Dr Sonit Singh
Lecturer

Dr Sonit Singh

Engineering
Computer Science and Engineering

Sonit Singh is a Lecturer in the School of Computer Science and Engineering at the University of New South Wales (UNSW), Sydney, Australia. Before being promoted to the Lecturer position, he was 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. Since August 2021, he joined UNSW and has been involved in teaching COMP9517: Computer Vision and COMP9444: Neural Networks and Deep Learning.

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.

Location
405, K17 Building School of Computer Science and Engineering
  • Journal articles | 2023
    Singh S; Hoque S; Zekry A; Sowmya A, 2023, 'Radiological Diagnosis of Chronic Liver Disease and Hepatocellular Carcinoma: A Review', Journal of Medical Systems, 47, http://dx.doi.org/10.1007/s10916-023-01968-7
    Journal articles | 2021
    Rybinski M; Dai X; Singh S; Karimi S; Nguyen A, 2021, 'Erratum: Extracting family history information from electronic health records: natural language processing analysis (JMIR Medical Informatics (2021) 9:4 (e24020) DOI: 10.2196/24020)', JMIR Medical Informatics, 9, http://dx.doi.org/10.2196/30153
    Journal articles | 2021
    Rybinski M; Dai X; Singh S; Karimi S; Nguyen A, 2021, 'Extracting family history information from electronic health records: Natural language processing analysis', JMIR Medical Informatics, 9, http://dx.doi.org/10.2196/24020
    Journal articles | 2021
    Singh S; Karimi S; Ho-Shon K; Hamey L, 2021, 'Show, tell and summarise: learning to generate and summarise radiology findings from medical images', Neural Computing and Applications, 33, pp. 7441 - 7465, http://dx.doi.org/10.1007/s00521-021-05943-6
  • Preprints | 2024
    Singh S; Stevenson G; Mein B; Welsh A; Sowmya A, 2024, Automatic 3D Multi-modal Ultrasound Segmentation of Human Placenta using Fusion Strategies and Deep Learning, , http://arxiv.org/abs/2401.09638v1
    Conference Papers | 2023
    Canepa L; Singh S; Sowmya A, 2023, 'Visual Question Answering in the Medical Domain', in 2023 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2023, pp. 379 - 386, http://dx.doi.org/10.1109/DICTA60407.2023.00059
    Preprints | 2023
    Canepa L; Singh S; Sowmya A, 2023, Visual Question Answering in the Medical Domain, , http://arxiv.org/abs/2309.11080v1
    Conference Papers | 2023
    Chu Z; Singh S; Sowmya A, 2023, 'TSDNET: A Tumour Segmentation Network with 3D Direction-Wise Convolution', in Proceedings - International Symposium on Biomedical Imaging, http://dx.doi.org/10.1109/ISBI53787.2023.10230462
    Conference Papers | 2023
    Rahman MA; Singh S; Shanmugalingam K; Iyer S; Blair A; Ravindran P; Sowmya A, 2023, 'Attention and Pooling based Sigmoid Colon Segmentation in 3D CT images', in 2023 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2023, pp. 312 - 319, http://dx.doi.org/10.1109/DICTA60407.2023.00050
    Preprints | 2023
    Rahman MA; Singh S; Shanmugalingam K; Iyer S; Blair A; Ravindran P; Sowmya A, 2023, Attention and Pooling based Sigmoid Colon Segmentation in 3D CT images, , http://arxiv.org/abs/2309.13872v1
    Conference Papers | 2023
    Zhang S; Gharleghi R; Singh S; Sowmya A; Beier S, 2023, 'Assessing Encoder-Decoder Architectures for Robust Coronary Artery Segmentation', in Bailey D; Punchihewa A; Paturkar A (eds.), Proceedings of the 2023 38th International Conference Image and Vision Computing New Zealand (IVCNZ), IEEE, Palmerston North, New Zealand, presented at IVCNZ 2023 Image and Vision Computing, Palmerston North, New Zealand, 29 November 2023 - 30 November 2023, http://dx.doi.org/10.1109/IVCNZ61134.2023.10343804
    Preprints | 2023
    Zhang S; Gharleghi R; Singh S; Sowmya A; Beier S, 2023, Assessing Encoder-Decoder Architectures for Robust Coronary Artery Segmentation, , http://arxiv.org/abs/2310.10002v1
    Preprints | 2021
    Rybinski M; Dai X; Singh S; Karimi S; Nguyen A, 2021, Correction: Extracting Family History Information From Electronic Health Records: Natural Language Processing Analysis (Preprint), , http://dx.doi.org/10.2196/preprints.30153
    Preprints | 2020
    Rybinski M; Dai X; Singh S; Karimi S; Nguyen A, 2020, Extracting Family History Information From Electronic Health Records: Natural Language Processing Analysis (Preprint), , http://dx.doi.org/10.2196/preprints.24020
    Conference Papers | 2019
    Singh S; Karimi S; Ho-Shon K; Hamey L, 2019, 'Biomedical concept detection in medical images: MQ-CSIRO at 2019 Imageclefmed caption task', in CEUR Workshop Proceedings
    Conference Papers | 2019
    Singh S; Karimi S; Ho-Shon K; Hamey L, 2019, 'From Chest X-Rays to Radiology Reports: A Multimodal Machine Learning Approach', in 2019 Digital Image Computing: Techniques and Applications, DICTA 2019, http://dx.doi.org/10.1109/DICTA47822.2019.8945819
    Conference Papers | 2018
    Singh S; Ho-Shon K; Karimi S; Hamey L, 2018, 'Modality Classification and Concept Detection in Medical Images Using Deep Transfer Learning', in International Conference Image and Vision Computing New Zealand, http://dx.doi.org/10.1109/IVCNZ.2018.8634803
    Conference Papers | 2018
    Singh S, 2018, 'Pushing the limits of radiology with joint modeling of visual and textual information', in ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Student Research Workshop, pp. 28 - 36, http://dx.doi.org/10.18653/v1/p18-3005
    Preprints | 2018
    Singh S, 2018, Natural Language Processing for Information Extraction, , http://arxiv.org/abs/1807.02383v1
    Conference Papers | 2014
    Kamya S; Sachdeva M; Dhaliwal N; Singh S, 2014, 'Fuzzy logic based Intelligent Question Paper Generator', in 2014 IEEE International Advance Computing Conference (IACC), IEEE, presented at 2014 IEEE International Advance Computing Conference (IACC), 21 February 2014 - 22 February 2014, http://dx.doi.org/10.1109/iadcc.2014.6779494
    Conference Papers | 2014
    Kaur R; Singh S, 2014, 'Background modelling, detection and tracking of human in video surveillance system', in 2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH), IEEE, presented at 2014 Innovative Applications of Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH), 28 November 2014 - 29 November 2014, http://dx.doi.org/10.1109/cipech.2014.7019097
    Conference Papers | 2012
    Chaudhary A; Singh SS, 2012, 'Lung Cancer Detection on CT Images by Using Image Processing', in 2012 International Conference on Computing Sciences, IEEE, presented at 2012 International Conference on Computing Sciences (ICCS), 14 September 2012 - 15 September 2012, http://dx.doi.org/10.1109/iccs.2012.43

I feel honored to receive the following awards:

  • 2023: UNSW Engineering Deans Early Career Academic Fellowship
  • 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.

Professional societies:

  • Member, Association for Computing Machinery (ACM)
  • Member, Institute of Electrical and Electronics Engineers (IEEE)
  • Member, Association for Computational Linguistics (ACL)
  • Associate Fellow of Higher Education Academy, UK (AFHEA)

 

Reviewing service:

  • Computer Methods and Programs in Biomedicine
  • Health Information Science and Systems
  • IEEE International Symposium on Biomedical Imaging (ISBI)
  • Artificial Intelligence in Medicine
  • Association for Computational Linguistics (ACL)
  • Artificial Intelligence in Medicine (AIIM)
  • Conference on Computer Vision and Pattern Recognition (CVPR)
  • IEEE Journal of Biomedical and Health Informatics (JBHI)
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
  • Radiotherapy and Oncology
  • European Conference on Machine Learning (ECML)

 

Engineering Education:

  • Attended Essentials of Supervision Workshop (Supervising Doctoral Studies)
  • Attending Scientia Education Academy Lecture Series
  • Computers and Education
  • Computers and Education: Artificial Intelligence

 

Seminars, Workshops, Conferences

  • Attended Hybrid Workshop for Machine Learning Advances  in Cardiovascular Health
  • Attended Big Data Stream planning day at Ingham Institute for Applied Medical Research
  • Attended UNSW Computing Research Expo 2022
  • Attending Image Analytics Pillar launch at Tyree IHealthE

 

My Research Supervision

  • Louisa Canepa (Honors thesis candidate)

         Topic: Medical Visual Question Answering (Med-VQA)

         Joint supervision with Prof. Arcot Sowmya

  • Md Akizur Rahman (PhD candidate

          Topic: AI Driven Automated Diverticulitis Prognosis and Treatment Planning

          Joint supervision with Prof. Arcot Sowmya

  • Ziping Chu (MPhil candidate)

          Topic: A self-adapting framework for medical image segmentation

           Joint supervision with Prof. Arcot Sowmya

  • Matthew Gibson (PhD candidate)

          Topic: Machine Learning for Change Detection in Remote Sensing

          Joint supervision with Prof. Arcot Sowmya

  • Shisheng Zhang (PhD candidate)

          Topic: Learning to predict risk of Coronary Artery Disease from CTCA Images

          Joint supervision with Ramtin Gharleghi, Arcot Sowmya, and Susann Beier

 

 

My Teaching

  • Term 3, 2021 - COMP9517: Computer Vision

In Term 3 2021 I did Lecturing and Tutoring for COMP9517: Computer Vision course. I was mainly responsible for delivering lectures in Week 8 "Convolutional Neural Networks and their applications" and Week 9 "Applications of Deep Learning" where I covered various applications at the intersection of computer vision and natural language processing. As it was for the first time I was teaching a course at UNSW, I also get involved in tutoring COMP9517 to have better understanding of the course and its assessments. I revised tutorial/lab specifications and did marking of labs, assignment, project, and the final exam. Overall, it was a great teaching and learning experience.

 

  • Term 2, 2022 - COMP9444: Neural Networks and Deep Learning

In Term 2, 2022, I did Lecturing and Tutoring for COMP9444 course. I was mainly responsible for delivering lectures from Week 4 to Week 7, covering topics on Computer Vision and Natural Language Processing.

 

  • Term 3, 2022 - COMP9444: Neural Networks and Deep Learning

In Term 3, 2022, I did Lecturing and Tutoring for COMP9444 course. I was mainly responsible for delivering lectures from Week 4 to Week 7, covering topics on Computer Vision and Natural Language Processing.

 

  • Term 2, 2023 - COMP9444: Neural Networks and Deep Learning/ COMP9511: Human Computer Interaction

In Term 3, 2022, I am Lecturing and Tutoring for COMP9444 course. I am mainly responsible for delivering lectures from Week 4 to Week 7, covering topics on Computer Vision and Natural Language Processing. For COMP9511, I am mainly delivering tutorials and marking assessments.