Shaibal Barua is a Senior Lecturer at Mälardalen University in Computer Science and working with the Artificial Intelligence and Intelligent Systems group. He received his Ph.D. in computer science in 2019 from Mälardalen University. In 2013 he received his MSc in Computer Science and in 2015 he received licentiate degree from Mälardalen University.

Research Interest:

Artificial Intelligence & Machine Learning
Explainable AI
Statistical Learning Theory
Data Analytics
Signal Processing and Multi-sensor Data Fusion

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Latest publications:

Integrating XGBoost, SHAP, and DiCE for Prescriptive Maintenance of Undercarriage Sprockets (Feb 2027)
LIBAN Mohamed AHMAD , Mobyen Uddin Ahmed, Shaibal Barua, Shahina Begum, Daniel Aurel , JONATHAN WRIGHT , Emmanuel Weiten
9th Artificial Intelligence and Cloud Computing Conference (AICCC2026)

A Mobile Machine Vision App with VLM-based Validation for Industrial Inspection Data Acquisition (Dec 2026)
Anwar Ur Rehman , Shahina Begum, Mobyen Uddin Ahmed, Shaibal Barua, Daniel Aurel , Emmanuel Weiten
2026 19th International Conference on Machine Vision. (ICMV2026)

Optimising Wheel Replacement Schedules for Freight Trains based on Machine Learning Models (Nov 2026)
Max Strang , Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum
15th International Conference on Data Science, Technology and Applications (DATA 2026)

Physics-Informed Neural Networks for Real-Time Thermal Monitoring of Electric Vehicle Propulsion Motors (Oct 2026)
Carl-Johan Bohwalli , Mobyen Uddin Ahmed, Md Mohsin Kabir, Shaibal Barua, Jahirul Islam , Shahina Begum
27th Engineering Applications and Advances of Artificial Intelligence (EAAAI26)

Explaining Agent Interactions through their Causal Behavior and Counterfactuals (Oct 2026)
Mir Riyanul Islam, Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum
27th Engineering Applications and Advances of Artificial Intelligence (EAAAI26)

Evaluating AI Agent Prompting and Fine-Tuning Strategies for Structured Data Extraction from Industrial PDFs (Sep 2026)
Md Masum Billah , Mobyen Uddin Ahmed, Shaibal Barua, Nicolas Leberruyer , Shahina Begum
ARRAY (ARRAY)

Project Title	Status
ARTIMATION :TRANSPARENT ARTIFICIAL INTELLIGENCE AND AUTOMATION TO AIR TRAFFIC MANAGEMENT SYSTEMS	finished
AUTOMAD:AUTOnomous Decision Making in Industry 4.0 using MAchine Learning and Data Analytics	finished
BRAINSAFEDRIVE: A Technology to detect Mental States During Drive for improving the Safety of the road	finished
DIGICOGS:DIGital Twins for Industrial COGnitive Systems through Industry 4.0 and Artificial Intelligence	finished
Embedded Sensor Systems for Health Plus	finished
ESS-H - Embedded Sensor Systems for Health Research Profile	finished
FitDrive: Monitoring devices for overall FITness of DRIVErs	active
Food4Health: A Personalized System for Adaptive Mealtime Situations for Elderly	finished
HIVEMIND:Human-centred collaboratIVE MultI-ageNt framework for accelerating software Development and maintenance	active
MONITOR: A Data-driven Intelligent MONITORring System to Improve Quality of Working Life	active
PREST:Predictive Strategy using Machine Learning for Smart Test Case Selection	active
PROMPT - Professional Master’s in Software Engineering (step II, phase B&C)	finished
SafeDriver: A Real Time Driver's State Monitoring and Prediction System	finished
SimuSafe : Simulator of Behavioural Aspects for Safer Transport	finished
TRUSTY: TRUSTWORTHY INTELLIGENT SYSTEM FOR REMOTE DIGITAL TOWER	active
Trust_Gen_Z:Trustworthy Generative AI for Advanced Industrial DigitaliZation	active
VDM - Vehicle Driver Monitoring	finished
Xbest: Generative AI towards Inference to the Best Explanation	active

MSc theses supervised (or examined):

Thesis Title	Status
	available
A systematic review on theoretical aspects of k-nearest neighbour algorithm	available
An intelligent system for driver cognitive load detection using eye tracking data	available
Data-driven cognitive load classification system using machine-learning algorithm	available
Distributed case retrieval for big data using Spark platform and Case-Based Reasoning	selected
Applying artificial intelligence to identify drivers cognitive load based on correlation between EEG signals and driving behaviour signals	in progress
Machine Learning applied on embedded system recordings	in progress
Case representation methodology for a scalable Case-Based Reasoning	finished
Feature selection of EEG-signal data for cognitive load	finished
Stress Management for Pilots	finished

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