Shaira Tabassum
About
Shaira Tabassum is currently a Researcher in the Department of Computer Science at NTNU. She is an Erasmus Mundus Scholar, having completed her master's in Computational Colour and Spectral Imaging (COSI) program. Her research interest includes 3D Reconstruction, Image Processing, Computer Vision, and Deep Learning.
Before joining the COSI program, Shaira conducted research at Kyushu University, Japan, as a Japanese Government (MEXT) Scholar in the Department of Information Science and Technology. There, she applied machine learning techniques to medical data analysis, intending to enhance the performance of remote healthcare systems.
In addition to her research experience, Shaira has worked in industry roles, including as a Software Engineer at NAMS Innovation and as a Jr. Software Engineer at Grameen Communications. She also contributed to academia, serving as a Teaching Assistant at United International University (UIU) for two years.
Shaira holds a Bachelor's degree in Computer Science and Engineering (CSE) from UIU, graduating in October 2019. During her undergraduate studies, she was recognized with the prestigious Google Women Techmakers Scholarship in 2019 in Sydney, Australia for her academic results and leadership role in expanding women’s participation in technology.
Competencies
Research
Publications
- Tabassum, S., & Amirshahi, S. A. (2024, June). Quality of NeRF Changes with the Viewing Path an Observer Takes: A Subjective Quality Assessment of Real-time NeRF Model. In 2024 16th International Conference on Quality of Multimedia Experience (QoMEX) (pp. 88-91). IEEE.
- Tabassum, S., Abedin, N., Rahman, M. M., Rahman, M. M., Ahmed, M. T., Islam, R., & Ahmed, A. (2022). An online cursive handwritten medical words recognition system for busy doctors in developing countries for ensuring efficient healthcare service delivery. Scientific reports, 12(1), 3601.
- Tabassum, S., Abedin, N., Maruf, R. I., Ahmed, M. T., & Ahmed, A. (2022, March). Improving health status prediction by applying appropriate missing value imputation technique. In 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech) (pp. 345-348). IEEE.
- Tabassum, S., Takahashi, R., Rahman, M. M., Imamura, Y., Sixian, L., Rahman, M. M., & Ahmed, A. (2021, May). Recognition of doctors’ cursive handwritten medical words by using bidirectional LSTM and SRP data augmentation. In 2021 IEEE Technology & Engineering Management Conference-Europe (TEMSCON-EUR) (pp. 1-6). IEEE.
- Podder, K. K., Tabassum, S., Khan, L. E., Salam, K. M. A., Maruf, R. I., & Ahmed, A. (2021, May). Design of a sign language transformer to enable the participation of persons with disabilities in remote healthcare systems for ensuring universal healthcare coverage. In 2021 IEEE Technology & Engineering Management Conference-Europe (TEMSCON-EUR) (pp. 1-6). IEEE.
- Tabassum, S., Sampa, M., Maruf, R., Yokota, F., Nakashima, N., & Ahmed, A. (2020). An analysis on remote healthcare data for future health risk prediction to reduce health management cost. In APAMI 2020c: 11th Biennial Conference of the Asia-Pacific Association for Medical Informatics (Vol. 115, p. 119).
- Tabassum, S., Sampa, M. B., Islam, R., Yokota, F., Nakashima, N., & Ahmed, A. (2020, November). A data enhancement approach to improve machine learning performance for predicting health status using remote healthcare data. In 2020 2nd International Conference on Advanced Information and Communication Technology (ICAICT) (pp. 308-312). IEEE.
- Tabassum, S., Ullah, S., Al-Nur, N. H., & Shatabda, S. (2020). Poribohon-BD: Bangladeshi local vehicle image dataset with annotation for classification. Data in brief, 33.
- Tabassum, S., Ullah, M. S., Al-Nur, N. H., & Shatabda, S. (2020, June). Native vehicles classification on Bangladeshi roads using CNN with transfer learning. In 2020 IEEE Region 10 Symposium (TENSYMP) (pp. 40-43). IEEE.
- Tabassum, S., Zaman, M. I. U., Ullah, M. S., Rahaman, A., Nahar, S., & Islam, A. M. (2019, December). The cardiac disease predictor: IoT and ML driven healthcare system. In 2019 4th International Conference on Electrical Information and Communication Technology (EICT) (pp. 1-6). IEEE.
- Zaman, M. I. U., Tabassum, S., Ullah, M. S., Rahaman, A., Nahar, S., & Islam, A. M. (2019, May). Towards IoT and ML driven cardiac status prediction system. In 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT) (pp. 1-6). IEEE.