Dr. Arulmurugan Ramu

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Dr. Arulmurugan Ramu

Department of Computational Science and Software Engineering
Heriot-Watt International Campus of K. Zhubanov Aktobe Regional University, Aktobe, Kazakhstan

I am an Associate Professor in the Department of Computational Science and Software Engineering at Heriot-Watt International Campus of K. Zhubanov Aktobe Regional University, Aktobe, Kazakhstan, specialising in Artificial Intelligence, Machine Learning, and Deep Learning. My research focuses on developing intelligent systems that solve real-world problems in healthcare, computer vision, and natural language understanding. I lead the AI & Intelligent Systems Lab and collaborate with international research groups across academia and industry.

Email Publications CV (Jul 2026) Google Scholar ORCID Scopus
125+ Publications
1,800+ Citations
15+ Years Experience
6 Alumni Graduated

Research

My lab investigates foundational and applied problems in AI, with a focus on building systems that are accurate, interpretable, and clinically deployable.

Medical Image Analysis

Deep learning models for early detection and classification of diseases from MRI, CT, and X-ray images. Current focus on brain tumour segmentation and diabetic retinopathy grading.

CNN U-Net Transfer Learning

Natural Language Processing

Transformer-based models for text classification, sentiment analysis, and information extraction from biomedical literature and clinical notes.

Transformers BERT Text Mining

Explainable AI

Developing interpretability methods for black-box models to improve transparency and trust in AI-driven clinical decision support systems.

XAI SHAP Grad-CAM

Federated Learning

Privacy-preserving distributed machine learning frameworks enabling collaborative model training across hospitals and institutions without sharing raw patient data.

Federated Learning Privacy Distributed AI

Computer Vision

Object detection, semantic segmentation, and scene understanding for autonomous systems, surveillance, and remote sensing applications.

YOLO GAN Image Segmentation

Healthcare AI Systems

End-to-end intelligent systems for patient risk stratification, treatment recommendation, and clinical workflow optimisation in smart hospital environments.

Healthcare AI Predictive Modelling EHR

Publications

Selected recent publications. See Google Scholar for the full list (125+ papers, 1,800+ citations). ↓ Download BibTeX

Book 2027 Forthcoming

Data Science and AI for Climate Change: Building a Sustainable Future

D. Vetrithangam, Puneet Kumar, Arulmurugan Ramu (Eds.)

Current Advances in Biodiversity, Conservation and Environmental Sciences, Apple Academic Press, February 2027 · Est. 354 pp · ISBN: 978-1-77964-677-4

Chapter 2027

Data Science Modelling in Agricultural Market Supply Chains

S. Shivananda, Lincy Meera Mathews, Arulmurugan Ramu, M. Sathya

Chapter 10 in Strategic Planning and Adaptation of Resilient Agri-Food Systems in a Changing World, Denis Samygin & Vasilii Erokhin (Eds.), IGI Global Scientific Publishing, 2027 · 28 pp · ISBN: 979-8-3373-4987-9

DOI IGI Global
Journal 2026 In Press

A Machine Learning-Based Recommendation System Using Content-Based Filtering Techniques

Meruert Yerekesheva, Arulmurugan Ramu, Arman Kabidolda, Altynzer Baiganova

Eng. Technol. Appl. Sci. Res. (ETASR), December 2026

Book 2020

Advances in Computing, Communication, Automation and Biomedical Technology

Arulmurugan Ramu (Ed.)

Hardcover, January 2020 · ISBN: 978-81-950008-0-7

Conference2012

Adaptive Based Kernel Method for Denoising Image

Arulmurugan R. & Sengottuvelan P.

National Conference on Recent Trends in Information and Communication Technology, April 2012

Conference2013

A Novel Framework for Face Recognition Using ASM and Sparse Coding

Arulmurugan R. & LaxmiPriya M. R.

International Conference on Advanced Computing (ICoAC), 2013

Conference2014

Robust Face Recognition for Pose and Illumination Using Extended ASM and Sparse Coding

Arulmurugan R. & LaxmiPriya M. R.

ICIIECS 2014

Conference2015

An Effective Text Mining on Use of Side Information for Clustering

Arulmurugan R. & Subamanikandan A.

ICIIECS, March 2015

Conference2015

Android Based Application for Call Taxi Booking

Arulmurugan R., Sankar G., & Vinothkumar M.

RTICT, March 2015

Conference2016

P2P File Sharing Using Proximity-Aware Interest Clustering

Arulmurugan R. & Varalakshmi T.

ICETSET '16, March 2016

Conference2017

Lung Cancer Segmentation in CT Images Using Watershed Algorithm and Artificial Neural Network

Arulmurugan R.

National Conference on Open Data Sciences and Computing, March 2017

Conference2017

Herbal Information System

Arulmurugan R.

National Conference on Open Data Sciences and Computing, March 2017

Conference2018

Heart Attack Intimation and Easy Monitoring System Using IoT

Arulmurugan R.

International Joint Conferences on Advances in Engineering and Technology, May 2018

Conference2019

Autonomous and Automated Vehicles – The Future Transportation Systems

Arulmurugan R.

ICSSIT 2019, IEEE

Conference2019

A Detailed Analysis of Big Data Analytics – Challenges and Opportunities

Arulmurugan R.

ICSSIT 2019, IEEE

Conference2019

Artificial Intelligence and Machine Learning for Enterprise Management

Arulmurugan R.

ICSSIT 2019, IEEE

Conference2019

Analysis of Cloud Based Simulation Methods and Optimization Algorithms

Arulmurugan R.

ICSSIT 2019, IEEE

Conference2019

Multispectral Data Processing for Agricultural Applications Using Deep Learning Classification Methods

Arulmurugan R.

EAI BDCC 2019

Conference2019

Intelligent Vehicle System Problems and Future Impacts for Transport Guidelines

Arulmurugan R.

ICSSIT 2019, IEEE

Conference2022

Reorganizing Virtual Machines as Docker Containers for Efficient Data Centres

VasanthaKumari N. & Arulmurugan R.

EAI BDCC, 2022

View all 125+ publications on Google Scholar ↗

Teaching

Courses I teach at the undergraduate and postgraduate level.

UG

Programming Languages (Java, C)

UG

Object-Oriented Analysis and Design (OOAD)

UG

Operating System Principles

UG

Data Structures, Algorithms and Analysis

UG

Artificial Intelligence

UG

Machine Learning

UG

Programming in Python

PG

Deep Learning

PG

Natural Language Processing

Editorial

Guest-edited special issues in international journals.

Lab & Team

The AI & Intelligent Systems Lab. We are always looking for motivated students and collaborators.

Alumni

Former students who have graduated and moved on to great positions.

  • Hirut Mekonen Firissa — M.Sc IT, 2024–2025 · Mattu University, Ethiopia · "Impact of Commonly Used Optimizers and Learning Rate on the Performance of the Transfer Learning Model during the Detection of Pneumonia"
  • Mekdes Solomon — M.Sc IT, 2024–2025 · Mattu University, Ethiopia · "BERT-Based Hybrid Deep Learning Approach for Sentiment Analysis of Afan Oromo Text"
  • Diro Tolosa Goda — M.Sc IT, 2024–2025 · Mattu University, Ethiopia · "Afaan Oromo Textual Entailment Classification Using a Deep Learning Approach"
  • Teshale Mengesha Kochito — M.Sc IT, 2024–2025 · Mattu University, Ethiopia · "Kafi-Noonoo Text Summarization with a Deep Learning Approach"
  • Abebayehu Meseret — M.Sc IT, 2023–2024 · Mattu University, Ethiopia · "Custom Fraud Analysis Using Deep Learning"
  • Mulusew Bekele Agajo — M.Sc IT, 2023–2024 · Mattu University, Ethiopia · "Analysis of Different Batch Sizes in a Deep Learning Model for Detection of Enset Leaf Bacterial Wilt Disease"
🎓 Now Accepting PhD Applications — 2025–26

Join the Lab

I am looking for self-motivated PhD and Masters students with a strong background in mathematics, programming (Python), and a passion for AI research. Research areas: Healthcare AI, Federated Learning, Computer Vision, NLP. If you are interested, please send your CV and a brief statement of research interests to arulmr@gmail.com.

Get in touch

Collaboration Network

Most frequent co-authors across 125+ publications.

Talks & Keynotes

Invited lectures, keynote addresses, and conference presentations.

Keynote

Recent Trends in Technology

International Conference on Recent Trends in Technology (ICRTT 2026)

17 April 2026 · Organized by Faculty of Computer Science and Engineering

News

Contact

For research collaborations, student enquiries, or speaking invitations, please reach out.

Office Room 203 PS, 2nd Floor
Heriot-Watt International Campus of K. Zhubanov Aktobe Regional University
Aktobe, Kazakhstan
Office Hours Mon – Fri, 9:00 AM – 5:00 PM

I aim to respond within 2 business days.

Work With Me

Open opportunities to collaborate, study, or consult.

🎓

PhD Supervision

I accept 1–2 PhD students per year in AI, ML, Deep Learning, and Healthcare AI. Funding opportunities available.

Apply for PhD
🤝

Joint Research

Interested in co-authoring papers, sharing datasets, or running joint experiments? I welcome international academic collaborations.

Propose Collaboration
🏢

Industry Consulting

I consult for organisations applying AI and Machine Learning to real-world challenges in healthcare, smart cities, and IoT.

Get in Touch

Paper of the Month

A highlighted publication with plain-language context.

★ Featured

Gaussian Dual Adjacency Graph Based Spatial Correlated and Temporal Time Dependent Traffic Prediction in Bangalore City

In plain English: This paper develops a new AI model that predicts city traffic patterns more accurately by combining both the physical layout of roads (spatial structure) and how traffic changes over time (temporal dynamics). Tested on real Bangalore traffic data — it outperforms existing methods.

Scientific Reports, Nature Portfolio · 2025 DOI: 10.1038/s41598-025-25075-4
—Citations
2025Year
Q1Journal Rank

PhD Alumni & Supervision

Researchers I have supervised and mentored.

TD

T. D. Adugna

Pattern Recognition and Machine Learning

2024

Researcher · Journal of Machine and Computing

RV

R. Venkatesh

ML for Adaptive Curriculum Design

2026

Published · Springer Nature Singapore

SK

S. K. Ravichandran

Spatial-Temporal Traffic Prediction

2025

Published · Scientific Reports, Nature

+

Open Position

AI / ML / Deep Learning — 2025–26

2025

Apply now →

Research Journey

Key milestones across two decades of research.

2018

First Springer Chapter

Early Detection of Lung Cancer using Neural Networks — published in Lecture Notes in Computational Vision and Biomechanics.

2019

Two Springer Books

Authored Computational Intelligence and Sustainable Systems and Computing and Communication Systems in Urban Development.

2020

IoT Research Book

Edited Business Intelligence for Enterprise Internet of Things — Springer, with global co-editors.

2022

100+ Publications Milestone

Crossed 100 peer-reviewed publications spanning journals, books, and conference proceedings.

2025

Nature Portfolio Publication

Traffic prediction paper published in Scientific Reports, cementing AI research at the international level.

2026

ICRTT 2026 Keynote

Invited keynote speaker at the International Conference on Recent Trends in Technology — recognising global research leadership.

Research Topics

Hover a topic to explore — click to filter publications.

Preprints & Working Papers

Under review / submitted manuscripts and early-stage research notes.

Research Paper
Acquisition-Consistent Attribution Regularisation for Explanation Stability in Explainable AI Medical Image Classification
Arulmurugan Ramu (Corresponding Author) et al.
Explainable AI · Medical Imaging · XAIRequest preprint
Research Paper
Mechanistic Evaluation of Transformer-based Architectures for Enhanced Small Object Detection in Crowded Computer Vision Scenes: Density-Steered Token Attention
Arulmurugan Ramu (Corresponding Author); Altynzer Baiganova; Sowjanya Lakshmi A
Computer Vision · Deep LearningRequest preprint
Research Paper
Energy-Aware Federated Learning under Communication and Privacy Constraints for IoT Sensing
Arulmurugan Ramu et al.
Federated Learning · IoT · PrivacyRequest preprint
Research Paper
Deployment-Oriented Federated Learning for Chest Radiography: A Unified Framework and a Falsification-Oriented Audit of Generalisation, Calibration, Privacy and Drift
Arulmurugan Ramu et al.
Federated Learning · Healthcare AI · Medical ImagingRequest preprint
Research Paper
A Permutation-Controlled Audit of Conditional Calibration in Multi-Label Chest Radiograph Classification
Arulmurugan Ramu et al.
Healthcare AI · Calibration · Medical ImagingRequest preprint

Grants & Funding

Research supported by international funding bodies and university grants.

K. Zhubanov Aktobe Regional University
Determination of Semantic Relationships Between Model Elements & Ontology-Based Research (Contract No. 24)
May–Aug 2026Researcher: Arulmurugan Ramu
Active
University Research Grant
Blockchain Security for Vehicular Ad-Hoc Networks in Urban Environments
2021–2023PI: Dr. Arulmurugan Ramu
Completed

Research Vision

Bridging artificial intelligence and real-world impact — in healthcare, language, and society.

My research sits at the intersection of machine learning, natural language processing, and clinical decision support. I am driven by a single question: how can AI systems be made not only accurate, but trustworthy and deployable in high-stakes environments?

Over the past decade, my work has focused on three converging frontiers. First, medical image analysis — developing deep learning pipelines for early detection of brain tumours, diabetic retinopathy, and skin lesions from MRI, CT, and dermatoscopic images. Second, low-resource NLP — building text classification, named entity recognition, and speech systems for under-resourced languages such as Afaan-Oromo, Tamil, and Arabic, where data scarcity demands creative transfer learning strategies. Third, explainable AI (XAI) — designing interpretability layers using SHAP, Grad-CAM, and attention mechanisms so that clinical professionals can understand, audit, and safely act on model predictions.

Looking ahead to 2025–2030, my lab is expanding into federated learning for privacy-preserving clinical collaboration, LLM fine-tuning for biomedical question answering, and edge-deployable AI for resource-constrained healthcare settings in Central Asia and East Africa. The goal is not publication counts — it is measurable benefit to patients, practitioners, and communities.

Google Scholar Profile Semantic Scholar

Global Research Impact

Publications cited and collaborations active across 40+ countries.

Kazakhstan India UK USA Ethiopia Germany China
Home institution (Kazakhstan)
Active collaborations

Most-Cited Papers

Live citation data from Semantic Scholar — updated automatically.

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