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Abira Sengupta

PhD
School of Computing
Multi-Agent System
University of Otago, NZ

Email: abira[dot]sengupta[at]postgrad[dot]otago[dot]ac[dot]nz

ORCID:0000-0002-6867-3362

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About | Research areas | Research projects | Publications | Teaching | CV |


About Me

Hi, I am Abira. Welcome to my academic webpage. I finished my PhD in Multi-Agent System under the supervision of Prof. Stephen Cranefield, University of Otago, NZ. Explainable AI for Climate, particularly Wildfire, is my current area of focus. I am a Visiting Scientist and Affiliated Researcher at the Indian Statistical Institute (ISI). I am a passionate tutor in the School of Computing at the University of Otago. I am also a member of IEEE, CAIPP, SINZ, and AIRA.

Earlier in my pre-Doctoral work I focused on Computer Vision and Machine Learning and deep learning to face recognition for biometrics. I was a guest lecturer at various Indian universities.

My birthplace is Kolkata, India. In 2019, I moved to Dunedin, New Zealand, to complete my doctorate. In my spare time, I enjoy gardening and listening to music. I also enjoy riding my bicycle and learning new skills.

Research Areas

Research projects

L2S

Post-PhD projects:

[1] 2023-2024 University of Otago | Collaboration Study

- Recent Advances in Explainable Machine Learning to identify the most important features that influence the performance of wildfire prediction models. Link

[2] 2024 Indian Statistical Institute | Collaboration Study

- Exploring the impact of precipitation, cloudbursts, and wildfire detection, as well as predicting fire spread using Explainable Machine Learning techniques.

[3] 2023: University of Otago | Postdoctoral research assistant

- Making decisions about healthcare services in various parts of New Zealand by utilising machine learning to find significant information.

L2S

PhD project:

My work focuses on the use of logical reasoning regarding expectations and generalised representation to help computational agents to solve a range of collective action problems. The different applications of expectation-related reasoning, such as expectation, team reasoning norms, norm, and norm emergence from emotion, were explained in this work. The central claim of my research is to build a generalised computational model in which symbolic representations of norms are used as an input and an Expectation Event Calculus (Prolog-based) is used to represent how explicit reasoning of expectation is generated and how it is fulfilled or violated.

L2S

Other Research work

[1] 2021 Univ. of Otago, NZ | Research Assistant

- A computational analysis of text data for emotion recognition.

[2] April 2017-December 2018: Indian Statistical Institute | Pre-Doctoral Research

- ConvNet-based Face Recognition for Biometric Authentication and Pincode detection of multilingual behaviour.

[3] July 2011-June 2013: West Bengal University of Technology | Masters Research

- Localized Algorithm for Coverage in Wireless Sensor Networks.

[4] July 2009-June 2010: West Bengal University of Technology | Bechelors Research

- Developing an Academics Management System.


Publications

Papers

  1. Fathima Nuzla Ismail, Abirs Sengupta, "Teaching and Learning Experience with the Kahoot feedback system”, Asia-Pacific Journal of Teacher Education, 2024 (submitted)
  2. Abirs Sengupta, Fathima Nuzla Ismail, "Software as a Medical Device: Design and Compliance”, ICCAE, 2025 (Accepted)
  3. Abirs Sengupta, Fathima Nuzla Ismail, "Modelling methane emissions from rice paddies using machine learning", IVCNZ, 2024 (Accepted)
  4. Abirs Sengupta, Brendon J. Woodford, "Recent Advances in Explainable Machine Learning Models for Wildfire Prediction", Applied Computing and Geosciences 2024 (submitted)
  5. Abira Sengupta, Stephen Cranefield, Jeremy Pitt, "Generalising Axelrod's Metanorms Game through the use of explicit domain-specific norms", COINE 2023. [paper]
  6. Fathima Nuzla Ismail, Abira Sengupta,, Brendon Woodford, Sherlock Licorish, "A Comparison of One-class versus Two-class Machine Learning Models for Wildfire Prediction in California", AusDM 2023. [paper]
  7. Abira Sengupta, Stephen Cranefield, Jeremy Pitt, "Solving social dilemmas by reasoning about expectations", COINE 2021: 1-18. [paper]
  8. Abira Sengupta, Saurabh Malgaonkar, Nikita Mehrotra, Tejas Hirave, " A Preliminary Investigation of LEACH, TEEN and DEEC Towards Wireless Sensing Application", ICCICT 2021. [paper]
  9. Abhijit Das, Abira Sengupta, Muhammad Saqib, Umapada Pal, and Michael Blumenstein, "More Realistic and Efficient Face-Based Mobile Authentication using CNN", IJCNN, 2018. [paper]
  10. Nabin Sharma, Abira Sengupta, Rabi Sharma, Umapada Pal, and Michael Blumenstein, "Pincode detection using Deep CNN for postal Automation", IVCNZ, 2017. [paper]
  11. Abhijit Das, Abira Sengupta, Umapada Pal, and Michael Blumenstein, "Linking Challenging Face Images Captured from the Optical Phenomenon in the Wild for Forensic Science", IJCB, 2017. [paper]

Posters

  1. Abira Sengupta, Stephen Cranefield, Jeremy Pitt, "Generic representation of expectations can help computational agents to solve social dilemmas", AIRA, NZ, https://www.ainz.ai/2022-posters

Awards and Funding

    • [1] Commerce Research Grant (2023).
    • [2] Marsden scholarship for 3 years PhD studies in NZ (2019 - 2022).
    • [3] Technical Education Quality Improvement Programme for MTech scholarship in India (2012 - 2013).

Teaching

L2S

[1] Tutor/Demonstrator at the University of Otago, NZ (2019 to 2023) |

- 2024, 2019: COMP 101, R and SQL coding.
- 2023: DIGH 708 & 709, Digital Health Technologies.
- 2024, 2022, 2021, 2020: INFO 204, Machine learning using Python coding.
- 2024, 2023, 2022, 2021: COMP 120, Data Science using R.
- 2022: INFO 301, Software development.
- 2021: INFO 310, software and system development using JAVA.


[2] Guest Lecturer in Kolkata, India (2015-2018) | Part-time Faculty

- Jadavpur University - Taught multimedia systems.
- Kalyani Govt Engg College - Taught Algorithms, Automata, Graphics, Multimedia.
- Aliah University - Taught Sensor Networking theory.
- Narula Institute of Technology - Taught C coding, Multimedia, Networking theory.