Md. Salauddin
Sarker
System
Architect & AI Researcher
Data Science Researcher | Explainable AI (XAI) • Time-Series Forecasting • Industrial Analytics
Institutional Affiliation
Dept. of Educational Technology & Engineering (EdTE)
University of Frontier Technology (UFTB), Bangladesh
Researcher ID
ORCID: 0009-0005-7907-7522I develop reliable and interpretable machine learning for real-world decision systems. My primary research interests lie in Explainable AI (XAI) and Time-Series Forecasting, creating trustworthy models for healthcare and industrial analytics. My goal is to advance these fields through a rigorous MSc candidacy, transitioning robust theoretical research into impactful, deployable solutions.
GPA: 3.84 out of 4.00
Published
Research
Industrial Data
Engineering
Two times
Dean's Awardee
Candidacy
Fall 2026 Ready
Scholarship Grade
"The complexity of industrial data requires the precision of neural interpretation."
Scientific
Philosophy
Active Research
Agenda
Scholarship
Aspiration.
Specializing in Trustworthy Data Science—architecting machine learning systems that maintain interpretability and robustness under real-world industrial constraints.
Explainable AI (XAI)
Developing faithful, actionable explanations for high-stakes decision makers using SHAP, LIME, and Grad-CAM.
Dynamic Forecasting
Evaluating neural resilience across non-stationary longitudinal data and multi-region normalizations.
Strategic AI Roadmap
Future Trajectories (2026-2030)
Knowledge-Grounded
LLMs
Integrating retrieval-augmented generation (RAG) with explainable reasoning to reduce hallucination in enterprise environments.
Target: Trustworthy AI
Recursive Agentic
Reasoning
Developing autonomous agents capable of self-correcting reasoning loops for complex multi-step industrial automation.
Target: Industrial
Scale
Quantization-Aware
Edge AI
Optimizing deep models for low-power edge deployment in agri-tech and healthcare without sacrificing interpretability.
Target: Global Impact
Academic Pedigree
Educational Foundation
B.Sc. in Educational Technology & Engineering (EdTE)
University of Frontier Technology (UFTB), Bangladesh
CGPA: 3.84 out of 4.00
2019 — 2024
Specialized Coursework
Artificial
Intelligence
Big
Data Analytics
Educational
Robotics
Advanced
Statistics
Industrial
Automation
Higher Secondary (Science)
Dhaka College
GPA: 5.00 out of 5.00
Secondary School Certificate
SHKSC
GPA: 5.00 out of 5.00
Research-Relevant Experience
Data Engineering & Operation Analytics
Software Developer / Data Systems
Q Cosmetics Ltd
May 2025 – Present
"Bridging the gap between industrial IoT data and enterprise intelligence. My work
focuses on scalable ETL pipelines that serve as the foundation for trustworthy
predictive analytics."
Operational Impact
- → Rolled out multi-module ERP workflows, reducing order cycle time by 35%.
- → Built Python–PostgreSQL ETL pipelines, improving audit consistency and data quality.
Analytics & BI
- → Built KPI dashboards (Metabase/Tableau), reducing monthly reporting from 3 hours to 15 minutes.
- → Structured master data and reconciliation logic for reliable downstream analytics.
Metrics are based on internal operational tracking and monthly reporting audits.
Technical Matrix.
Multi-Disciplinary Stack & Scientific Toolkit
Computational Stack
- Python
- SQL
- Java
- PHP
- Dart
- Linux / Shell
ML / AI / XAI
- PyTorch / TF
- SHAP / LIME
- Grad-CAM
- ARIMA / OLS
- Scikit-Learn
- Computer Vision
Data & BI
- PostgreSQL
- Odoo (ERP)
- ETL Pipelines
- Tableau
- Metabase
- Data Warehousing
Proficiencies
Bengali
Native
English (IELTS: 6.5)
Professional
Japanese
Basic (N5)
Awards & Honors
Dean’s Award (2022, 2024)
University of Frontier Technology (UFTB)
Academic excellence for two non-consecutive cycles for top-tier GPA.
National STEAM Olympiad 2023
9th Place (National) • Campus Ambassador
Selected as campus leader to coordinate innovation drive; ranked top 10 nationally for technical pitch.
Academic Leadership
UFTB STEAM Club
Vice President
Facilitating technical mentorship for 200+ members and orchestrating high-fidelity engineering hackathons.
UFTB Robotics Club
Executive Member
Orchestrating large-scale robotics competitions and facilitating cross-discipline engineering hackathons.
UFTB Language Club
Japanese Language Secretary
Facilitating multi-lingual research communication and fostering global academic exchange.
Published
Scientific Output.
Registry of Published Peer-Reviewed Journals & Conferences
Artificial
Intelligence Review
Springer
Nature
Vol 59, 105 (2026)
Leveraging explainable AI for sustainable agriculture: a comprehensive review of recent advances
Authors:
Aditya Rajbongshi, Fatema Tuz Johora, Arafat Hossain, Md. Salauddin Sarker, Md Habibur Rahman, Md Wahidur Rahman, Fahad T. Alotaibi, Mohammad Ali Moni
Key Contribution
Mapped 150+ papers to create a novel 4-tier taxonomy for evaluating local explanations (LIME, SHAP, Grad-CAM) in precision agriculture systems.
Scientific Methodology
Systematic mapping of 150+ papers; specialized 4-tier taxonomy for post-hoc local explanations in agri-systems.
XAI Frameworks
Evaluation of LIME, SHAP, and Grad-CAM for transparent decision-making in precision agriculture.
Artificial Intelligence (AI) has emerged as a transformative force across various industries, including agriculture, where it is being adopted to enhance productivity, efficiency, and sustainability. However, a significant challenge arises from the lack of transparency in AI models, which can undermine their dependability, particularly in critical fields like agriculture and medicine. This review explores recent advances in leveraging Explainable AI (XAI) to bridge the gap between model complexity and human trust.
DOI Reference
10.1007/s10462-025-11459-5
IEEE
Xplore
Full
Paper
COMPAS 2025
Bridging Climates: Weather Forecasting Using OLS and ARIMA Models with a Multi-Country Dataset
Authors:
Arafat Hossain, Md. Salauddin Sarker, Aditya Rajbongshi, Most. Rakiba Khanom Jisa, Maria Afrin Bindu, Kayes Mohammad Abdullah
Key Contribution
Conducted a 61-year multi-country clinical analysis of climate data, proving OLS outperforms ARIMA (RMSE 0.30) for baseline long-term predictions in Bangladesh.
Architectural Approach
OLS + ARIMA hybrid forecasting on a 61-year multi-country climate dataset (Bangladesh, Saudi Arabia, Japan, Russia).
Research Impact
OLS outperformed ARIMA for Bangladesh (RMSE 0.30, MAE 0.25); accurate long-term weather prediction via time-series analytics.
DOI Reference
10.1109/COMPAS67506.2025.11381792
IDAA
2025
Specialized
Track
EdgeVision: Quantization-Aware Inference for Industrial Edge
Authors:
Md.
Salauddin Sarker, et al.
Key Contribution
Developed an 8-bit INT quantization approach for ARM edge nodes achieving sub-10ms inference latency targeting industrial vision.
Optimization Focus
8-bit INT quantization on ARM platforms; Sub-10ms inference for low-power nodes.
Forum Status
Featured as High-Potential Research at the IDAA 2025 Scientific Forum.
Educational
Data Mining
Research
Paper
Accuracy 94.74%
Bridging Educational Gaps: Predicting Retakes Among Bangladeshi Undergraduates with Machine Learning and Explainable AI
Authors:
Nusrat Zahan Nila, Md. Ali Mahmud Pritom, Fatema Tuz Johora, Aditya Rajbongshi, Md. Salauddin Sarker, Md. Ashrafuzzaman
Key Contribution
Built an early course-retake prediction framework for Bangladeshi undergraduates using a soft voting classifier with SHAP and LIME, reaching 94.74% accuracy on a 474-student dataset.
Predictive Framework
474 real student records, extensive preprocessing, and baseline comparison across LR, GNB, RF, SVC, Perceptron, KNN, and a proposed soft voting ensemble.
XAI Insights
SHAP and LIME exposed the factors driving retake risk, including lack of preparation, family issues, poor time management, and related academic pressures.
Verified Credentials
Technical Validation.
Academic Certifications & Professional Recognition
8
Certificates
3
Conferences
2×
Dean's List
Verified
Status
Archive In Motion
Certificates issued under Gazipur Digital University reflect the institution's former name. The university is now recognized as UFTB.
Research Case Studies
Evidence of Technical Readiness & Scientific Method
Case Study #01
— Deep Learning + XAI
Rice Leaf Disease Detection
Building an accurate and interpretable classifier for sustainable agri-diagnostics.
The
Problem
Need for reliable, transparent identification of leaf pathogens in field conditions.
The
Data
Multi-class leaf image dataset; diverse environmental backgrounds.
Approach: Transfer learning (VGG16/ResNet50/EfficientNetB0) + attention mechanisms.
Explainability: Grad-CAM heatmaps for decision transparency and feature verification.
Results: 99.42% accuracy; sustained 42 FPS on mobile edge platforms.
RESEARCH IMPACT (MSc READY)
Demonstrated that spatial attention maps can pinpoint pathogenic regions in leaf images better than standard CNNs, crucial for trustworthy field diagnostic deployment.
Spatial
Attention Heatmap Visualization
Case Study #02 —
Time-Series
Bridging Climates: Multi-Country Weather Forecasting
OLS vs ARIMA evaluation across 61 years of multi-country climatic data (Bangladesh, Saudi Arabia, Japan, Russia).
The
Problem
Forecasting weather variables accurately across geographically diverse regions.
The
Data
61 years of historical weather data across multiple regions.
Approach: OLS + ARIMA hybridization; comprehensive error diagnostics and baseline comparisons across 4 countries.
Metrics: OLS outperformed ARIMA for Bangladesh (RMSE 0.30, MAE 0.25); demonstrated reliable long-term prediction via time-series analytics.
KEY INSIGHT (LEARNING)
Identified that non-stationarity requires careful time-indexed evaluation and domain-aware baselines rather than just high-complexity architectures.
Multi-Country
Climate Analysis
Case Study #04
— Industrial ML
Industrial Customer Churn Prediction
Bridging operational ERP data with predictive retention strategy.
The
Problem
Predicting organizational churn and identifying key risk drivers in commercial flows.
The
Output
85% prediction accuracy with feature importance insights for retention.
Approach: Classification models (XGBoost/RandomForest) + SHAP feature importance analysis.
Outcome: Actionable retention strategy insights for operational management.
Academic Endorsements
Farhana Islam
Assistant Professor & Chairman
Dept. of Educational Technology & Engineering
farhana0001@uftb.ac.bd
University of Frontier Technology (UFTB), Bangladesh
Aditya Rajbongshi
Assistant Professor
Dept. of Educational Technology & Engineering
aditya0001@uftb.ac.bd
University of Frontier Technology (UFTB), Bangladesh
Curriculum Vitae
Academic & Professional Summary
Research Direction: Seeking fully funded MSc (Thesis) opportunities in XAI + Time-Series + Reliable ML.
Data Systems: Proven industry experience in ERP Workflows + ETL Pipelines + BI Dashboards.
Scientific Output: Multiple Published Papers across IEEE and Springer venues.
Dean's Award (2x) • GPA 3.84
Odoo 17 & Industrial ERP Specialist
Active Researcher in Explainable AI
MSc
Candidacy 2026.
I am seeking a fully funded MSc with thesis (Fall 2026) to research Explainable AI, Time-Series Forecasting, and Trustworthy ML.
Get in Touch.
Collaboration & Inquiry
I am always open to discussing new opportunities in Explainable AI, Industrial Automation, and Odoo ERP. Whether you have a question or just want to say hi, I'll try my best to get back to you!
Email Address
md.salauddin.sarker.icte@gmail.comAcademic Referees
Available upon request for MSc applications.
Location
Dhaka, Bangladesh
WhatsApp / Phone
+880 1521-260707