Mr Raktim Kumar Mondol

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.

  • Journal articles | 2024
    Mondol RK; Millar EKA; Sowmya A; Meijering E, 2024, 'BioFusionNet: Deep Learning-Based Survival Risk Stratification in ER+ Breast Cancer Through Multifeature and Multimodal Data Fusion', IEEE Journal of Biomedical and Health Informatics, http://dx.doi.org/10.1109/JBHI.2024.3418341
    Journal articles | 2023
    Mondol RK; Millar EKA; Graham PH; Browne L; Sowmya A; Meijering E, 2023, 'hist2RNA: An Efficient Deep Learning Architecture to Predict Gene Expression from Breast Cancer Histopathology Images', Cancers, 15, pp. 2569, http://dx.doi.org/10.3390/cancers15092569
    Journal articles | 2022
    Mondol RK; Truong ND; Reza M; Ippolito S; Ebrahimie E; Kavehei O, 2022, 'AFExNet: An Adversarial Autoencoder for Differentiating Breast Cancer Sub-Types and Extracting Biologically Relevant Genes', IEEE/ACM Transactions on Computational Biology and Bioinformatics, 19, pp. 2060 - 2070, http://dx.doi.org/10.1109/TCBB.2021.3066086
  • Conference Papers | 2024
    Mondol RK; Millar EKA; Sowmya A; Meijering E, 2024, 'MM-Survnet: Deep Learning-Based Survival Risk Stratification in Breast Cancer Through Multimodal Data Fusion', in Proceedings - International Symposium on Biomedical Imaging, http://dx.doi.org/10.1109/ISBI56570.2024.10635810
    Preprints | 2024
    Mondol RK; Millar EKA; Sowmya A; Meijering E, 2024, BioFusionNet: Deep Learning-Based Survival Risk Stratification in ER+ Breast Cancer Through Multifeature and Multimodal Data Fusion, , http://dx.doi.org/10.48550/arxiv.2402.10717
    Preprints | 2024
    Mondol RK; Millar EKA; Sowmya A; Meijering E, 2024, MM-SurvNet: Deep Learning-Based Survival Risk Stratification in Breast Cancer Through Multimodal Data Fusion, http://arxiv.org/abs/2402.11788v1
    Preprints | 2023
    Mondol RK; Millar EKA; Graham PH; Browne L; Sowmya A; Meijering E, 2023, hist2RNA: An efficient deep learning architecture to predict gene expression from breast cancer histopathology images, http://dx.doi.org/10.3390/cancers15092569
    Conference Papers | 2015
    Hasan R; Nandy T; Abedin MI; Hassan A; Mondol RK, 2015, 'Simulation of carrier mobility through Graphene Nanoribbon based DNA sensor', in 2015 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), IEEE, pp. 1 - 5, presented at 2015 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), 05 March 2015 - 07 March 2015, http://dx.doi.org/10.1109/icecct.2015.7225951
    Conference Papers | 2015
    Hassan A; Hasan Z; Mondol RK, 2015, 'Analytical formulation of graphene nanoribbon varactor diode', in 2015 International Conference on Advances in Computer Engineering and Applications, IEEE, pp. 993 - 996, presented at 2015 International Conference on Advances in Computer Engineering and Applications (ICACEA), 19 March 2015 - 20 March 2015, http://dx.doi.org/10.1109/icacea.2015.7164851
    Conference Papers | 2015
    Hassan A; Mondol RK; Hasan MR, 2015, 'Computer network design of a company — A simplistic way', in 2015 International Conference on Advanced Computing and Communication Systems, IEEE, pp. 1 - 4, presented at 2015 International Conference on Advanced Computing and Communication Systems (ICACCS), 05 January 2015 - 07 January 2015, http://dx.doi.org/10.1109/icaccs.2015.7324121
    Conference Papers | 2015
    Hassan A; Mondol RK; Jafar IB; Shahin MZI, 2015, 'Theoretical modeling of current measurement in nanoscale device considering Green's function formalism', in 2015 International Conference on Advances in Computer Engineering and Applications, IEEE, pp. 988 - 992, presented at 2015 International Conference on Advances in Computer Engineering and Applications (ICACEA), 19 March 2015 - 20 March 2015, http://dx.doi.org/10.1109/icacea.2015.7164850
    Conference Papers | 2015
    Mondol RK; Hassan A; Hasan R, 2015, 'Quantum capacitance in strained armchair Graphene nanoribbon considering Edge effect', in 2015 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), IEEE, pp. 1 - 5, presented at 2015 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), 05 March 2015 - 07 March 2015, http://dx.doi.org/10.1109/icecct.2015.7225950
    Conference Papers | 2015
    Mondol RK; Imran Khan M; Mahbubul Hye AK; Hassan A, 2015, 'Hardware architecture design of face recognition system based on FPGA', in 2015 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), IEEE, pp. 1 - 5, presented at 2015 International Conference on Innovations in Information,Embedded and Communication Systems (ICIIECS), 19 March 2015 - 20 March 2015, http://dx.doi.org/10.1109/iciiecs.2015.7193228
    Conference Papers | 2014
    Khan MI; Mondol RK; Zamee MA; Tarique TA, 2014, 'Hardware architecture design of Anemia detecting regression model based on FPGA', in 2014 International Conference on Informatics, Electronics & Vision (ICIEV), IEEE, presented at 2014 International Conference on Informatics, Electronics & Vision (ICIEV), 23 May 2014 - 24 May 2014, http://dx.doi.org/10.1109/iciev.2014.6850814
    Conference Papers | 2014
    Khan MI; Mondol RK, 2014, 'FPGA Based Leaf Chlorophyll estimating regression model', in The 8th International Conference on Software, Knowledge, Information Management and Applications (SKIMA 2014), IEEE, pp. 1 - 6, presented at 2014 8th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), 18 December 2014 - 20 December 2014, http://dx.doi.org/10.1109/skima.2014.7083557
    Conference Papers | 2014
    Saha S; Hossain MM; Alam MN; Mondol RK, 2014, 'Fuzzy logic analysis of knitted fabrics spirality', in Fifth International Conference on Computing, Communications and Networking Technologies (ICCCNT), IEEE, pp. 1 - 5, presented at 2014 5th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 11 July 2014 - 13 July 2014, http://dx.doi.org/10.1109/icccnt.2014.6963109

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.