STAFF PROFILE
Dr Tabinda Sarwar
Position:
Lecturer
College / Portfolio:
STEM College
School / Department:
STEM|School of Computing Technologies
Email:
tabinda.sarwar@rmit.edu.au
Campus:
City Campus
Contact me about:
Research supervision
1 PhD Completions4 PhD Current Supervisions
- Sarwar, T.,Ramamohanarao, K.,Daducci, A.,Schiavi, S.,Smith, R.,Zalesky, A. (2023). Evaluation of tractogram filtering methods using human-like connectome phantoms In: NeuroImage, 281, 1 - 12
- Sarwar, T.,Seifollahi, S.,Chan, J.,Zhang, X.,Aksakalli, V.,Hudson, I.,Verspoor, K.,Cavedon, L. (2022). The Secondary Use of Electronic Health Records for Data Mining: Data Characteristics and Challenges In: ACM Computing Surveys, 55, 1 - 36
- Sultana, N.,Chan, J.,Sarwar, T.,Qin, A. (2022). Learning to optimise general TSP instances In: International Journal of Machine Learning and Cybernetics, , 1 - 16
- Sarwar, T.,Jimeno Yepes, A.,Zhang, J.,Chan, J.,Hudson, I.,Evans, S.,Cavedon, L. (2022). Development and validation of retrospective electronic frailty index using operational data of aged care homes In: BMC Geriatrics, 22, 1 - 11
- Sarwar, T.,Tian, Y.,Yeo, B.,Ramamohanarao, K.,Zalesky, A. (2021). Structure-function coupling in the human connectome: A machine learning approach In: NeuroImage, 226, 1 - 11
- Sarwar, T.,Ramamohanarao, K.,Zalesky, A. (2021). A critical review of connectome validation studies In: NMR in Biomedicine, 34, 1 - 18
- Sultana, N.,Chan, J.,Sarwar, T.,Qin, K. (2021). Learning to Optimise Routing Problems using Policy Optimisation In: Proceedings of the 2021 International Joint Conference on Neural Networks (IJCNN 2021), Shenzhen, China, 18-22 July 2021
- Drobnjak, I.,Neher, P.,Poupon, C.,Sarwar, T. (2021). Physical and digital phantoms for validating tractography and assessing artifacts In: NeuroImage, 245, 1 - 20
- Zalesky, A.,Sarwar, T.,Ramamohanarao, K. (2020). A cautionary note on the use of SIFT in pathological connectomes In: Magnetic Resonance in Medicine, 83, 791 - 794
- Sarwar, T.,Seguin, C.,Ramamohanarao, K.,Zalesky, A. (2020). Towards deep learning for connectome mapping: A block decomposition framework In: NeuroImage, 212, 1 - 17