Dr Matloob Khushi

Conjoint Lecturer
Children's Medical Research Institute (CMRI)
Associate Lecturer In Data Science
School of Information Technologies

J12 - The School of Information Technologies
The University of Sydney


Website School of Information Technologies

Biographical details

Dr. Khushi received his Ph.D. from the University of Sydney under the supervision of Professor Christine Clarke and Dr. Dinny Graham. His thesis title was development of novel software tools and methods for investigating the significance of overlapping transcription factor genomic interactions. He has 17 years of experience in data science and software algorithms.

Research interests

Data is everywhere these days, and more is being produced at an exponential rate. Much of this so-called "big data" can be considered junk until it is analysed by sophisticated computational algorithms to reveal its compelling story. This is the focus of Dr Matloob Khushi's research.

"Big data comes in all shapes and sizes, including videos, images, financial data, medical and genomic data. My research looks at developing novel methods of analysing and managing it to unveil patterns that were not visible by applying previously known methods.

"The applications are endless, including in health, agriculture, banking, education and robotics. It's very exciting to me that the effective analysis of these ubiquitous large datasets holds the potential to improve people's lives.

"For example, by analysing and learning from big data, we can design a health-assisting gadget that can alert someone when they need to see a doctor, or an artificial intelligence-based financial agent that can advise people on where and how to invest.

"Many research laboratories already study their own internally produced datasets, but my research focuses on the integrated analysis of publicly available large datasets from cross-laboratory sources, which can potentially reveal some very interesting patterns.

"For example, my research in this area has unveiled previously unknown molecular interactions between oestrogen and progesterone receptors in regulating breast cancer, interactions that were later experimentally confirmed by another lab.

"One of my future aims is to develop novel efficient machine learning methods to analyse and manage large datasets of any nature.

"I joined the University of Sydney as a data scientist in 1998 while also completing my PhD here. After a post-doctoral fellowship and a lot of further research, I joined the School of Information Technologies in 2017.

"The University of Sydney is home to many world-leading researchers, and I consider myself fortunate to be surrounded and inspired by such people. I hope to contribute further towards the University's world-leading position in research."

Teaching and supervision

COMP5310 - Principles of Data Science

In the media

    Keywords

    Machine Learning; Bioinformatics

    Selected publications

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    Journals

    • Khushi, M., Napier, C., Smyth, C., Reddel, R., Arthur, J. (2017). MatCol: A tool to measure fluorescence signal colocalisation in biological systems. Scientific Reports, 7(1), 1-9. [More Information]
    • Khushi, M. (2015). Benchmarking database performance for genomic data. Journal Of Cellular Biochemistry, 116(6), 877-883. [More Information]
    • Khushi, M., Liddle, C., Clarke, C., Graham, J. (2014). Binding Sites Analyser (BiSA): Software for Genomic Binding Sites Archiving and Overlap Analysis. PloS One, 9(2), 1-12. [More Information]
    • Khushi, M., Clarke, C., Graham, J. (2014). Bioinformatic analysis of cis-regulatory interactions between progesterone and estrogen receptors in breast cancer. PeerJ, 2, 1-20. [More Information]
    • Khushi, M., Edwards, G., de Marcos, D., Carpenter, J., Graham, J., Clarke, C. (2013). Open source tools for management and archiving of digital microscopy data to allow integration with patient pathology and treatment information. Diagnostic Pathology, 8(1), 1-7. [More Information]
    • Khushi, M., Carpenter, J., Balleine, R., Clarke, C. (2012). Electronic Biorepository Application System: Web-Based Software to Manage Receipt, Peer Review, and Approval of Researcher Applications. Biopreservation and Biobanking, 10(1), 37-44. [More Information]

    2017

    • Khushi, M., Napier, C., Smyth, C., Reddel, R., Arthur, J. (2017). MatCol: A tool to measure fluorescence signal colocalisation in biological systems. Scientific Reports, 7(1), 1-9. [More Information]

    2015

    • Khushi, M. (2015). Benchmarking database performance for genomic data. Journal Of Cellular Biochemistry, 116(6), 877-883. [More Information]

    2014

    • Khushi, M., Liddle, C., Clarke, C., Graham, J. (2014). Binding Sites Analyser (BiSA): Software for Genomic Binding Sites Archiving and Overlap Analysis. PloS One, 9(2), 1-12. [More Information]
    • Khushi, M., Clarke, C., Graham, J. (2014). Bioinformatic analysis of cis-regulatory interactions between progesterone and estrogen receptors in breast cancer. PeerJ, 2, 1-20. [More Information]

    2013

    • Khushi, M., Edwards, G., de Marcos, D., Carpenter, J., Graham, J., Clarke, C. (2013). Open source tools for management and archiving of digital microscopy data to allow integration with patient pathology and treatment information. Diagnostic Pathology, 8(1), 1-7. [More Information]

    2012

    • Khushi, M., Carpenter, J., Balleine, R., Clarke, C. (2012). Electronic Biorepository Application System: Web-Based Software to Manage Receipt, Peer Review, and Approval of Researcher Applications. Biopreservation and Biobanking, 10(1), 37-44. [More Information]

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