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Dr Ashim Chakraborty

Ashim Chakraborty For media enquiries please contact the Press Team

Lecturer

Faculty:
Faculty of Science and Engineering
School:
Computing and Information Science
Location:
Cambridge
Areas of Expertise:
Computer Science
Research Supervision:
Yes

Ashim is a senior lecturer and researcher primarily working in the areas of computer vision, medical image processing, machine learning, and intelligent systems.

His broader research interests focus on applied artificial intelligence and machine learning, image processing, robotics, and the implementation of AI in immersive technology.

[email protected]

Connect with Ashim on LinkedIn

Visit Ashim's ResearchGate profile

Background

Ashim possesses a multidisciplinary expertise spanning medical image processing, pattern and shape recognition, classification, artificial intelligence (AI), applied mathematics, and business management. His doctoral research focused on devising a lightweight system for the early detection of diabetic retinopathy, leveraging techniques in retinal image processing, decision-based classification, and AI methodologies.

Being a Fellow of the Higher Education Authority, UK (FHEA), Ashim's scholarly pursuits center on medical informatics and imaging for addressing challenges in healthcare domains, applied AI, data transformation strategies, algorithmic developments, deep reinforcement learning, and the utilisation of AI in immersive technologies. Additionally, Ashim contributes as a reviewer for the UK Research and Innovation (UKRI) funding service and the Elsevier Journal Hub.

Spoken Languages

  • English
  • Bangla

Research interests

  • Medical informatics
  • Applied artificial intelligence
  • Computer vision and pattern recognition
  • Smart data transformation
  • Deep reinforcement learning
  • Eye tracking technology
  • Immersive technology
PhD supervision

Razieh Ehsaniamrei: Modelling and optimizing carbon emission factors in the food supply chain using artificial intelligence (2021-Ongoing).

Areas of research supervision

M.Z. Hossain (2016) 'Real-time mobile enabled scheme for virtual spectacle frame selection'.

Teaching

Course Leader

BSc Data Science Degree Apprenticeship

Modules taught
  • System Architecture and Automation
  • Computer Graphics Programming
  • Database Application Programming
  • Software Implementation (C# Programming)

Qualifications

  • PhD in Machine Learning and Medical Image Processing
  • BSc and MSc in Pure and Applied Mathematics
  • MSc in Business Management
  • PGCert Learning & Teaching in Higher Education

Memberships, editorial boards

  • Fellow of Higher Education Academy, UK (FHEA)

Research grants, consultancy, knowledge exchange

  • van der Linde, I., Chakraborty, A., Sapkota, R. (2022) 'How People Look at Pictures: A Health and Wellbeing Perspective using Machine Learning'. £10k
  • Chakraborty, A., Cristina, L., Ball, G. (2023) ‘Advanced Cloud-Based Neonatal Risk Assessment: Automated Classification via Data Fusion of Skin Colour and Ventilation Data’ £30k
  • Hasan, Md., Chakraborty, A., Cirstea, S., Islam, S. (2023) ‘: QuantoSniff: A Next Generation Cyber Defence using Quantum-Safe Cryptography’ KTN, Innovate UK 12k

Selected recent publications

Chakraborty, A., Hubbard, T., Cirstea, S., (2024) ‘A Deep Transfer Learning Approach for Lung Tumor Detection with Resilience Testing Under Suboptimal Conditions.’ 25th IEEE International Conference on Industrial Technology, Bristol, UK

Hasan, M. M.,. Bitto, A. K., Chakraborty, A.,  Nanwani, R.,  Rahman, M. M., and Hameed, N.(2023)  ‘Net0Chain: An AI-Enabled Climate and Environmental Risks (CER) Framework for Achieving Net-Zero’  15th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), Kuala Lumpur, Malaysia, 2023, pp. 163-168, doi: 10.1109/SKIMA59232.2023.10387335.

Chakraborty, A., Wilson, G., Cristina, L., Biba., M. (2022) 'An Optimised Morphological Image Processing Method suitable for the Early Detection of Diabetic Retinopathy'. In: IEEE 18th International Conference on Intelligent Computer Communication and Processing, Cluj-Napoca, Romania.

Chakraborty, A., Chik, D., Biba, M. and Hossain, M. (2017) 'A decision scheme based on adaptive morphological image processing for mobile detection of early-stage diabetic retinopathy'. In: 11th International Conference (IEEE) on Software, Knowledge, Information Management and Applications (SKIMA).

Hossen, M., Chik, D., Chakraborty, A. and Hossain, M. (2016) 'Real-time mobile enabled scheme for virtual spectacle frame selection'. In: 9th International Conference (IEEE) on Software, Knowledge, Information Management and Applications.

Recent presentations and conferences

Chakraborty, A., Hubbard, T., Cristea, S. (2023) ‘A deep transfer learning approach for lung tumour detection with resilience testing under suboptimal conditions’. 2nd MTRC annual research conference, Anglia Ruskin University, Cambridge, UK

Hasan, M. M., Chakraborty, A., and Cirstea, S. (2022). 'A next-generation explainable AI-enabled (XAI) expert system for eye disease detection and risks stratification', 1st MTRC annual research conference, Anglia Ruskin University, Chelmsford, UK (poster presentation).

Chakraborty, A. (2018) 'Mobile enabled intelligent retinal image-based diagnosis', AI for Medical Informatics, Engineering and Devices, 28 June 2018, Chelmsford, UK (presentation).

Chakraborty, A., Chik, D., Biba, M. and Hossain, M.A. (2017) 'A decision scheme based on adaptive morphological image processing for mobile detection of early-stage diabetic retinopathy' (presentation).

Chakraborty, A., Chik, D. and Hossain, M. (2016) 'Mobile based decision support system for early stage of diabetic retinopathy'. 6th Annual FsT Research Conference, New and Emerging Research, Anglia Ruskin University, Chelmsford, UK (poster presentation).