The University of Georgia
Working in the InforMation PRocEssing and SenSing (IMPRESS) lab as an GRA under Dr. Mehmet Kurum. The focus of the lab includes Electromegnetic wave modelling, microwave remote sensing, off-road robotics, etc.
Working in the InforMation PRocEssing and SenSing (IMPRESS) lab as an GRA under Dr. Mehmet Kurum. The focus of the lab includes Electromegnetic wave modelling, microwave remote sensing, off-road robotics, etc.
Worked as an adjunct lecturer for Summer 2023 and Fall 23 at the Department of Computer Science and Engineering at BRAC University.
Teaching:
CSE 250: Circuits and Electronics
Worked in the Machine Learning Group under professor Muhammad E. H. Chowdhury. The main focus of the group is to use ML approaches in Biomedical instrumentation.
Worked in different R&D projects assigned to the Biomedical team and Hardware team to design and develop IoT based Hardware and Firmware.
Python to access web data, Python data structures, Using databases with python, Retrieving, Processing, and Visualizing Data with Python, Data Analysis using Python
Machine Learning (ML) Algorithms, Artificial Neural Network; Libraries: Pandas, Numpy, Matplotlib, Tensorflow, Pytorch
Semantic Segmentation, Landmark Detection, Activity Recognition, Object Detection and Classification
Arduino Projects, Firmware implementation, Circuit design and Implementation
This has been my 4th-year 1st-semester thesis project under the supervision of Dr Mosabber Uddin Ahmed. In this project, we have tried to detect the reading activity (reading English, Japanese horizontal, Japanese vertical and not reading) of 10 different users from JINS MEME EOG glasses data.
This project aims to solve the drinking water problem in some parts of Dhaka city. The system can purify the water before entering the reserviour tank. The project is funded by IEEE SIGHT/HAC.
This project tries to scrap the iedcr.gov.bd website to show the required data using python. When Run, this programms will access the iedcr website and fetch the latest data and show the outputs. Modifying this programs we can easily use those data for further analysis or represent them in different platforms.
This deep learning based project takes the camera/web-cam images/videos to classify 7 different expressions: surprise, happy, sad, neutral, angry, disgust, fear. It was done following the Coursera project: Facial Expression Recognition with Keras
This is a ardiono based Line follower robot. Which has extra features like: Obstacle avoiding, wall following, stopping at cave, sharp turning, completing line gap.
This project involved detection of 21 different classes of vehicles in Dhaka city. We explored AI-based scheme based on YOLOv5 models & weachieved promising results.