Mr Sonit   Singh
Postdoctoral Fellow

Mr Sonit Singh

Sch: Computer Science & Eng

Sonit Singh is a Postdoctoral Research Fellow in the School of Computer Science and Engineering at the University of New South Wales (UNSW), Sydney, Australia. Before joining UNSW, he did his PhD degree at Macquarie University, in collaboration with Macquarie University Hospital and Data61, CSIRO. His PhD thesis entitled “Multimodal Machine Learning for Medical Imaging” focused on developing multimodal machine learning models at the intersection of Computer Vision and Natural Language Processing that can jointly reason on medical images and radiology reports. Before this, he completed the Master of Research degree in Natural Language Processing and Machine Learning at Macquarie University in 2017. His Masters thesis entitled "Generalizing Link Prediction for Information Extraction" focused on extending knowledge graphs reasoning from triplets to n-ary relations. He received the Bachelor of Technology in Electronics and Communication Engineering from Lovely Professional University (India) in 2011. During his PhD and Masters, he was supported by an international Macquarie University Research Excellence scholarship and the Data61 CSIRO top-up scholarship.

Sonit Singh is also very passionate about learning and teaching. He has been actively teaching various computer science and engineering courses since 2011. Back in India, he taught various courses in Electronics Engineering, including Artificial Intelligence, Computer Vision, Robotics and Automation, Neural Networks and Fuzzy Logic, Electronic Devices and Circuits. After joining Department of Computing, Macquarie University in 2017, he had the opportunity to do lecturing and tutoring Data Structures and Algorithms, Data Science, Artificial Intelligence, Document Processing and Semantic Web, and Machine Learning units. In August 2021, he joined UNSW and is teaching Computer Vision course in Term 3, 2021.

Sonit Singh has broad interests in Artificial Intelligence, Computer Vision, Natural Language Processing, Machine Learning, Deep Learning, Medical Imaging, and their intersections. Other research projects towards which he is highly inclined include Image Captioning, Visual Question Answering, Visual Dialog, and Visual-Language Navigation. Overall, Sonit Singh is passionate about teaching humans and machines. His research answers questions that impact clinical practice and patient outcomes.

412-07, K17 Building School of Computer Science and Engineering

I feel honored to receive the following awards:

  • 2021: Highly Commended Finalist for 2021 Vice Chancellor's Learning and Teaching Awards at Macquarie University
  • 2019: Awarded Postgraduate Research Fund (PGRF) in the Department of Computing, Macquarie University
  • 2019: Awarded Data61, CSIRO top-up scholarship (Duration: 3 years; AUD 10,000 per annum)
  • 2018: International Macquarie University Research Excellence Scholarship (iMQRES) including tuition fee waiver and providing living stipend for 3 years
  • 2016: International Macquarie University Research Excellence Scholarship (iMQRES) including tuition fee waiver and providing living stipend for 1 year
  • 2014: Received Teaching Excellence Award in the School of Electronics and Communication Engineering at Lovely Professional University, India
  • 2011: Academic Roll of Honour - Vice-Chancellor's roll of honour for academic merit at undergraduate level



Sonit Singh is currently working towards the development of novel methods for analysing medical imaging data. Specifically, he is working on the following two projects:

  1. Biomedical engineering project on the development of camera tracking based system for the registration of multiple 3D Ultrasound volumes of human placenta to form an extended ultrasound volume for having 3D view and analysis of the entire human placenta. The project is in collaboration with UNSW's Perinatal Imaging Research Group (Royal Hospital for Women / UNSW's School for Women's and Children's Health).
  2. Applying artificial intelligence technologies for the diagnosis and staging of liver diseases using ultrasound imaging. Specifically, project aims at discovering relevant imaging biomarkers in sequential ultrasound images/volumes that are predictive of Hepatocellular Carcinoma (HCC). This discovery will lead to early detection and staging of liver diseases, in turn saving human lives. The project is in collaboration with multiple hospitals across New South Wales, including St George, Liverpool, and Royal Prince Alfred.

Term 3, 2021 - COMP9517: Computer Vision