Pramit Dutta
Pramit Dutta
Greetings! I am Pramit Dutta, a Master of Applied Science (MASc) candidate in Computer Engineering with a focus on Artificial Intelligence at the University of Guelph. I have a bachelor degree in Electronics and Telecommunication Engineering from Chittagong University of Engineering and Technology. I am currently working as a Graduate Research Assistant in the AI enabled Medical Imaging Lab under the supervision of Dr. Eranga Ukwatta.
My research primarily focuses on multimodal approaches, with a particular emphasis on Vision-Language Models and their potential in domains like medical imaging. I am interested in developing data-efficient and scalable solutions by using VLMs to align and interpret visual and textual information. My goal is to advance AI-driven healthcare by integrating text and image within multimodal frameworks to enhance model understanding and generalization.
Thank you for your interest in my profile. Please take a moment look at my CV:
My CV
Master of Applied Science in Computer Engineering Candidate
Affiliation with CSAI (Collaborative Specialization in Artificial Intelligence)
School of Engineering, University of Guelph
Ontario, Canada
September 2024 – Present
CGPA: 4.00 out of 4.00 (After 3rd Semester)
Bachelor of Science (Engineering)
Department of Electronics and Telecommunication Engineering
Chittagong University of Engineering and Technology,
Chittagong, Bangladesh
January 2018 – March 2023
CGPA: 3.81 out of 4.00
Title: Graduate Research Assistant
Institution: AI-Enabled Medical Imaging Lab, University of Guelph
Duration: September 2024 – Present
Description: The AI-Enabled Medical Imaging Lab focuses on advancing health
care solutions through AI-driven approaches. As a Graduate Research Assistant, my
responsibilities include developing and optimizing artificial intelligence models for
multimodal learning, with an emphasis on creating innovative solutions for medical image
analysis and improving patient care outcomes.
Title: Graduate Teaching Assistant
Institution:University of Guelph
Duration: September 2024 – December,2024 (4month)
Description: As a Graduate Teaching Assistant in Signal Processing (Fall 2024), I was
responsible for conducting laboratory sessions to help students grasp the fundamental concepts
in signal processing. My role also involved grading assignments and invigilating exams.
Additionally, I collaborated with the course instructor and fellow GTAs to design practical lab
exercises that aligned with the course objectives.
A representation of my proficiency in each skill (Drag to Scroll)
Developing VLM-based systems
that integrates images and text
Core frameworks for
multimodal models
Medical reasoning and
synthesis tasks
Medical image analysis with
Deep Learning & SSL
Used in research
project on medical imaging
Good Grasp of signal processing with applications in image and audio analysis, also worked as a GTA for Signal Processing.
Experienced with HPC clusters and Shell scripting
Experience in automated IoT system design
Position: Graduate Research Assistant (GRA)
Lab: AI-Enabled Medical Imaging Lab, University of Guelph
Duration: September 2024 – Present
Description: My research focuses on domain adoption for vision language model that integrate radiological images with clinical context to support AI-driven healthcare decisions. I generally prefer to take context-driven approach, and work in collaboration with the clinicians to ensure the clinical relevance of these models and ensure they align with real-world medical workflows. In addition, I am exploring the potential of my work extending this work through collaborations with the veterinary and business schools into different domains.
| Serial No | Title | Type | URL |
|---|---|---|---|
| 01 | Self-Supervised Learning for Retinal Disease Classification: Reducing Annotation Dependency with Transformation-Based Pretext Learning with Limited Labels | Abstract/Poster | [Check Out The Paper] |
| 02 | Conv-ViT: A Convolution and Vision Transformer based Hybrid Feature Extraction Method to Detect Retinal Disease Detection | Journal | [Check Out The Paper] |
| 03 | Identifying Counterfeit Products using Blockchain Technology in Supply Chain System | Conference Paper | [Check Out The Paper] |
| 04 | COVID-19 Detection using Transfer Learning with Convolutional Neural Network | Conference Paper | [Check Out The Paper] |
| 05 | Optimization of Temperature and Relative Humidity in an Automatic Egg Incubator Using Mamdani Fuzzy Inference System | Conference Paper | [Check Out The Paper] |
| 06 | Multi-Classification of Brain Tumour Images Using Transfer Learning Based Deep Neural Network | Conference Paper | [Check Out The Paper] |
Title: Conv-ViT: A Convolution and Vision Transformer based Hybrid Feature Extraction Method to Detect Retinal Disease Detection
Description: A triple stream feature extractor which fuse the feature extracted by Inception V3, ResNet-50 and Vision Transformer.
Supervisor: Dr. Md. Azad Hossain
1. Reviewer at IAES International Journal of Artificial Intelligence [Certificate]
2. Reviewer at Bulletin of Electrical Engineering and Informatics(BEEI) [Certificate]
01. Machine Learning an online non-credit course authorized by Stanford University and offered
through Coursera
[External Link]
02. DeepLearning.AI TensorFlow Developer Professional Certificate
[External Link]
03. AI For Everyone an online non-credit course authorized by DeepLearning.AI and offered
through
Coursera
[External Link]
04.Internet of Things provided by Planetter Ltd.
[External Link]
05.TensoeFlow Advance Techniques Specialization Certificate authorized by DeepLearning.AI and
offered through Coursera
[External Link]
06.AI for Medicine Specialization Certificate authorized by DeepLearning.AI and
offered through Coursera
[External Link]
1. 2nd Runner Up in Recruitment4.0 organized by JobMarketBDLtd.
[Click Here]
2. 2nd Runner Up in Leadership4.0 organized by JobMarketBDLtd.
[Click Here]
© Copyright Pramit Dutta 2021
*This Portfolio was Last Updated on: 26th Auguest, 2025 (EST- Eastern Standard Time)
