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Lecturer
University of Asia Pacific
January 2022 - Present

Lecturer
International University of Business Agriculture and Technology (IUBAT)
October 2021 - January 2022 

  A Deep Learning Approach to Predict Autism Spectrum Disorder Using Multisite 
Resting-State fMRI. (Thesis) [2020 - 2021]
This work is based on autism spectrum disorder (ASD) detection using derived functional 
connectivity features from rs-fMRI data of the ABIDE dataset. A deep neural network 
(DNN) classifier has been used to perform the classification task.
  Face Occlusion Recognition for Masked Faces [2021 - Present]
The objective of this work is to remove mask objects in facial images. It comprises of
two stages: unmasking of masked faces and image completion of the removed mask 
region.
  A Comprehensive Study on Atlas-based Classification of Autism Spectrum Disorder 
using Functional Connectivity Features from Resting state fMRI [under review]
This work presents a comprehensive study using 11 different brain atlases to extract 
regions of interest and 3 different measures to compute functional connectome from 
fMRI times-series data which would aid in autism detection. A deep neural network 
classifier identified as Model-2 that has been proposed in the author’s previous research 
work is used to perform prediction task. 

Industrial attachment training at Chittagong Port Authority (CPA)

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• Machine Learning
• Deep Learning
• Computer Vision
• Data Science
• Data Mining
• Artificial Intelligence

International Peer Reviewed Journal:
1.  Faria Zarin Subah, Kaushik Deb, Pranab Kumar Dhar, Takeshi Koshiba. “A Deep Learning  Approach to Predict Autism Spectrum Disorder Using Multisite Resting-State fMRI”.  Applied Sciences (2021)