Prothito Shovon Majumder

Prothito Shovon Majumder

Lecturer, BRAC University.
CS Graduate, University of Dhaka.

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Posts

Hands-On Deep Learning and Open-source Large Language Model Workshop

less than 1 minute read

Published:

The Cognitive Agents and Interaction Lab at University of Dhaka arranged a workshop on deep learning and open-source LLMs, where I was one of the presenters and trainers. The contents discussed in the workshop included multilayer perceptrons, neural networks and their implementations in PyTorch, transformer architectures, attention mechanisms, LLM fine-tuning and deployments.

portfolio

Apellai

A subsonic client, built using Kotlin, for storing, filtering, searching music libraries and podcasts in servers, with additional options for like/dislike, media controls and server switching.

Deversorium

Built with MERN stack, a web application for managing the residence and meal system for hostels, with separate interfaces for tenants and owners.

Habitrix

A Flutter application for tracking progress of forming new habits and visualising over defined periods of time, with additional features of priority-based task scheduling.

publications

Vision Transformer and FFT-ReLU Fusion for Advanced Image Deblurring

Preprint, 2024

In this paper, we utilise the FFT-ReLU prior to enhance relevant frequency components using the Fast Fourier Transform (FFT) while applying ReLU sparsity to suppress noise. Our approach utilizes a Vision Transformer as a pre-processing model to generate a less blurry intermediate image by capturing both local and global features, which is then refined through FFT-ReLU, resulting in a sharp, high-quality output. Our experimental results demonstrate that our method consistently outperforms state-of-the-art image deblurring models, providing sharper and more visually compelling images.

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Blind Image Deblurring With FFT-ReLU Sparsity Prior

IEEE/CVF Winter Conference on Applications of Computer Vision, 2025

The paper introduces a method for blind image deblurring, which is the process of recovering a sharp image from a blurred one without prior knowledge about the blur kernel. The proposed method leverages a prior that targets the blur kernel to achieve effective deblurring across a wide range of image types. The authors' extensive empirical analysis shows that their algorithm achieves results that are competitive with the state-of-the-art blind image deblurring algorithms, and it offers up to two times faster inference, making it a highly efficient solution.

Recommended citation: Abdul Mohaimen Al Radi, Prothito Shovon Majumder, & Md. Mosaddek Khan. (2024). Blind Image Deblurring with FFT-ReLU Sparsity Prior.
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Deblurring in the Wild: A Real-World Dataset from Smartphone High-Speed Videos

Under review, 2025

We introduce the largest real-world image deblurring dataset constructed from smartphone slow-motion videos. Using 240 frames captured over one second, we simulate realistic long-exposure blur by averaging frames to produce blurry images, while using the temporally centered frame as the sharp reference. Our dataset contains over 42,000 high-resolution blur-sharp image pairs, making it approximately 10 times larger than widely used datasets, with 8 times the amount of different scenes, including indoor and outdoor environments, with varying object and camera motions. We benchmark multiple state-of-the-art (SOTA) deblurring models on our dataset and observe significant performance degradation, highlighting the complexity and diversity of our benchmark. Our dataset serves as a challenging new benchmark to facilitate robust and generalizable deblurring models.

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talks

teaching

CSE220: Data Structures

Undergraduate Course, CSE Department, BRAC University, 2024

This course introduces the concepts of the fundamental data structures of computer science, such as

  • arrays (linear and multidimensional)
  • linked lists (singly and doubly)
  • binary trees
  • stacks
  • heaps
  • hashing
  • graphs

CSE221: Algorithms

Undergraduate Course, CSE Department, BRAC University, 2025

This course digs deep into analysing time and space complexities of algorithms, and introduces some classic algorithms of computer science involving

  • sorting
  • searching
  • greedy algorithms
  • dynamic programming
  • graph algorithms

CSE230: Discrete Mathematics

Undergraduate Course, CSE Department, BRAC University, 2025

This is a foundational course for introducing mathematical concepts for building the basics of problem-solving. The course discusses

  • propositional logic
  • proofs
  • sets
  • linear homogeneous recurrence relations
  • prime numbers and divisibility
  • integer representations
  • pigeonhole principle
  • permutations and combinations

CSE320: Data Communications

Undergraduate Course, CSE Department, BRAC University, 2025

This course discusses the layers of the OSI model and the TCP/IP protocol suite, and discusses different functionalities and mathematical notions of the physical and data link layers. Topics include

  • network models
  • addressing principles of models
  • data and signals
  • digital transmissions
  • digital-to-analog conversion
  • analog transmission
  • multiplexing
  • error detection in data link layer
  • multiple access in data link layer