Professor Jagath Rajapakse

 

Description: Macintosh HD:Users:jagath:Google Drive:My Info:photos:IMG_0180a.jpeg

 

Jagath Rajapakse, PhD, FIEEE

Professor of Computer Engineering

School of Computer Science and Engineering

Nanyang Technological University

N4-2a11, 50 Nanyang Avenue

Singapore 639798

Email: asjagath@ntu.edu.sg, jagath.rajapakse@gmail.com

 Tel: 67905802, 93623027

 

 

*      Research positions

*      MEng and PhD Research Student Scholarships

*      Part-time positions for NTU undergrads

Jagath Rajapakse is Professor of Computer Engineering at the Nanyang Technological University (NTU), Singapore. He has BSc degree in Electronics and Telecommunication Engineering and MSc and PhD degrees in Electrical and Computer Engineering. He was Visiting Scientist to the Max-Planck Institute of Cognitive and Brain Sciences, Germany, and the National Institute of Mental Health, USA. He is Visiting Professor to the Department of Biological Engineering at Massachusetts Institute of Technology (MIT). He serves as Editor for Engineering Applications in Artificial Intelligence journal (IF = 6.212). He was Fulbright Scholar and is IEEE Fellow.

 

Professor Rajapakse’s  research works are in the areas of brain imaging, computational and systems biology, and machine and deep learning. He has published over 300 peer-reviewed research articles in high-impact journals and conferences. His research articles have been cited over 13,000 times. He was recently ranked among the top 2% scientists globally by Stanford Study. His current research focus on developing techniques and tools for diagnosis and treatment of brain diseases. He develops tools to detect and segment brain structures, lesions, and tumours from CT and MRI scans with deep learning technologies. He investigates the connectome from functional MRI and DTI scans for disease identification and biomarker discovery. He is also looking into how neuroimaging data can be integrated with multi-omics (genomics, proteomics, transcriptomics, and epigenomics) data for investigating neurological and psychiatric diseases.

 

TEACHING

CZ4042: Neural networks and deep learning

CE7412: Computational and systems biology

 

 

RECENT PUBLICATIONS

1.    Y. Chan, C. Wang, W. K. Soh, and J. C. Rajapakse, “Combining neuroimaging and omics datasets for disease classification using graph neural networks,” Frontiers of Neuroscience, IF = 4.677, 23 May 2022, DOI: https://doi.org/10.3389/fnins.2022.866666 

2.    S. Gupta, M. Lim, and J. C. Rajapakse, “Decoding task-specific and task-general architectures of the brain,” Human Brain Mapping, DOI:  http://doi.org/10.1002/hbm.25817

3.    S. Gupta, Y. H. Chen, and J. C. Rajapakse, “Obtaining leaner deep neural networks for decoding brain functional connectome in a single shot,” Neurocomputing, January, 2021, DOI: 10.1016/j.neucom.2020.04.152

4.    X. Zhong and J. C. Rajapakse, “Graph embeddings on gene ontology annotations for protein-protein interaction prediction,” BMC Bioinformatics, 21, 516, December 2020, DOI: 10.1186/s12859-020-03816-8

5.    S. Gupta and J. C. Rajapakse, “Iterative consensus spectral clustering improves detection of subject and group level brain functional modules,” Scientific Reports, 10: 7590, May 2020, DOI:10.1038/s41598-020-63552-0, IF = 4.011

6.    S. Gupta, J. C. Rajapakse, and R. E. Welsch, “Ambivert degree identifies crucial brain functional hubs and improves detection of Alzheimer’s disease and autism spectrum disorder,” NeuroImage: Clinical, Volume 25, 102186, Jan 2020, DOI: 10.1016/j.nicl.2020.102186, IF = 3.943

7.    L.-C. Tranchevent, F. Azuaje, and J. C. Rajapakse, “A deep neural network approach to predicting clinical outcomes of neuroblastoma patients,” BMC Medical Genomics, 12, 178, Dec 2019, DOI: 10.1186/s12920-019-0628-y, IF = 3.317

8.    R. Kaalia and J.C. Rajapakse, “Refining modules to determine functionally significant clusters in molecular networks,” BMC Genomics, 20: 901, Dec 2019, DOI: 10.1186/s12864-019-6294-9, IF = 3.730

9.    X. Zhong, R. Kaalia, and J. C. Rajapakse, “GO2Vec: transforming GO terms and proteins to vector representations using graph embeddings” BMC Genomics, 20: 918, Dec 2019, DOI: 10.1186/s12864-019-6272-2, IF = 3.730

10. S. Gupta, Y. H. Chen, and J. C. Rajapakse “Decoding brain functional connectivity implicated in AD and MCI,” MICCAI 2019, LNCS 11766, pp. 781–789, 2019, DOI: 10.1007/978-3-030-32248-9_87

11. K. Baum, J. C. Rajapakse, and F. Azuaje, “Analysis of correlation-based molecular networks from different omics data by fitting stochastic block models,” F1000Research, 8: 465, Aug 2019, DOI: 10.12688/f1000research.18705.2

12. W. Liu and J. C. Rajapakse, “Fusing gene expressions and transitive protein interactions for inference of gene regulatory networks,” BMC Systems Biology, 13(Suppl 2): 37, April 2019, DOI: 10.1186/s12918-019-0695-x, IF = 2.05

13. A. N. Barrett, C. Y. Fong, A. Subramanian, W. Liu, Y. Feng, M. Choolani, A. Biswas, J. C. Rajapakse, and A. Bongso, “Human Wharton’s jelly mesenchymal stem cells show unique expressions compared with bone marrow mesenchymal stem cells using single-cell RNA sequencing,” Stem Cells and Development, 28(3), Feb 2019, DOI: 10.1089/scd.2018.0132, IF = 3.315

14. R. Kaalia and J. C. Rajapakse, “Functional homogeneity and specificity of topological modules in human proteome,” BMC Bioinformatics, 19: 553, Feb 2019, DOI: 10.1186/s12859-018-2549-8, IF = 2.511

15. X. Sui and J. C. Rajapakse, “Profiling heterogeneity of Alzheimer’s disease using white matter impairment factors,” Neuroimage: Clinical, 20, pp. 1222 – 1232, Oct 2018, DOI: 10.1016/j.nicl.2018.10.026, IF = 4.348

16. W. Liu, J. Liu, and J. C. Rajapakse, “Gene ontology enrichment improves performances of functional similarity of genes,” Scientific Reports, 8: 12100, Aug 2018, DOI: 10.1038/s41598-018-30455-0 ,IF = 4.122

17. D. N. Wadduwage, J. Kay, V. R. Singh, O. Kiraly, M. R. Sukup-Jackson, J. C. Rajapakse, B. P. Engelward, and P. T. C. So, “Automated fluorescence intensity and gradient analysis enables detection of rare fluorescent mutant cells deep within the tissue of RaDR mice,” Scientific Reports, 8:12108, Aug 2018, DOI: 10.1038/s41598-018-30557-9, IF = 4.122, 

18. L.-C. Tranchevent, P. V. Nazarov, T. Kaoma, G. P. Schmartz, A. Muller, S.-Y. Kim, J. C. Rajapakse, and F. Azuaje, “Predicting clinical outcome of neuroblastoma patients using an integrative network-based approach,” Biology Direct, 13:12, June 2018, DOI:10.1186/s13062-018-0214-9, IF = 2.649

 

FUNDED RESEARCH PROJECTS

1.     “Software application for thermal image analytics,” $130,000 grant from Wonder Engineering Technologies, 04/04/2022 – 03/04/2024

2.    “Decoding the connectome by deep encoding on graphs,” AcRF Tier-2 Grant, Ministry of Education, Singapore, 02/02/2022 – 01/02/2025, $730,249.00

3.    “Developing unsupervised machine learning techniques for discovering novel ocular and brain imaging biomarkers of Alzheimer’s disease,” $169,000.00 grant from MSD International GMBH, 01/10/2021 – 31/09/2023

4.    Machine learning for demand forecasting,” $263,000.00 grant from Becton Dickinson Holding Pte. Ltd., 30/04/2021 – 29/04/2023

5.    “Multilayer networks for identification of biomarkers and prediction of clinical variables from multi-omics data,” AcRF Tier-1 Grant, Ministry of Education, Singapore, 01/05/2020 – 31/07/2021, $99,998.75

6.    “Detection of customer emotions and behaviour from speech,” Singtel-NTU Cognitive and Artificial Intelligence Joint Lab grant (IAF-ICP-RES 1-1.1), AStar and Singtel joint grant, 01/06/2018 – 30/05/2020, $390,593.00

7.    “Study of Alzheimer’s disease heterogeneity and progression using latent grey-matter atrophy and white-matter impairment factors,” AcRF Tier-1 RG149/17 Grant, Ministry of Education, Singapore, 01/03/2018 – 28/02/2020, $99,912.48

8.    “Predicting missing and spurious links and labels of protein-interaction networks,” AcRF Tier-2 Grant MOE2016-T2-1-029, Ministry of Education, Singapore, 09/01/2017 – 08/07/2020, $ 579,536.00

 

 

RESEARCH TEAM

Dr. Parvin Kumar, Wallenberg Postdoctoral Research Fellow

Mr. Anh Chung Soo, Research Associate

Mr. Yi Hao Chan, Ph.D. student

Mr. Soh Wei Kwek, Ph.D. student

Ms. Charlene Ong Zhi Lin, Ph.D. student

Mr. Chung Suhwan, Ph.D. student

Mr. Wang Conghao, Ph.D. student

Mr. Chun Hung How, M.Eng. student

Mr. Shreyas Goyal, M.Eng. student

 

 

PHD STUDENT AND VISITING RESEARCH POSITIONS

For PhD applicants and Visiting Scientist positions, kindly email your interests and CV to Professor Jagath Rajapakse (asjagath@ntu.edu.sg).

 

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Last updated on 30/04/2022