Jiangning is a Professor and Group Leader in the Cancer and Infection and Immunity Programs in the Monash Biomedicine Discovery Institute (BDI), and Department of Biochemistry and Molecular Biology, School of Biomedical Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, Australia. As a highly accomplished bioinformatician and data-driven scientist, he specializes in cutting-edge areas such as Artificial Intelligence, Bioinformatics, Comparative Genomics, Cancer Genomics, Bacterial Genomics, Computational Biomedicine, Data Mining, Infection and Immunity, Machine Learning, Proteomics, and Biomedical Big Data Analytics. His expertise is highly sought after in the rapidly evolving field of data-driven biomedical research, where he is recognized for his ability to bridge computational innovation with biomedical discovery.

He is Director of the AI-driven Bioinformatics and Biomedicine Laboratory in the Monash BDI and an Associate Investigator of the ARC Centre of Excellence in Advanced Molecular Imaging. He is also a member of the Monash Data Futures Institute (MDFI), Alliance for Digital Health at Monash (ADAM) and Center to Impact Antimicrobial Resistance (AMR). His research focuses on leveraging heterogeneous data modeling, advanced machine learning and analytics to address critical challenges in infection and immunity, cancer biology, and pharmaco-informatics.

Professor Song is an active contributor to the scientific community, serving as an Associate Editor for several top-tier journals, including IEEE Journal of Biomedical and Health Informatics, BMC Bioinformatics, Genomics, Proteomics & Bioinformatics, Frontiers in Bioinformatics, and BMC Genomic Data. Additionally, he serves on the editorial boards of Computers in Biology and Medicine, Biomolecules, Protein & Peptide Letters, and The Innovation Life, and as a Guest Editor for prestigious journals such as Genome Biology, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Current Bioinformatics, and BMC Genomics. His leadership extends to organizing international conferences, including serving as Program Committee Co-Chair for the 30th International Conference on Genome Informatics (GIW) and the Australian Bioinformatics and Computational Biology Society (ABACBS) Annual Conference in 2019, and the 10th International Conference on Bioscience, Biochemistry and Bioinformatics (ICBBB) in 2020.

Prof Song holds honorary positions as Professor at the Bioinformatics Center, Institute for Chemical Research and is an International Expert Committee member on Bioinformatics, the International Joint Usage/Research Center (iJURC), Kyoto University, Japan. He is also an Honorary Professor within the Faculty of Science, the University of Melbourne. He is also a founding member of Monash University's Centre to Impact AMR, where he chairs the Bioinformatics and Computational Biomedicine Group, driving the development of AMR Big Data and AI-driven research capabilities.

Jiangning is a PC member for more than 20 international conferences on bioinformatics, computational biology, health informatics, and e-Science, including BIBM, IEEE e-Science, InCoB, ISB, ICPB, ICIC, IIBM, GIW and AAAI. He is an invited reviewer for >60 journals (on average 50-80 reviews per year) in bioinformatics, computational biology, machine learning, data mining, systems biology, and chemoinformatics, including top-tier journals Cell, Nature Biotechnology, Nature Methods, Nature Machine Intelligence, Nature Biomedical Engineering, Nature Chemical Biology, Nature Computational Science, Nature Communications, Nucleic Acids Res, Genome Biology, Briefings in Bioinformatics, Bioinformatics, iScience, Cell Reports Medicine, IEEE Journal of Biomedical and Health Informatics, PLoS Comput Biol, Neurocomuting, Pattern Recog, Neurocomputing, BMC Bioinformatics, IEEE/ACM Trans Comput Biol and Bioinform, and J Chem Info Model.

As Chief Investigator, he has secured over 35 grants (~$20.0M, 25 as CIA/CIB), funded by prestigious organzations such as the US NIH, Australian MRFF/NHMRC/ARC, and other granting bodies (e.g. the Japan Society for the Promotion of Science [JSPS], the Ministry of Science and Technology of  China [MOST], the Chinese Academy of Sciences [CAS] and the National Natural Science Foundation of China [NSFC], Monash University, Kyoto University and The University of Tokyo). Remarkably, he secured a major five-year NIH R01 project (CIB, AI111965, US$4.56 million) with the program lead Professor Jian Li FAA FAHMS at Monash University and other US collaborators to develop cutting-edge systems pharmacology approaches for predicting and validating antibiotic/small-molecule non-antibiotic combinations for new targeted therapies for treating life-threatening infections caused by antibiotic-resistant bacterial 'superbugs'. His recent work with Prof Tatsuya Akutsu at Kyoto University on developing novel bioinformatic algorithms for identifying novel substrates of apoptotic caspases and limited proteolysis has been recognised and awarded three consecutive Collaborative Research grants by Kyoto University, Japan. More recently, he has been awarded an International Joint Research grant in collaboration with Prof Seiya Imoto by the Institute of Medical Science of the University of Tokyo (IMSUT) to conduct collaborative research in the frontier of interdisciplinary research in human genomic data analytics.

Jiangning is motivated to investigate, develop, and deploy cutting-edge bioinformatics methodologies to better understand and address a range of open and challenging problems in genomics, molecular biology, and systems biology. To date, he and his team members have developed 60+ bioinformatics toolkits/webservers/software to serve the wider research community, including PROSPERous, iFeature, iFeatureOmega, iProt-Sub, Quokka, Muscadel, iLearn, iLearnPlus, Procleave, and DeepCleave. Many of these tools have been highlighted as useful bioinformatic tools and have been widely used by the international research community. The high impact of these tools signifies how biomedical knowledge discovery can indeed be alternatively catalysed by data-driven machine-learning techniques.

A career is a journey. With a unique interdisciplinary background spanning fermentation engineering, applied mathematics, computer science, and systems biology, Professor Song is uniquely positioned to tackle large-scale biomedical data challenges in the era of Data Science and Analytics. His career reflects a commitment to lifelong learning, epitomized by Monash University's motto - "Ancora Imparo" ("I am still learning").  He has had the privilege of collaborating with renowned scientists, including ARC Australian Federation/Laureate Fellows Prof Kevin Burrage (The University of Queensland & University of Oxford), Prof James Whisstock (Monash), Prof Trevor Lithgow (FAA, Monash), Prof Jamie Rossjohn (FRS, FAA, Monash), and Prof Geoff Webb (IEEE Fellow, Monash) as his collaborators or supervisors throughout his academic career, further enriching his research journey.

Outside of academia, Professor Song enjoys spending time with his family, exploring the natural beauty of the Dandenong Ranges and Mornington Peninsula, and indulging in music and movies. His work has been featured in several Monash University stories, highlighting his team’s groundbreaking interdisciplinary research.

If you are interested in his research, you might want to read the following Monash featured stories that report on his team and collaborators' most-recent interdisciplinary research:

https://www.monash.edu/discovery-institute/news-and-events/news/2024-articles/t-cell-breakthrough-a-step-towards-personalised-medicine-to-prevent-disease

https://lens.monash.edu/@jiangning-song/2024/10/29/1387131/t-cell-breakthrough-a-step-towards-personalised-medicine-to-prevent-disease

https://www.monash.edu/discovery-institute/news-and-events/news/2023-articles/developing-ai-to-help-identify-at-risk-bowel-cancer-patients

https://www.monash.edu/it/news/2023/boost-for-a-digital-health-revolution

https://www.monash.edu/data-futures-institute/news/mdfi-seed-grants-to-foster-international-partnerships-in-ai-for-good

https://www.monash.edu/data-futures-institute/research/mdfi-flagship-projects/ai-and-smart-drug-design-against-superbugs

https://www.monash.edu/impact-amr/case-studies-and-stories/antimicrobial-resistance-evolves-quickly,-and-we-need-to-be-prepared

https://www.monash.edu/medicine/news/latest/2020-articles/funding-for-fight-against-superbugs

https://www.monash.edu/discovery-institute/news-and-events/news/2019-articles/combating-superbugs-with-ai-and-big-data

https://www.monash.edu/medicine/discovery-institute/news-and-events/news/new-tool-to-speed-up-translation-of-genome-sequences

https://research.monash.edu/en/clippings/bioinformatics-tool-to-unearth-new-pointers-to-disease

University ranking: Monash University is one of Australia’s group of eight - the most research-intensive universities in the country - and consistently ranks among the world's top 50 universities (QS World University Rankings: 36th; US News Best Global Universities Rankings: 38th;  Times Higher Education World University Rankings: 58th; CWTS Leiden World: 49th; Academic Ranking of World Universities, i.e. ShanghaiRanking: 75th); Top 1 QS World University Rankings of Pharmacy & Pharmacology, Top 32th QS World University Rankings of Medicine. Monash has an international reputation for interdisciplinary research with an emphasis on global issues.

If you would like to learn more about his research or explore potential collaboration opportunities, please contact [email protected].  Prospective postgraduate students, both in Australia and internationally, who are interested in pursuing a Ph.D. under Professor Song’s mentorship at Monash University are also encouraged to reach out.

Professor Jiangning Song is a dedicated Ph.D. mentor, supervisor, and examiner at Monash University. He currently supervises 12 Ph.D. students (6 as primary supervisor) across diverse research areas, including bioinformatics, computational biomedicine, medical imaging, machine learning, multi-omics data analysis, and multimodal data modeling. To date, he has successfully supervised 11 Ph.D. and 3 master’s students to completion at Monash University. He also chairs or serves on the review committees for 6 Ph.D. students, providing guidance and expertise to shape the next generation of researchers.

His graduates have gone on to achieve remarkable success, with some receiving prestigious ARC Future Fellowship, NHMRC Emerging Leadership, NHMRC CJ Martin Overseas Fellowship, and others securing leadership roles in both academia and industry. Approximately 70% of his graduates now work in industry, while 30% have pursued academic careers, reflecting the versatility and impact of his mentorship.

Professor Song is passionate about fostering innovation and excellence in his students, equipping them with the skills and knowledge to tackle complex challenges in bioinformatics and biomedicine. If you are driven by a passion for cutting-edge research and aspire to make a meaningful impact in these fields, Professor Song’s lab offers an inspiring and collaborative environment to achieve your goals.