Computer Vision Laboratory
 

Image of Tissa Chandesa

Tissa Chandesa

Assistant Professor,

Contact

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 as well as a Lord Dearing Award recipient.

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) as well as Director of Marketing and Students Experience.

Expertise Summary

Dr Chandesa research aims toward Computer Vision, Image Processing, Deep & Machine Learning, Generative Artificial Intelligence (GAI) and the use of Educational Technologies as well as GAI 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

Previously, was module convenor for the Artificial Intelligence Methods module.

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

Research Summary

Developing novel and efficient Computer Vision and Image Processing techniques and applications to support/solve interdisciplinary as well as multidisciplinary research problems in active research… read more

Selected Publications

  • YAQUB, I, CHEN, Z-Y, LIAO, I Y, MAUL, T, SEOW, H-S and CHANDESA, T, 2024. A Novel Framework using Large Language Models to Automate Coursework Feedback for Computer Science modules. In: In The 16th International Conference on Education Technology and Computers (ICETC 2024), Porto, Portugal..
  • HANG, R, MAUL, T, CHEN, Y-F, CHANDESA, T, LIAO, I Y and CHEN, Z-Y, 2024. Exploring SSL Enhancement Through Triplet-Based Representation Learning. In: In 2024 IEEE 16th International Conference on Advanced Infocomm Technology (ICAIT 2024), Hubei, China..
  • KHOO, J, BEH, A K J, HERMAWAN, D K, HASLAN, R H, CHANDESA, T, TOO, W K and PRICE, J, 2024. Evaluating the “design-it-in” approach: Interdisciplinary reflections on embedding Generative Artificial Intelligence use in learning and assessments. In: . In Teaching and Learning Conference 2024, Nottingham, United Kingdom.
  • ABDALLA, I, SAKUNDARINI, N, MAY MAY, C C and CHANDESA, T, 2024. In: MOHD. ISA, W H, KHAIRUDDIN, I M, MOHD. RAZMAN, M A, SARUCHI, S 'A, TEH, S-H and LIU, P, eds., Lecture Notes in Networks and Systems: Detection of Fault Features in Remanufacturing of Automotive Components Using Image Processing and Computer Vision Techniques. 850. Springer, Singapore.

Current Research

  1. Developing novel and efficient Computer Vision and Image Processing techniques and applications to support/solve interdisciplinary as well as multidisciplinary research problems in active research fields in Science, Engineering as well as Arts and Social Sciences.

  2. Creating educational focused Artificial Intelligence tools to augment the teaching and learning experience in Higher Education, subsequently contributing to the emerging fields of Artificial Intelligence and Education.

  • ABDALLA, I, SAKUNDARINI, N, MAY MAY, C C and CHANDESA, T, 2024. In: MOHD. ISA, W H, KHAIRUDDIN, I M, MOHD. RAZMAN, M A, SARUCHI, S 'A, TEH, S-H and LIU, P, eds., Lecture Notes in Networks and Systems: Detection of Fault Features in Remanufacturing of Automotive Components Using Image Processing and Computer Vision Techniques. 850. Springer, Singapore.
  • KHOO, J, BEH, A K J, HERMAWAN, D K, HASLAN, R H, CHANDESA, T, TOO, W K and PRICE, J, 2024. Evaluating the “design-it-in” approach: Interdisciplinary reflections on embedding Generative Artificial Intelligence use in learning and assessments. In: . In Teaching and Learning Conference 2024, Nottingham, United Kingdom.
  • HANG, R, MAUL, T, CHEN, Y-F, CHANDESA, T, LIAO, I Y and CHEN, Z-Y, 2024. Exploring SSL Enhancement Through Triplet-Based Representation Learning. In: In 2024 IEEE 16th International Conference on Advanced Infocomm Technology (ICAIT 2024), Hubei, China..
  • YAQUB, I, CHEN, Z-Y, LIAO, I Y, MAUL, T, SEOW, H-S and CHANDESA, T, 2024. A Novel Framework using Large Language Models to Automate Coursework Feedback for Computer Science modules. In: In The 16th International Conference on Education Technology and Computers (ICETC 2024), Porto, Portugal..
  • ABDALLA, I, SAKUNDARINI, N, MAY MAY, C C and CHANDESA, T, 2023. Detection of Fault Features in Remanufacturing of Automotive Components Using Image Processing and Computer Vision Techniques. In: In Innovative Manufacturing, Mechatronics & Materials Forum 2023 (iM3F 2023), Pekan, Pahang, Malaysia.
  • LIM, W X, CHEN, Z-Y, AHMED, A, CHANDESA, T and LIAO, I-Y, 2019. A review of machine learning techniques for applied eye fundus and tongue digital image processing with diabetes management system In: The International Conference on Digital Image and Signal Processing (DISP 2019).
  • CHANDESA, T and HARTLEY, M, 2010. Automated Sketcher using Edge Detection Techniques International Journals of Computers And Applications. 32(4), 404-411
  • CHANDESA, T, PRIDMORE, T and BARGIELA, A, 2009. Using Process-Behaviour charts to detect Occlusion and Camouflage in Visual Tracking In: Research for a Better Tomorrow: Impact in the 21st Century Conference.
  • CHANDESA, T, PRIDMORE, T and BARGIELA, A, 2009. Detecting occlusion and camouflage during visual tracking In: IEEE International Conference on Signal and Image Processing Applications (ICSIPA '09). 468-473

Computer Vision Laboratory

The University of Nottingham
Jubilee Campus
Wollaton Road
Nottingham, NG8 1BB


telephone: +44 (0) 115 8466543
email: andrew.p.french@nottingham.ac.uk