Ashim Chakraborty

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 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, image processing, network, cyber security, and the semantic web.

Email: ashim.chakraborty@aru.ac.uk

View Ashim's profiles on LinkedIn and Research Gate.

Background

Ashim has a multidisciplinary background in Medical Image processing, Pattern and Shape recognition, Classification, Artificial Intelligence, Applied Mathematics, and Business Management. His doctoral research explored a lightweight system for early detection of Diabetic Retinopathy using retinal image processing, decision-based classification, and Artificial intelligence (AI). As an associate fellow of the Higher Education Authority, UK (HEA), Ashim's research interest is Digital image processing, Applied AI, Smart Data Transformation, Algorithms, Cloud-AI, Deep Reinforcement Learning, Brain-computer Interface, Semantic Web, Networks and Cyber Security.

Spoken Languages

English and Bangla.

Research interests

  • Applied Artificial intelligence
  • Medical informatics
  • Networks and Cyber Security
  • Smart Data Transformation
  • Algorithms
  • Deep Reinforcement Learning
  • Brain-computer Interface

Areas of research supervision

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

Teaching

  • System architecture and automation
  • Computer graphics programming
  • Database application programming
  • Database design and implementation
  • Project management and quality assurance

Qualifications

  • BSc in Pure and Applied Mathematics
  • MSc in Applied Mathematics
  • MSc in Business Management

[Ashim’s PhD thesis titled ‘A Lightweight, Novel Feature Extraction and Classification System for the Early Detection of Diabetic Retinopathy’ is submitted to the Anglia Ruskin University Doctoral School and waiting for the final oral examination].

Memberships, editorial boards

  • Associate fellow of Higher Education Academy

Research grants, consultancy, knowledge exchange

  • University of Greenwich consultancy project coordinator for Business solutions

Selected recent publications

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. 2017 11th International Conference 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. 9th International Conference (IEEE) on Software, Knowledge, Information Management & Applications., 62.

Recent presentations and conferences

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).

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).

2018, 2017 and 2016.; Mobile enabled intelligent retinal image-based diagnosis. AI for Medical Informatics, Engineering and Devices. 28 June 2018, Chelmsford, UK. (Presentation).