Debaditya Acharya

Debaditya is a Lecturer in Geospatial Science at RMIT University and teaches Remote Sensing and Photogrammetry. His research interests are computer vision, machine learning, and 3D building modelling.

Previously, Debaditya worked as a CSIRO Early Research Career (CERC) Postdoctoral Fellow, CSIRO, where his work contributed to the Future Science Platforms (FSP) of Machine Learning & Artificial Intelligence (MLAI) and its applications to fisheries, especially anomaly detection using Spatio-temporal modeling, deep learning, and computer vision. Also, he 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 on the topic of visual sensing for indoor positioning, which aims at the development of an infrastructure-free indoor positioning technology using 3D building models. 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 contributed to a project for creating a benchmark dataset for comparing the errors of 3D modeling from point cloud data, resulting in the ISPRS benchmark for indoor modeling. His past project involvement includes modeling the Royal Exhibition Building using LiDAR data, under the University of Melbourne MSE2025 project. Previously, he worked on a research engagement project with Queen Victoria Market and developed a pedestrian tracking framework using CCTV data, and liaised with LiDAR data collection for creating a 3D model.

Industry experience:
- CSIRO Early Research Career Postdoctoral Fellow | Machine Learning and Artificial Intelligence (MLAI) Future Science Platform (FSP) | CSIRO
- Postdoctoral Research Associate | RMIT University