Mr Raktim Kumar Mondol
Casual Academic
Engineering
Computer Science and Engineering
Raktim Kumar Mondol is a PhD candidate in Computer Science and Engineering, specializing in computer vision, bioinformatics, multimodal analysis, and deep learning. He completed his MEng in Engineering with High Distinction from RMIT University, Australia, in 2019. Mondol's research interests include histopathological image analysis, clinical prognosis prediction, and enhancing clinical understanding through the interpretability of computational models. He has been awarded prestigious scholarships from both UNSW and RMIT University.
E-mail
- Publications
- Media
- Grants
- Awards
- Research Activities
- Engagement
- Teaching and Supervision
2021 Awarded Research Training Program (RTP) Scholarship for Doctoral Research Studies
2019 Completed Masters by Research with High Distinction
2017 RMIT Research Stipend Scholarship
2017 RMIT Research International Tuition Fee Scholarship
2013 B.Sc. in Electrical and Electronic Engineering with High Distinction
2013 Vice Chancellor Award Spring 2013, BRAC University
2010 Dean Award Fall 2010, Fall 2011, BRAC University
Reflecting on my research activities as a PhD candidate in Computer Science and Engineering, my focus spans across several innovative domains, including computer vision, bioinformatics, multimodal analysis, and deep learning.
Additionally, my research extends to multimodal risk prediction and survival analysis. This involves integrating various types of data and computational techniques to predict patient outcomes, particularly in oncology. By analyzing diverse data sets, from clinical metrics to imaging data, I aim to develop models that can more accurately forecast patient prognosis and survival rates. This approach is crucial in personalizing patient care and improving treatment strategies.
Another significant part of my research revolves around the interpretability of computational models in clinical settings. I strive to make these advanced models accessible and understandable to healthcare professionals, enhancing their practical utility in patient care. The overarching goal of my research is to bridge the gap between complex technological solutions and their real-world applications in healthcare, ultimately aiming to improve patient outcomes and advance the field of medical technology. My research activities combine theoretical exploration with practical application, all driven by the aspiration to make meaningful contributions to healthcare through innovative technology.
My Teaching
The courses I teach are designed to offer students hands-on experience and theoretical knowledge, preparing them for challenges in both academic and industry settings. I find great fulfillment in guiding students to understand and apply complex concepts, and in contributing to their growth as future leaders in technology.
Currently, I tutor in the following courses:
- COMP9444 - Neural Networks and Deep Learning
- COMP9517 - Computer Vision
- COMP9414 - Artificial Intelligence
These courses align closely with my research interests. They provide an ideal platform to integrate my research findings with teaching, enhancing the learning experience for my students by providing them with up-to-date knowledge and practical skills.