University of Science and Technology Chittagong

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Topu Biswas

Research Lecturer
Faculty of Science, Engineering & Technology


Topu Biswas (Member, IEEE) is currently serving as a Research Lecturer at the department of Computer Science and Engineering. Prior to joining the USTC, he received a Master of Engineering Science (M.Eng.Sc.) degree from Multimedia University (MMU) and a B.Sc. degree in Electrical and Electronic Engineering degree from the Pabna University of Science and Technology (PUST). His research interests include developing different machine learning and artificial intelligence-based systems to advance healthcare through the lens of equity inclusion. The research project “Automated Diagnosis and Prognosis of Chronic Wounds for e-Health Applications” (part of his master’s degree) have been awarded eight national and international awards, including the Gold Medal and “the Best of the Best Award (within 247 Projects).” Apart from his study, he also held different leadership positions. He was part of the organizing team for multiple national and international conferences and was also elected President of the MMU Postgraduates Society (2019/2020) which represents the interests of all MMU postgraduate students of the two campuses and eight faculties at MMU.


  • M.Eng.Sc.-Multimedia University (MMU), Malaysia
  • B.Sc. in Electrical & Electronic Engineering (EEE), Pabna University of Science and Technology (PUST)

Program Affiliated

  • B.Sc. in Computer Science and Engineering (CSE)

Areas of Interest

  • AI for healthcare
  • Computer vision
  • Image Processing
  • Machine Learning
  • Deep Learning

Courses Taught

  • Neural Network and Fuzzy Systems
  • Computer Graphics and Image Processing
  • Computer Graphics and Image Processing Lab
  • Artificial Intelligence & Expert Systems
  • Artificial Intelligence & Expert Systems Lab
  • Computer Fundamentals
  • Computer Applications in Pharmacy

Journals & Articles

  • A Machine Learning Web App to Predict Diabetic Blood Glucose Based on a Basic Noninvasive Health Checkup, Sociodemographic Characteristics, and Dietary Information: Case Study. Published in: JMIR Diabetes vol 8 (2023).  PMID: 37999944