Abu Zahid Bin Aziz

Abu Zahid Bin Aziz

Research Assistant

University of Utah

About Me

A Computer Science(CS) PhD student at the University of Utah with an interest in Data Analysis, Deep Learning and Web application development. I also work as a Research Assistant at the Elhabian Lab of SCI, University of Utah where I am working on different deep learning based statistical shape modeling for medical images.

I completed my bachelor’s from Rajshahi Univerisity of Engineering & Technology, Bangladesh where I started my research journey by working on various deep learning applications in bioinformatics-related projects. I also worked at a start-up after my undergraduate degree. There, I worked on a wide range of aspects, from implementing research methodologies to deploying ML/DL models to production for public usage.

Interests
  • Deep Learning
  • Medical Imaging
  • Bioinformatics
Education
  • PhD in Computing (Specialization - Image Analysis), 2024 - Present

    University of Utah

  • MS in Computing (Specialization - Image Analysis), 2022 - 2024

    University of Utah

  • BSc in Computer Science & Enginerring, 2016-2021

    Rajshahi University of Engineering & Technology, Bangladesh

Skills

Python

100%

Deep Learning

100%

Data Visualization

80%

AWS

80%

Backend Development

80%

Experience

 
 
 
 
 
Scientific Computing and Imaging Institute at the University of Utah
Research Assistant
August 2022 – Present Utah

Responsibilities include:

  • Deep learning based statistical shape modeling on different medical imaging datasets
  • Contributing to existing statistical shape modeling-based projects. (ShapeWorks)
 
 
 
 
 
MyMedicalHUB
Junior AI Developer
MyMedicalHUB
February 2021 – July 2022 Dhaka, Bangladesh

Responsibilities include:

  • Applying state-of-the-art algorithms for various computer vision tasks such as pose estimation, instance segmentation.
  • Developing and monitoring a live AI based server that handles thousands of API requests everyday.
 
 
 
 
 
MyMedicalHUB
Research Intern
MyMedicalHUB
June 2020 – January 2021 Dhaka, Bangladesh

Responsibilities include:

  • Developed a deep learning method for detecting abnormalities from musculoskeletal images.
  • Contributed to multiple human pose estimation based projects.

Accomplish­ments

Research article peer reviewer
Worked as a reviewer at this Q1 journal (IF: 3.752)
See certificate
Coursera
Mathematics for Machine Learning - Multivariate Calculus
See certificate
Coursera
Data Analysis with PySpark
Learned applying different queries to your dataset to extract useful Information and how to visualize this information using matplotlib
See certificate
Coursera
Deep Learning Specialization
See certificate

Projects

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Probabilistic approaches for Data Augmentation
This is for CS6190 probabilistic machine learning project. Here, we have taken a small dataset of medical images (~230) and used two probabilistic approaches, generative adversarial networks (GAN) and variational autoencoder (VAE), to generate more realistic images to increase the number of samples, which play significant roles in deep learning-based methodologies.
Probabilistic approaches for Data Augmentation
Deep Transfer Learning-Based Musculoskeletal Abnormality Detection
We utilized the transfer learning approach to detect abnormalities because of its ability to share knowledge from similar tasks. We used an updated version of a pre-trained model (DenseNet169) to detect abnormalities for five different organs of the upper extremity.
Deep Transfer Learning-Based Musculoskeletal Abnormality Detection

Contact

Feel free to contact me if it’s for just chatting.