Projects per year
Personal profile
Biography
Dr. Susmita Saha is a distinguished Research Fellow at the Turner Institute of Brain and Mental Health, School of Psychological Sciences, Monash University. She is also working with the iBRAIN group, Department of Neuroscience. In this role, she is responsible for leading the analysis of human structural and susceptibility MRI in neurological diseases as part of TRACK-FA, a world-first, international multi-modal longitudinal neuroimaging study that aims to identify sensitive, clinical trial ready, neuroimaging biomarkers for Friedreich’s ataxia (FRDA). She is leading two other AI projects utilising TRACK-FA data, as a chief investigator.
Her research focus is on utilising artificial intelligence (AI) in the healthcare industry, with an emphasis on medical imaging of neurological disorders. Saha has contributed significantly to the field of AI in healthcare by addressing medical challenges using novel machine learning and deep learning techniques, including predicting the likelihood of neurodevelopmental disorders in preterm infants, predicting epileptic seizure and associated treatment outcomes. She is currently passionate about applying AI to neurodegenerative disorders like hereditary cerebellar ataxia including Friedreich Ataxia.
Prior to this role, Dr. Susmita was a Postdoctoral Fellow of CSIRO (Commonwealth Scientific and Industrial Research Organisation) (2018-2021) and worked as a Postdoctoral Researcher at IBM Research Australia during 2015-2017 with the Brain Inspired Computing team.
Dr. Susmita Saha achieved her PhD in May 2016 in Biomedical engineering, The University of Melbourne. The study was conducted as part of the 'Bionic Eye' project in collaboration with Department of Electrical and Electronics Engineering, Department of Anatomy and Neuroscience, The University of Melbourne, National Vision Research Institute, Melbourne, and Bionic Vision Australia. The project involved investigation of synaptic circuitry associated with retinal output neurons in health and disease
She has secured over $300k in funding from internal grants and philanthropy (Friedreich's Ataxia Research Alliance, USA), with renowned domestic and international collaborators. Saha has published 20 high-quality peer-reviewed journal and conference articles and holds six patents. She is actively involved in community and leadership activities, serving as Secretary of IEEE Victorian Section. She has been recognised for outstanding contributions, receiving the IEEE Outstanding Volunteer Award 2022 and the Outstanding Event/Initiative Award 2022 for her work in the IEEE Women in Engineering International Leadership Summit 2022.
Saha's significant research contributions stem from her innovative approach and expertise in multidomain and multimodal biomedical data analysis, specialising in AI techniques. Her productive and collaborative approach, coupled with her leadership experience, has allowed her to make significant strides in the field.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
Biomedical Engineering, PhD, University of Melbourne
Award Date: 1 May 2016
External positions
Assistant Secretary, IEEE Victorian section
1 Jan 2022 → …
Research area keywords
- Medical Image Analysis, Artificial Intelligence applications in healthcare, Biomedical Data Processing, Neurological/NeuroDevelopmental Diseases, Computational Neuroscience
Collaborations and top research areas from the last five years
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Deriving Functional MRI Equivalent Biomarkers in Friedreich Ataxia Solely Using Brain Structure Data
Saha, S., Cao, T., Naeije, G., Noman, F., Karistianis, N. & Fornito, A.
Friedreich's Ataxia Research Alliance (United States of America)
1/09/24 → 31/08/25
Project: Research
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An optimized deep learning-based method for cerebellum segmentation
Rezende, T., Harding, I., Saha, S., Muro Martinez, A. R., Hideki Shiraishi, D., França Jr, M. C. & Cendes, F.
13/03/23 → 28/02/25
Project: Research
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Prognostic enrichment for early-stage Huntington's disease: An explainable machine learning approach for clinical trial
Ghofrani-Jahromi, M., Poudel, G. R., Razi, A., Abeyasinghe, P. M., Paulsen, J. S., Tabrizi, S. J., Saha, S. & Georgiou-Karistianis, N., Jan 2024, In: NeuroImage: Clinical. 43, 11 p., 103650.Research output: Contribution to journal › Article › Research › peer-review
Open Access2 Citations (Scopus) -
Early brain morphometrics from neonatal MRI predict motor and cognitive outcomes at 2-years corrected age in very preterm infants
Pagnozzi, A. M., van Eijk, L., Pannek, K., Boyd, R. N., Saha, S., George, J., Bora, S., Bradford, D. K., Fahey, M., Ditchfield, M., Malhotra, A., Liley, H., Colditz, P. B., Rose, S. & Fripp, J., 15 Feb 2023, In: NeuroImage. 267, 10 p., 119815.Research output: Contribution to journal › Article › Research › peer-review
Open Access9 Citations (Scopus) -
Social media bot detection with deep learning methods: a systematic review
Hayawi, K., Saha, S., Masud, M. M., Mathew, S. S. & Kaosar, M., Apr 2023, In: Neural Computing and Applications. 35, 12, p. 8903-8918 16 p.Research output: Contribution to journal › Review Article › Research › peer-review
Open Access30 Citations (Scopus) -
Predicting fluid intelligence in adolescence from structural MRI with deep learning methods
Saha, S., Pagnozzi, A., Bradford, D. & Fripp, J., Sept 2021, In: Intelligence. 88, 10 p., 101568.Research output: Contribution to journal › Article › Research › peer-review
7 Citations (Scopus) -
An effective approach for high-resolution 3D MRI reconstruction on highly motion-corrupted neonatal data
Saha, S., Pagnozzi, A., George, J., Colditz, P., Rose, S., Bradford, D., Boyd, R., Pannek, K. & Fripp, J., Sept 2020, In: Developmental Medicine & Child Neurology. 62, S3, p. 83 1 p., SP09.Research output: Contribution to journal › Meeting Abstract › peer-review