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Dr Debaditya Acharya

CERC Postdoctoral Fellow


Debaditya is working as a CSIRO Early Research Career (CERC) Postdoctoral Fellow, in CSIRO, where his work will contribute towards the Future Science Platforms (FSP) of Machine Learning & Artificial Intelligence (MLAI) and its applications to fisheries. Previously, he had worked as a postdoctoral research associate at RMIT University, Australia, working on projects related to food automation using computer vision and deep learning.

He completed his Doctor of Philosophy from the University of Melbourne, Australia, where he worked in the topic of visual sensing for indoor positioning, which aims at the development of an infrastructure-free indoor positioning technology that is suitable for mass implementation. He has worked in the field of object tracking and positioning in indoor environments, using computer vision and deep learning. His research works are published in international peer-reviewed journals and international conferences.

He completed Master of Technology in geoinformatics and natural resource engineering from IIT Bombay, India, where he has worked in the domains of geoinformatics, remote sensing, image processing, synthetic aperture RADAR (SAR) and digital photogrammetry. Previously he completed his Bachelor of Technology in mining engineering from IIEST, Shibpur, India. Before his masters, Debaditya worked for two years as assistant manager (mining) in an underground mine of Coal India Limited, where development was being practised by Continuous Miner. He aided the capital and revenue activities of the project and planning for the optimal functionality of the mine.

He is involved with a project for creating a benchmark dataset for comparing the errors of 3D modelling from point cloud data, resulting in the ISPRS benchmark for indoor modelling. His past project involvement includes modelling the Royal Exhibition Building using LiDAR data, under the University of Melbourne MSE2025 project. Previously, he has worked on a research engagement project with Queen Victoria Market. He developed a pedestrian tracking framework using CCTV data and liaised LiDAR data collection for creating a 3D model.