently pursuing a PhD in Computer Vision and Artificial Intelligence at the School of Computer Science and Engineering, University of New South Wales (UNSW) in Sydney, Australia. My research is dedicated to developing AI-based methods for the efficient analysis and interpretation of medical imagery, with a particular focus on colorectal diseases.

Prior to starting my doctoral studies, I was part of a multidisciplinary research team in Sri Lanka exploring applications of Optical Coherence Tomography (OCT) across various domains. In 2024, I completed my MPhil at the University of Sri Jayewardenepura, where I investigated the use of OCT imaging to detect circular leaf spot disease in persimmon by analyzing leaf microstructures. During that time, I also had the opportunity to collaborate with a group working on MRI-based brain cancer analysis, which deepened my appreciation for medical-image-driven AI solutions.

My broader interests center around artificial intelligence and computer vision, especially their applications in healthcare. I’m passionate about creating AI-driven systems that can interpret complex medical data rapidly and accurately, with the ultimate goal of supporting better diagnostics and improving patient outcomes worldwide.

deshan@workstation ~/portfolio % cat education.txt

- PhD, School of Computer Science and Engineering, UNSW Sydney, Australia (2024 Oct - Present)

- MPhil, Faculty of Engineering, University of Sri Jayewardenepura, Sri Lanka (2021 Oct - 2024 Aug)

- BScEng (Hons), Faculty of Engineering, University of Peradeniya, Sri Lanka (2014 Jan - 2017 Oct)

deshan@workstation ~/portfolio % cat experience.txt

- Casual Acedemic, School of Computer Science & Engineering, UNSW Sydney, Australia (2025 Feb - Present)

- Lecturer, Faculty of Engineering, University of Sri Jayewardenepura, Sri Lanka (2021 Sept - 2024 Oct)

- Instructor, Faculty of Engineering, University of Sri Jayewardenepura, Sri Lanka (2019 Dec - 2024 Aug)

- Visiting Lecturer, ICBT Campus , Sri Lanka (2023 Sept - 2024 Sept)

- Visiting Lecturer, APIIT, Sri Lanka (2022 Nov - 2023 Mar)

- Software Engineer, WSO2, Sri Lanka (2017 Nov - 2018 Jun)

- System and Network Engineer (Intern), IBM World Trade Corporation, Sri Lanka (2016 Oct - 2017 Mar)

deshan@workstation ~/portfolio % cat research.txt

- AI-Driven Analysis of Colorectal Diseases Using Computer Vision and Machine Learning:
The development of advanced, AI-driven methods for the analysis of colorectal diseases is the primary focus of my PhD research. This work involves applying computer vision and machine learning techniques to improve the accuracy, efficiency, and interpretability of medical image analysis in colorectal disease diagnostics. This research is being conducted at CSE UNSW Sydney, under the supervision of Prof. Arcot Sowmya, Dr. Sonit Singh, and Dr. Praveen Ravindran .

- Optical Coherence Tomography (OCT) Applications:
Focused on applying Optical Coherence Tomography (OCT) and deep learning for non-invasive plant disease detection. The thesis, titled "A Deep Learning Approach for the Automated Pre-identification and Analysis of Circular Leaf Spot Disease in Persimmon Using Optical Coherence Tomography Images," involved developing an AI-based approach for early detection of circular leaf spot disease in persimmon. This work carried out at the Faculty of Engineering, University of Sri Jayewardenepura, under the supervision of Dr. Udaya Wijenayake and Dr. Ruchire Eranga Wijesinghe.

- MRI-Based Brain Tumor Analysis Using Machine Learning:
Research focused on analyzing brain tumors using diffusion-weighted MRI, with an emphasis on Apparent Diffusion Coefficient (ADC) images. Demographic and texture features were extracted to identify distribution patterns, and machine learning techniques were applied to classify tumors as malignant or benign. The study was carried out at the University of Peradeniya.

deshan@workstation ~/portfolio % cat publications.txt

- Kalupahana, D., Kahatapitiya, N.S., Kamalathasan, D., Wijesinghe, R.E., Silva, B.N. and Wijenayake, U., 2024. State-of-the-art of deep learning in multidisciplinary optical coherence tomography applications . IEEE Access.

- Kalupahana, D., Kahatapitiya, N.S., Silva, B.N., Kim, J., Jeon, M., Wijenayake, U. and Wijesinghe, R.E., 2024. Dense convolutional neural network-based deep learning pipeline for pre-identification of circular leaf spot disease of diospyros kaki leaves.

- Kahatapitiya, N.S., Kalupahana, D., Mohamed, H., Silva, B.N., Wijenayake, U., Han, S., Seong, D., Jeon, M., Kim, J. and Wijesinghe, R.E., 2024. Detection of Peak Intensity Using an Integrated Optical Modeling Method for Identifying Defective Apple Leaves. Engineering Proceedings, 82(1), p.45.

- Vijithananda, S.M., Jayatilake, M.L., Gonçalves, T.C., Rato, L.M., Weerakoon, B.S., Kalupahana, T.D., Silva, A.D., Dissanayake, K. and Hewavithana, P.B., 2023. Texture feature analysis of MRI-ADC images to differentiate glioma grades using machine learning techniques. Scientific Reports, 13(1), p.15772.

All publications -> Google Scholar