University of Nottingham Malaysia
School of Computer Science
     
  
 

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Tissa Chandesa

Assistant Professor,

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Biography

Dr Tissa Chandesa holds a BSc (Hons) and Ph.D. in Computer Science from the University of Nottingham. He is a Senior Fellow of the Higher Education Academy, UK, the first at University of Nottingham Malaysia to be bestowed such recognition, a Malaysian Human Resources Development Fund (HRDF) Certified Trainer, a Lord Dearing Award recipient, and a Reviewer for the IEEE Transactions on Image Processing.

Upon completing his doctorate, Dr Chandesa spent 9 plus years (2012-2021) with the Graduate School, University of Nottingham Malaysia where he held the roles of Research Training Convenor, Research Training Development Manager, and Interim Dean of the Graduate School. During his time with the Graduate School, Dr Chandesa was responsible to provide co-ordination, support, supervision, management and/or mentoring to professional service members of staff, junior as well as senior academics and postgraduates in relation to research and teaching development.

Dr Chandesa's true passion is in the field of Computer Science. This was the motivation behind his decision to pursue an academic career with the School of Computer Science at the University of Nottingham Malaysia, where he currently is Professor (Assistant), Director of Marketing as well as Director of Student Experience.

Expertise Summary

Dr Chandesa research aims toward Computer Vision, Image Processing, Deep & Machine Learning, Natural Language Processing and the use of Educational Technologies to augment the teaching and learning experience in Higher Education.

Teaching Summary

Module convenor for the following modules:

  1. Computer Fundamentals
  2. Introduction to Image Processing
  3. Artificial Intelligence Methods

Supervise Final Year (FYP), MSc as well as MPhil and PhD Projects.

Research Summary

  1. Incorporate Intelligent Scissors and/or Saliency Maps into Convolutional Neural Network(s) to create tools that can improve the classification process for biodiversity image analysis.

  2. Improve the architecture of Convolutional Neural Network (CNN) to accommodate a limited sample size of a dataset.

  3. Create educational focused AI tools to augment the teaching and learning experience in Higher Education, subsequently contributing to the emerging field of Educational Technologies.

School of Computer Science

University of Nottingham Malaysia
Jalan Broga, 43500 Semenyih
Selangor Darul Ehsan
Malaysia

telephone: +6 (03) 8924 8000
fax: +6 (03) 8924 8018

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