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Dr Sonit Singh

Dr Sonit Singh

Lecturer
  1. Doctorate of Philosophy (PhD) in Multimodal Machine Learning, Macquarie University, Sydney, Australia 2021
  2. Master of Research (M.Res.) in Natural Language Processing and Machine Learning, Macquarie University, Sydney, Australia, 2017
  3. Bachelor of Technology (B.Tech.) in Electronics and Communication Engineering,  Lovely Professional University, India, 2011
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.
E-mail
sonit.singh@unsw.edu.au
Location
205, K17 Building School of Computer Science and Engineering
  • Journal articles | 2024
    Chu Z; Singh S; Sowmya A, 2024, 'Robust Automated Tumour Segmentation Network Using 3D Direction-Wise Convolution and Transformer.', J Imaging Inform Med, 37, pp. 2444 - 2453, http://dx.doi.org/10.1007/s10278-024-01131-9
    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
    Preprints | 2024
    Singh S, 2024, Clinical Context-aware Radiology Report Generation from Medical Images using Transformers, http://arxiv.org/abs/2408.11344v1
    Preprints | 2024
    Singh S, 2024, CoVScreen: Pitfalls and recommendations for screening COVID-19 using Chest X-rays, http://arxiv.org/abs/2405.07674v1
    Preprints | 2024
    Singh S, 2024, Computer-Aided Diagnosis of Thoracic Diseases in Chest X-rays using hybrid CNN-Transformer Architecture, http://arxiv.org/abs/2404.11843v2
    Preprints | 2024
    Singh S, 2024, Designing a Robust Radiology Report Generation System, http://arxiv.org/abs/2411.01153v1
    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, pp. 1179 - 1183, 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, pp. 54 - 58, 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, pp. 142 - 146, presented at 2012 International Conference on Computing Sciences (ICCS), 14 September 2012 - 15 September 2012, http://dx.doi.org/10.1109/iccs.2012.43

  1. Sonit Singh and Arcot Sowmya, "Wireless Capsule Endoscopy Image Analytics and Predictive Diagnostics", 2022-2023 ($80,000)
  2. Sonit Singh, "Improving Engineering Education using Project-based Learning", Course Design Institute Grant, 2024 ($2,500)
  3. Sonit Singh, "The Engineer and the World - 35th Australasian Association for Engineering Education Annual Conference", EF Grant, 2024 ($3467)

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 has been involved in the following 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.
  3. Omics Imagification: Converting Omics data into Images for the application of Convolutional Neural Networks. The project aims to develop methods to transform non-image omics data into images for the application of convolutional neural networks. This project is in collaboration with Dr. Miad Zandavi (Harvard Medical School), Prof. Arcot Sowmya (School of CSE, UNSW Sydney), and A/Prof. Fatemeh Vafaee (School of BABS, UNSW Sydney).

 

Seminar/Presentations

  1. Sonit Singh, "Bridging the gap between Images and Text with Deep Learning", Guest lecture in COMP3420: Artificial Intelligence for Text and Vision course in School of Computing, Macquarie University (29 August 2023)
  2. Sonit Singh, "Overview of UNSW AI and Analytics", presentation to delegates and Head of the Foreign Policy Strategy Agency of the Ministry of the Foreign Affairs of the Republic of Indonesia (20 March 2024)
  3. Sonit Singh, "Artificial Intelligence in Medicine: Making Impact in Clinical Practice", presentation to delegates from Ministry of Foreign Affairs, Malaysia (May 2023)

Professional societies:

  1. Member, Association for Computing Machinery (ACM)
  2. Member, Institute of Electrical and Electronics Engineers (IEEE)
  3. Member, Association for Computational Linguistics (ACL)
  4. Associate Fellow of Higher Education Academy, UK (AFHEA)
  5. Member, Australasian Association for Engineering Education (AAEE) 

 

UNSW:

  1. Deputy Director, UNSW Online (Data Science and Analytics Program)
  2. Member, UNSW Data Science Hub (uDASH)
  3. Member, UNSW AI Institute (UNSW.AI)

 

Reviewing service:

  1. Computer Methods and Programs in Biomedicine
  2. Health Information Science and Systems
  3. IEEE International Symposium on Biomedical Imaging (ISBI)
  4. Artificial Intelligence in Medicine
  5. Association for Computational Linguistics (ACL)
  6. Artificial Intelligence in Medicine (AIIM)
  7. Conference on Computer Vision and Pattern Recognition (CVPR)
  8. IEEE Journal of Biomedical and Health Informatics (JBHI)
  9. IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
  10. Radiotherapy and Oncology
  11. European Conference on Machine Learning (ECML)
  12. IEEE Access

 

Engineering Education:

  1. Essentials of Supervision Workshop (Supervising Doctoral Studies)
  2. Scientia Education Academy Lecture Series
  3. Computers and Education
  4. Computers and Education: Artificial Intelligence
  5. Foundations of University Learning and Teaching (FULT) Program 2021
  6. UNSW Teaching Accelerator Program 2024
  7. UNSW Course Design Institute (CDI) Course Development Program 2024

 

Seminars, Workshops, Conferences

  1. Sydney Teaching Symposium, University of Sydney, 16 July 2024
  2. Attended Hybrid Workshop for Machine Learning Advances  in Cardiovascular Health
  3. Attended Big Data Stream planning day at Ingham Institute for Applied Medical Research
  4. Attended UNSW Computing Research Expo 2022
  5. Attended Image Analytics Pillar launch at Tyree IHealthE
  6. 2023 Indo-Pacific International Maritime Exposition, International Convention Centre, Sydney (7-9 November 2023)

 

Representing CSE to delegates of international universities, research organisations, and government and industry bodies

  1. Thapar Institute of Engineering and Technology, India (18 August 2023)
  2. Mahidol  University, Thailand (13 June 2023)

 

Posters

  1. Sonit Singh, "Advanced Computational Methods for Automated Image Analysis", CSE Research Expo, UNSW Sydney (24 October 2022)

Presentation/Seminars

  1. Sonit Singh, "Multimodal Machine Learning for Medical Imaging", MLCV Group, School of Computer Science and Engineering, UNSW Sydney (24 September 2021)
  2. Sonit Singh, "The Rise of Language Model", MLCV Group, School of Computer Science and Engineering, UNSW Sydney (17 December 2021)
  3. Sonit Singh, "Attention Augmented Convolutional Neural Networks", Computer Vision Group, School of Computer Science and Engineering, UNSW Sydney (08 July 2022)
  4. Sonit Singh, "Data Augmentation Techniques in Natural Language Processing", NLP Reading Group, School of Computer Science and Engineering, UNSW Sydney (12 September 2023)
  5. Sonit Singh, "Segment Anything Model", Biomedical Image Computing Group, School of Computer Science and Engineering, UNSW Sydney (28 March 2024)
  6. Sonit Singh, "Self-supervised Representation Learning for Images, Videos, Text, and Audio", MLCV Group,  School of Computer Science and Engineering, UNSW Sydney 
  7. Sonit Singh, "Retrieval-Augmented Generation for Large Language Models", Human-Centered Computing and Machine Learning Group,  School of Computer Science and Engineering, UNSW Sydney 

My Research Supervision

PhD Research Students

  1. Matt Gibson, "Machine Learning for Change Detection in Remote Sensing", School of Computer Science and Engineering, UNSW Sydney (Joint supervision with Prof. Arcot Sowmya)
  2. Md Akizur Rahman, "AI-Driven Automated Acute Diverticulitis Prognosis and Treatment Planning", School of Computer Science and Engineering, UNSW Sydney (Joint supervision with Prof. Arcot Sowmya, Dr. Alan Blair, and Dr. Praveen Ravindran (Colorectal Surgeon, Sydney Adventist Hospital))
  3. Shisheng Zhang, "Learning to Predict risk of Coronary Artery Disease from CTCA Images", School of Mechanical and Manufacturing Engineering, UNSW Sydney (Joint supervision with Prof. Arcot Sowmya and Dr. Susann Beier)
  4. Hao Wu, "Cardiovascular Risk Prediction based on CTCA images and clinical data using Machine Learning", School of Mechanical and Manufacturing Engineering, UNSW Sydney (Joint supervision with Prof. Arcot Sowmya and Dr. Susann Beier)
  5. Manna Elizabeth Philip, "Automated Fetal Cardiac Functional Assessment using 4D Ultrasound", School of Computer Science and Engineering, UNSW Sydney (Joint supervision with Prof. Arcot Sowmya, Prof. Alec Welsh (School of Medicine), and Dr. Gordon Stevenson (ML Engineer at Vexev Pty Ltd))
  6. Irfan Dwiki Bhaswara, "Surgical Instrument Detection and Tracking in robot-assisted surgery", School of Computer Science and Engineering, UNSW Sydney (Joint supervision with Prof. Erik Meijering and Prof. Arcot Sowmya)

MPhil Research Students

  1. Ziping Chu, "A self-adapting framework for medical image segmentation", School of Computer Science and Engineering, UNSW Sydney (Joint supervision with Prof. Arcot Sowmya)

Masters and Honours Research Students

  1. Darren Chong, "Omics Imagification: Representation Learning of Omics in the form of Images for the applications of CNN", September 2023 - Ongoing.
  2. Lachie Nguyen, "Diagnosing Coronary Stenosis in CTCA images using Artificial Intelligence", February 2024 - Ongoing
  3. Zhongsui Guo, "Smart Food Monitoring System", September 2023 - Ongoing 
  4. Runyu Wang, "Automated Music Generation using Neural Networks", May 2023 - Ongoing
  5. Rahul Soni, "Course Recommendation System based on Career Interests", February 2024 - Ongoing
  6. Rohan Patel, "Course Recommendation System based on Career Interests", February 2024 - Ongoing
  7. Vincent Pham, "Improving Student Engagement in Online Learning",  February 2024 - Ongoing
  8. Quoc Minh Quan Nguyễn, "Student Emotion Detection for Engagement in Online Learning,  February 2024 - Ongoing
  9. Jonathan Chen, "Symbolic Music Generation using Deep Learning",  February 2024 - Ongoing

Completions (Masters and Honours Thesis)

  1. Louisa Canepa, "Medical Visual Question Answering (Med-VQA), Honours in AI, May 2022 - April 2023.
  2. Michael Chen, "AI for the Diagnosis and Staging of Liver Diseases using Ultrasound Imaging", February 2023 - December 2023

Research Interns

  1. Shreyas Raturi, "Pan-cancer Classification using Omics Imagification techniques", SRM Institute of Science and Technology, India (May - November 2022)
  2. Vishnucharan S, "Adaptive Multiple Choice Question Generation using Knowledge Tracing Model", National Institute of Technology - Tiruchirappalli, India (April 2024 - Ongoing) 

 

My Teaching

  • 2024 Term 3

    COMP9444: Neural Networks and Deep Learning
    COMP9517: Computer Vision
     
  • 2024 Term 2

    COMP9444: Neural Networks and Deep Learning
     
  • 2024 Hexamester 2

    ZZSC9020: Data Science Project

    I taught and mentored "Data Science Project" course, a 6-Week data science capstone project where students need to apply knowledge learnt in "Data Science and Analytics" program to solve some real-world problem. Students are provided with real-world data and they need to do formulate the research question, conduct literature review, exploratory data analysis, model implementation, results analysis, error analysis, limitations and future work. 
     
  • 2024 Hexamester 1

    ZZEN9444: Neural Networks and Deep Learning (Online)

    I did lecturing for ZZEN9444 course, an accelerated 6-Weeks course delivered to UNSW Online (Data Science and Analytics) program cohort. I really enjoyed teaching this cohort as most of them are already working in the IT industry as senior data scientists, business analysts, machine learning engineers, etc. 
     
  • 2023 Term 3

    COMP9444: Neural Networks and Deep Learning 
    COMP9517: Computer Vision
     
  • 2023 Term 2

    COMP9444: Neural Networks and Deep Learning
    COMP9511: Human Computer Interaction
     
  • 2022 Term 3

    COMP9444: Neural Networks and Deep Learning 
     
  • 2022 Term 2

    COMP9444: Neural Networks and Deep Learning