About Me

Hi there! I'm Rashik Shahriar Akash and I'm

.

I am a PhD student in Computer Science at Kennesaw State University and a Graduate Research Assistant in the Trustworthy Machine Learning Research Lab. My research focuses on trustworthy medical AI, computer vision, and deep learning for healthcare, especially retinal imaging and early disease screening.

As a Gold Medalist from Daffodil International University, I work on AI systems that support reliable clinical decision-making. My recent work spans diabetic retinopathy detection, polyp segmentation, cervical cancer screening, dengue prediction, and genomic data analysis.

Research Areas: Trustworthy Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Computational Biology, AI for Social Good
Research Topics: Healthcare AI, Medical Image Analysis, Diabetic Retinopathy Detection, Early Disease Screening, Genomic Data Analysis

Education

  • PhD Student

    PhD in Computer Science

    Kennesaw State University

    Expected 2029

    Research Focus: Medical AI, Computer Vision, Deep Learning

  • GRADUATED

    Bachelor of Science in Computer Science & Engineering

    Daffodil International University

    May 2020 - June 2024

    CGPA: 3.93/4.00 | Gold Medalist of 12th Convocation

Research & Publications

BibTeX Citation

@article{https://doi.org/10.1155/jotm/1709439,
author = {Bhuiyan, Md Atik and Akash, Md Rashik Shahriar and Islam, Radiful and Polash, Shohidul Islam and Khushbu, Sharun Akter},
title = {Early Dengue Prediction in Bangladesh: A Comparative Study With Feature Analysis, Explainable Artificial Intelligence, and Model Optimization},
journal = {Journal of Tropical Medicine},
volume = {2025},
number = {1},
pages = {1709439},
year = {2025}
}

BibTeX Citation

@article{islam2024samu,
  title={SAMU-Net: A dual-stage polyp segmentation network with a custom attention-based U-Net and segment anything model for enhanced mask prediction},
  author={Islam, Radiful and Akash, Rashik Shahriar and Rony, Md Awlad Hossen and Hasan, Md Zahid},
  journal={Array},
  pages={100370},
  year={2024},
  publisher={Elsevier}
}

BibTeX Citation

@article{akash2024cervixpert,
  title={CerviXpert: A multi-structural convolutional neural network for predicting cervix type and cervical cell abnormalities},
  author={Akash, Rashik Shahriar and Islam, Radiful and Badhon, SM Saiful Islam and Hossain, KSM Tozammel},
  journal={Digital Health},
  volume={10},
  pages={20552076241295440},
  year={2024},
  publisher={SAGE Publications}
}

BibTeX Citation

@inproceedings{tapu2023review,
  title={A Review on the Impacts of Social Media on the Mental Health},
  author={Tapu, Md Abu Bakar Siddiq and Akash, Rashik Shahriar and Fahim, Hafiz Al and Jarin, Tanin Mohammad and Bhuiyan, Touhid and Reza, Ahmed Wasif and Arefin, Mohammad Shamsul},
  booktitle={International Conference on Intelligent Computing \& Optimization},
  pages={181--195},
  year={2023},
  organization={Springer}
}

BibTeX Citation

@inproceedings{akash2023comprehensive,
  title={A Comprehensive Review on Family Budget Management},
  author={Akash, Rashik Shahriar and Ullah, Mohammad and Islam, Radiful and Nahid, Sayed and Reza, Ahmed Wasif and Arefin, Mohammad Shamsul},
  booktitle={International Conference on Intelligent Computing \& Optimization},
  pages={379--391},
  year={2023},
  organization={Springer}
}

BibTeX Citation

@inproceedings{islam2025qpolypnet,
  title={QPolypNet: A Quantum-Inspired Deep Learning Model for Polyp Segmentation},
  author={Islam, Md Majedul and Akash, Rashik Shahriar and Azim, Sayed Mehedi and He, Selena},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={969--978},
  year={2025}
}

Projects

MRI Image Analysis for Brain Tumor Detection and Classification

Implemented deep learning models to classify brain MRI scans into four tumor categories, achieving 88.63% accuracy with InceptionV3.

Python TensorFlow InceptionV3 CNN Deep Learning
 View on GitHub

Accurate Breast Cancer Prediction using Machine Learning

Implemented machine learning algorithms to predict breast cancer diagnosis based on cell nucleus characteristics, with Logistic Regression and XGBoost achieving competitive accuracy.

Python scikit-learn XGBoost Logistic Regression
 View on GitHub

DNA Kingdom Prediction and Taxonomic Analysis Using PySpark

Analyzed DNA codon usage patterns to classify sequences into taxonomic kingdoms and explored evolutionary trends using PySpark for large-scale data processing.

Python PySpark Big Data Machine Learning
 View on GitHub

DIU Transport Management System

A Django-based system that automates record keeping for bus management, route management, and passenger management (booking and payments).

Django Python MySQL
 View on GitHub

Work Experience

  • Current

    Graduate Research Assistant

    Trustworthy Machine Learning Research Lab, Kennesaw State University

    August 2025 – Present

    • Developing and evaluating trustworthy deep learning models for diabetic retinopathy detection in NIH-funded research.
    • Focusing on cross-domain generalization, uncertainty-aware prediction, and reducing false negatives in screening workflows.
  • Research

    Research Assistant

    Health Informatics Research Lab

    July 2024 – July 2025

    • Collaborated on computer vision and medical imaging research projects.
    • Contributed to studies that resulted in Q1/Q2 journal publications.
  • Research

    Research Assistant

    Apurba-DIU Research and Development Lab   [Experience Letter]

    April 2023 – June 2024

    • Worked on 3 government-funded projects.
    • Character and word-level OCR data annotation and segmentation.
    • Tested the Font Interoperability Engine and Screen Reader Alo.
    • Contributed to literature reviews, custom algorithm development, implementation, and optimization.
  • Teaching

    Trainer — Advanced ML & DL Bootcamp

    DIU NLP & ML Research Lab   [Experience Letter]

    May 2023 – December 2023

    • Developed and delivered a hands-on curriculum for the bootcamp.
    • Led lectures, workshops, and practical sessions on TensorFlow and PyTorch.
    • Mentored participants and supervised capstone projects.
  • Teaching

    Trainer — ITEE Batch

    Daffodil International University

    April 2024

    • Taught classes preparing students for the IT Engineers Examination.
    • Developed instructional materials and practice tests.
  • Teaching

    Lab Prefect — Algorithm Lab

    Daffodil International University

    May 2022 – December 2022

    • Assisted in teaching algorithm lab classes.
    • Created functional and technical application documents.

Skills

Programming Languages

Python C++ Java JavaScript SQL

ML / Deep Learning

PyTorch TensorFlow Keras scikit-learn XGBoost

Computer Vision & Imaging

OpenCV NumPy Pandas Matplotlib Pillow

Big Data & Backend

PySpark Django MySQL REST APIs

Tools & Environment

Git GitHub Docker Linux LaTeX Jupyter

Research Areas

Medical Image Analysis Computer Vision Deep Learning NLP Computational Biology

Extracurricular Activities

Beyond research, I have organized programming contests, judged student competitions, anchored academic events, and contributed to student community-building at Daffodil International University.

News

  • Apr 2026
    Our paper “Trustworthy Diabetic Retinopathy Detection: Avoiding False Negatives through Confidence-Based Rejection” was accepted at the IEEE Engineering in Medicine and Biology Conference (EMBC 2026).
  • Mar 2026
    Our paper “Evaluating Transferability of Fundus-Trained Deep Models to Mobile Retinal Imaging for Diabetic Retinopathy Detection” was accepted at the IEEE International Symposium on Biomedical Imaging (ISBI 2026).
  • Nov 2025
    Our article “Early Dengue Prediction in Bangladesh: A Comparative Study with Feature Analysis, Explainable Artificial Intelligence and Model Optimization” was published in the Journal of Tropical Medicine (Q2). [Full Text]
  • Oct 2025
    Our paper “QPolypNet: A Quantum-Inspired Deep Learning Model for Polyp Segmentation” was accepted at the ICCV 2025 Workshop on Computer Vision for Automated Medical Diagnosis (CVAMD) and archived in the ICCV 2025 workshop proceedings. [Full Text]
  • Aug 2025
    Started my PhD in Computer Science at Kennesaw State University and joined the Trustworthy Machine Learning Research Lab as a Graduate Research Assistant on an NIH-funded diabetic retinopathy project.
  • Feb 2025
    Awarded the Gold Medal at the 12th Convocation of Daffodil International University for academic excellence in BSc in Computer Science (CGPA 3.93/4.00).
  • Dec 2024
    Our article “SAMU-Net: A dual-stage polyp segmentation network with a custom attention-based U-Net and segment anything model for enhanced mask prediction” was published in ARRAY (Q1, Elsevier). [Full Text]
  • Our article “CerviXpert: A multi-structural convolutional neural network for predicting cervix type and cervical cell abnormalities” was published in Digital Health (Q2, SAGE). [Full Text]
  • Jul 2024
    Joined the Health Informatics Research Lab (HIRL) as a Research Assistant, contributing to medical imaging research and journal publications.
  • Apr 2024
    Served as Trainer for the ITEE Batch April 2024 at Daffodil International University, helping students prepare for the Information Technology Engineers Examination.
  • Dec 2023
    Our review article “A Review on the Impacts of Social Media on the Mental Health” was published at the International Conference on Intelligent Computing & Optimization (ICO 2023, Springer). [Full Text]
  • Our review article “A Comprehensive Review on Family Budget Management” was published at the International Conference on Intelligent Computing & Optimization (ICO 2023, Springer). [Full Text]
  • Oct 2023
    Passed Level 2 (Fundamental Information Technology Engineer, FE) of the Information Technology Engineers Examination (ITEE).
  • May 2023
    Elected Vice President of the DIU Computer and Programming Club, leading workshops, programming contests, and student outreach activities.
  • Appointed Trainer for the Advanced Machine Learning and Deep Learning Bootcamp organized by the DIU NLP & ML Research Lab; designed curriculum and led hands-on TensorFlow/PyTorch sessions. [Letter]
  • Apr 2023
    Appointed Research Assistant at the Apurba-DIU Research and Development Lab, contributing to 3 government-funded projects on OCR data annotation, font interoperability, and screen reader testing. [Letter]
  • May 2022
    Joined as Lab Prefect at the Algorithm Lab, Daffodil International University, assisting in teaching algorithm lab classes and preparing technical documents.
  • Dec 2013
    Received Government Scholarship in the Junior School Certificate (JSC) Examination.
  • Dec 2011
    Received Government Scholarship for High School Entrance.

Leadership & Service

I contribute to academic communities through university committee service, student leadership, and peer-review activities for journals in artificial intelligence, pattern recognition, computational biology, and soft computing.

Leadership
2
Academic Service Roles

KSU & DIU

Current

Graduate Student Member

Research Computing Advisory Committee, Kennesaw State University

2026 – Present

Leadership

Vice President

DIU Computer & Programming Club, Daffodil International University

May 2023

Services
4
Active Peer-Review Journals

All Elsevier

Peer Reviewer

Pattern Recognition

Elsevier

Peer Reviewer

Computational Biology and Chemistry

Elsevier

Peer Reviewer

Systems and Soft Computing

Elsevier

Contact Me