Researcher

Dr Sonit Singh

Fields of Research (FoR)

Artificial intelligence, Computer vision, Natural language processing, Machine learning, Deep learning, Image processing, Pattern recognition, Biomedical imaging, Intelligent robotics, Medical robotics, Computing education, Engineering education

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Biography

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...view more

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.


My Grants

  1. Sonit Singh and Arcot Sowmya, "Wireless Capsule Endoscopy Image Analytics and Predictive Diagnostics", 2022-2023 ($80,000)

My Qualifications

  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

My Awards

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

 

 


My Research Activities

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)

My Research Supervision


Supervision keywords


Areas of supervision

Computer Vision, Natural Language Processing, Machine Learning, Deep Learning, Medical Imaging, Data Science, Robotics, Multimodal Machine Learning, AI in Education


Currently supervising

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 Engagement

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)

 

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. Attended Hybrid Workshop for Machine Learning Advances  in Cardiovascular Health
  2. Attended Big Data Stream planning day at Ingham Institute for Applied Medical Research
  3. Attended UNSW Computing Research Expo 2022
  4. Attended Image Analytics Pillar launch at Tyree IHealthE
  5. 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 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 COMP9444 course. I am mainly responsible for delivering lectures from Week 4 to Week 7, Week 9 and Week 10, covering topics on Computer Vision and Natural Language Processing. For COMP9511, I am mainly delivering tutorials and marking assessments.

  • Hexamester 1, 2024 - ZZEN9444: Neural Networks and Deep Learning

In Hexamester 1, 2024, 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. 

  • Hexamester 2, 2024 - ZZSC9020: Data Science Project

I am teaching and mentoring "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. 

 

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Location

Engineering
405, K17 Building
School of Computer Science and Engineering

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ORCID as entered in ROS

orcid_icon https://orcid.org/0000-0002-6485-131X

UNSW Sydney NSW 2052 Australia Telephone +61 2 93851000
Authorised by Deputy Vice-Chancellor (Research)
UNSW CRICOS Provider Code: 00098G ABN: 57 195 873 179

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