Professor Jagath
Rajapakse
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
*
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).
------
Last updated on 30/04/2022