Projects per year
Personal profile
Biography
Dr Priyanka Rana is a Postdoctoral Research Fellow in the Centre for Health Informatics (CHI), Australian Institute of Health Innovation (AIHI). She received her PhD in Computer Science from UNSW Sydney in March 2023.
Her research focuses on developing Computer Vision, Machine and Deep Learning methodologies for analysing images to address various biomedical challenges. Through her previous studies, she has acquired expertise in different areas of AI, including multi-channel image analysis, data augmentation, model generalisation, imbalanced data, optimal feature representation, multi-instance learning and synthetic image generation.
2024:
- She received the highly competitive Macquarie Research Acceleration Scheme (MQRAS) grant in July 2024.
- She received funding through the Early Career Researcher Enabling Scheme in March 2024.
2023: She won the Early Career Researcher (ECR) Showcase Competition.
2019-2022: She received prestigious UNSW Women in Engineering scholarship and the Australian Government Research Training Program scholarship during her PhD.
Research interests
Her current project is on multiplex Immunofluorescent (mIF) images which are particularly distinguished by their large number of channels and the high cost of their generation. The project is in collaboration with Melanoma Institue of Australia and aims to improve understanding of immunotherapy responses in melanoma and contribute to personalized medicine using AI. Successful completion of this project will provide valuable insights into treatment strategies and advance cancer research.
Teaching and Leadership
Dr Priyanka has taught postgraduate and undergraduate courses in Computer Science covering topics such as Computer vision, Design thinking, Human-Computer tnteraction, Data mining, E-Strategic management, Algorithms and Data structures, and Android development.
October 2015 - June 2018 : Lecturer at James Cook University, Singapore:
• Related work: https://www.slideshare.net/PriyankaRana17/presentations.
• Additionally, responsible for the two-day design SPRINT session for design thinking modules and conducting audit interviews for the projects undertaken by the students.
Education/Academic qualification
Computer science, PhD, Analysis of Cellular and Subcellular Morphology using Machine Learning in Microscopy Images, UNSW
Mar 2019 → Dec 2022
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Collaborations and top research areas from the last five years
Projects
- 1 Active
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Enhancing the transportability of clinical AI to different settings
Coiera, E., Liu, S. & Rana, P.
1/01/22 → 31/12/26
Project: Research
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Analysis of cellular and subcellular morphology using machine learning in microscopy images
Rana, P., Mar 2023Research output: Thesis › Doctoral Thesis
File98 Downloads (Pure) -
Imbalanced classification for protein subcellular localization with multilabel oversampling
Rana, P., Sowmya, A., Meijering, E. & Song, Y., 1 Jan 2023, In: Bioinformatics. 39, 1, p. 1-7 7 p., btac841.Research output: Contribution to journal › Article › peer-review
Open AccessFile9 Citations (Scopus)127 Downloads (Pure) -
Data augmentation with improved regularisation and sampling for imbalanced blood cell image classification
Rana, P., Sowmya, A., Meijering, E. & Song, Y., 27 Oct 2022, In: Scientific Reports. 12, p. 1-13 13 p., 18101.Research output: Contribution to journal › Article › peer-review
Open AccessFile13 Citations (Scopus)114 Downloads (Pure) -
Imbalanced cell-cycle classification using WGAN-div and mixup
Rana, P., Sowmya, A., Meijering, E. & Song, Y., 28 Mar 2022, Proceedings of the 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). Piscataway, NJ: IEEE:Institute of Electrical Electronics Engineers Inc, p. 1-4 4 p. (IEEE International Symposium on Biomedical Imaging).Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
5 Citations (Scopus) -
Estimation of three-dimensional chromatin morphology for nuclear classification and characterisation
Rana, P., Sowmya, A., Meijering, E. & Song, Y., 9 Feb 2021, In: Scientific Reports. 11, p. 1-13 13 p., 3364.Research output: Contribution to journal › Article › peer-review
Open AccessFile3 Citations (Scopus)73 Downloads (Pure)
Prizes
Press/Media
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ECR – How AI is helping Melanoma patients with treatment
2/04/24
1 item of Media coverage
Press/Media: Public Engagement Activities