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Md. Monibor Rahman (Study Leave USA)

Assistant Professor

Contact No: 01915094763

Email Address: engr.monibor@gmail.com

Status: On Leave

About:

Research Area:

Research Details:

1 Brain tumor segmentation, survival prediction, tumor grading, and MGMT status using MRI.
2 Abdominal multi-organ segmentation.
3 Prediction of cavity faults of the CEBAF system.
4 Clustering of multivariate time series signals.

Education:

Doctor of Philosophy (Ph.D.) in Electrical and Computer Engineering, [Expected-2024]

Old Dominion University, USA

B. Sc. in Electrical and Electronic Engineering, March 2008

Khulna University of Engineering and Technology (KUET), Bangladesh

Publications:

Journals:

1)    Lasitha Vidyaratne, Adam Carpenter, Tom Powers, Chris Tennant, Khan M Iftekharuddin, Md Monibor Rahman, Anna S Shabalina, “Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification at Jefferson Laboratory”. Frontiers in artificial intelligence, 2022.

2)    Linmin Pei, Lasitha Vidyaratne, Md Monibor Rahman, Khan M Iftekharuddin, “Context aware deep learning for brain tumor segmentation, subtype classification, and survival prediction using radiology images”. Scientific Reports 10, 19726 (2020).

Conferences:

1)    LS Vidyaratne, A Carpenter, R Suleiman, C Tennant, D Turner, Khan Iftekharuddin, Md Rahman, “Initial Studies of Cavity Fault Prediction at Jefferson Laboratory”, 18th Int. Conf. on Acc. and Large Exp. Physics Control Systems ICALEPCS2021, Shanghai, China.

2)    A. Carpenter , P. Degtiarenko, R. Suleiman, C. Tennant, D. Turner, L. S. Vidyaratne, K. Iftekharuddin, and Md. Monibor Rahman, “Using AI for Management of Field Emission in SRF Linacs”,18th Int. Conf. on Acc. and Large Exp. Physics Control Systems ICALEPCS2021, Shanghai, China.

3)    A Shabalina, A Carpenter, M Rahman, C Tennant, L Vidyaratne, “Machine Learning Based Cavity Fault Classification and Prediction”, Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States), 2020.

4)    Linmin Pei, Lasitha Vidyaratne, Md Monibor Rahman, Khan M Iftekharuddin , “Deep learning with context encoding for semantic brain tumor segmentation and patient survival prediction”, Medical Imaging 2020: Computer-Aided Diagnosis.

5)    Linmin Pei, Lasitha Vidyaratne, M Monibor Rahman, Zeina A Shboul, Khan M Iftekharuddin , “Multimodal brain tumor segmentation and survival prediction using hybrid machine learning”, International MICCAI Brainlesion Workshop, 2019.

6)    Linmin Pei, Lasitha Vidyaratne, Wei-Wen Hsu, Md Monibor Rahman, Khan M Iftekharuddin, “Brain Tumor Classification Using 3D Convolutional Neural Network”, International MICCAI Brainlesion Workshop, 2019.

7)    Sajratul Yakin Rubaiat, Md Monibor Rahman, and Md Kamrul Hasan , “Important Feature Selection & Accuracy Comparisons of Different Machine Learning Models for Early Diabetes Detection”, 2018 International Conference on Innovation in Engineering and Technology (ICIET).

8)    Muhammad Masud Rana, Rafiur Rahman, and Md Monibor Rahman , “Solid state transformer based on cascade multilevel converter for distribution network”, 2016 9th International Conference on Electrical and Computer Engineering (ICECE).

9)    Md Tanvir Hasan, Md Monibor Rahman, ANM Shamsuzzaman, Md Sherajul Islam, Ashraful G Bhuiyan, “InN-based dual channel high electron mobility transistor”, 2008 International Conference on Electrical and Computer Engineering.

Profile Link:

https://scholar.google.com/citations?user=4Ydpkg0AAAAJ&hl=en

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