Md Mohaiminul Islam Emon - Research & Data Analyst

Md Mohaiminul Islam Emon

Research & Data Analyst | Machine Learning Specialist | Real Estate Analytics Expert

Oslo, Norway

CBRE Norway • Simula Research Laboratory

Østfold University College • Chongqing University of Science and Technology

Transforming complex data into actionable insights. Specializing in real estate analytics, machine learning, and sports performance analysis at CBRE Norway and Simula Research Laboratory.

7+ Publications
10+ ML Projects
2+ Years Experience
Get In Touch View Projects

About Me

I am a Research and Data Analyst with a passion for uncovering insights that drive real-world impact. Currently working at CBRE Norway, I analyze Nordic real estate data and build data-driven solutions for sustainability and market intelligence.

My academic background includes a Master's in Applied Computer Science specializing in Machine Learning from Østfold University College, where I developed predictive models for injury prevention in Norwegian elite soccer players at Simula Research Laboratory.

With 7+ published research papers in IEEE and Springer conferences, I bridge the gap between theoretical research and practical applications. My expertise spans from real estate analytics and ESG reporting to sports performance analysis and healthcare AI.

Awards & Recognition

  • CQUST President Scholarship (Outstanding)
  • 4-Year Academic Excellence Scholarship
  • Micro-Lecture Competition 2nd Prize

Languages

  • Bengali (Native)
  • English (Fluent - C1)
  • Chinese (Intermediate - B1)
  • Hindi (Basic - A2)

Leadership

  • Founder & President, Research Hub Inc.
  • IEEE Brand Ambassador
  • Reviewer, Elsevier & Springer Journals

Work Experience

Research and Data Analyst

CBRE Norway Feb 2024 - Present Oslo, Norway

Leading data intelligence initiatives for Nordic real estate operations, focusing on ESG sustainability metrics and market analytics.

  • Collect and analyze Nordic real estate data supporting national operations across multiple business units
  • Maintain and update ESG dashboards tracking sustainability metrics for 500+ real estate assets
  • Build and manage SQL databases with Snowflake integration, improving data access efficiency by 40%
  • Develop Power BI dashboards for capital markets, valuation, leasing, and property management teams
  • Automate data preprocessing workflows using Alteryx and Python, reducing manual processing time by 60%
Python SQL Power BI Snowflake Alteryx ESG Analytics

Research Assistant

Simula Research Laboratory Oct 2022 - Aug 2024 Oslo, Norway

Conducted cutting-edge research in explainable AI and sports analytics, developing machine learning models for injury prediction and performance optimization.

  • Developed explainable AI (XAI) models for autonomous ships, enhancing decision-making transparency by 35%
  • Analyzed GPS data and wellness metrics from Norwegian women's soccer players to optimize training loads
  • Built ML models predicting injury risks with 82% accuracy, helping reduce training-related injuries by 25%
  • Integrated objective (GPS) and subjective (wellness) metrics to create comprehensive performance dashboards
  • Published master's thesis on injury prediction, contributing to sports science research
Machine Learning Python TensorFlow XAI Sports Analytics Time Series

Student Assistant

Høgskolen i Østfold Sep 2022 - Dec 2022 Halden, Norway

Supported teaching activities and student learning in computer science courses.

  • Assisted with lesson preparation, material collection, and equipment setup for 50+ students
  • Provided individual tutoring for students with learning challenges, improving pass rates by 15%
  • Tracked student attendance and managed class schedules efficiently

Trainee Data Analyst

Staff Asia Apr 2021 - Jun 2021 Sylhet, Bangladesh

Conducted market research and competitive analysis for the R&D team.

  • Analyzed course performance and competitive positioning for market expansion strategies
  • Gathered and reported global market data, trends, and competitor intelligence
  • Presented research findings to internal stakeholders, informing strategic decisions
Data Science Projects

Featured Projects

End-to-end data science and machine learning projects demonstrating problem-solving, technical expertise, and business impact.

Predicting Injuries in Norwegian Women's Soccer

Master's thesis project developing ML models to predict injuries in elite soccer players by analyzing GPS tracking data and wellness metrics.

Problem

Norwegian women's soccer teams faced high injury rates, impacting performance and athlete wellbeing. Need to identify risk factors and predict injuries before they occur.

Solution

Developed ML pipeline analyzing GPS data (distance, speed, acceleration) and subjective wellness reports. Applied Random Forest, XGBoost, and LSTM models with feature engineering.

Impact

  • 82% accuracy in predicting injury risk 7 days ahead
  • Identified key risk factors: training load spikes and poor sleep quality
  • Helped teams optimize training schedules, reducing injuries by 25%
Python Scikit-learn XGBoost LSTM Feature Engineering
Code

Breast Cancer Classification Using ML

Bachelor's thesis comparing seven machine learning algorithms for breast cancer diagnosis, achieving 97% accuracy in malignant vs benign classification.

Problem

Early breast cancer detection is critical for treatment success. Need automated, accurate classification system to support medical diagnosis.

Solution

Compared 7 ML algorithms (Logistic Regression, Decision Tree, Random Forest, SVM, KNN, Naive Bayes, AdaBoost) on Wisconsin Breast Cancer Dataset. Optimized hyperparameters and evaluated using cross-validation.

Impact

  • 97.2% accuracy with Random Forest classifier
  • 0.98 AUC-ROC score, indicating excellent diagnostic capability
  • Identified top predictive features for clinical interpretation
Python Scikit-learn Random Forest SVM Data Analysis

Pneumonia Detection from Chest X-Rays Using CNN

Deep learning model using Convolutional Neural Networks to automatically detect pneumonia from chest X-ray images with radiologist-level accuracy.

Problem

Manual X-ray analysis is time-consuming and requires expert radiologists. Need automated screening tool for faster pneumonia diagnosis in resource-limited settings.

Solution

Built CNN architecture with transfer learning (VGG16) on 5,863 chest X-ray images. Applied data augmentation and regularization techniques to prevent overfitting.

Impact

  • 93% accuracy in pneumonia detection
  • 95% sensitivity (recall), minimizing false negatives
  • Published in IEEE ICAPAI 2023 conference
TensorFlow Keras CNN Transfer Learning Medical AI

Indoor Air Quality Forecasting Using Time Series

Predictive models for indoor air quality using time series analysis on the GAMS dataset, helping optimize building ventilation systems.

Problem

Poor indoor air quality impacts health and productivity. Need forecasting system to predict air quality degradation and trigger ventilation proactively.

Solution

Evaluated 8 ML algorithms (LightGBM, XGBoost, Random Forest, KNN, SVR, Decision Tree, Linear Regression, LSTM) for time series forecasting. Performed feature engineering on temporal patterns.

Impact

  • 88% accuracy in predicting PM2.5 levels 1 hour ahead
  • LightGBM achieved best performance with lowest RMSE
  • System can reduce energy costs by 15% through smart ventilation
Python LightGBM XGBoost LSTM Time Series

COVID-19 Outbreak Prediction & Visualization

Machine learning model analyzing COVID-19 outbreak patterns across regions, with interactive visualizations for trend analysis and case prediction.

Problem

During pandemic, understanding outbreak patterns and predicting case numbers was crucial for resource allocation and policy decisions.

Solution

Built time series models using LSTM and Prophet on global COVID-19 data. Created interactive dashboards with geographical heatmaps and trend predictions.

Impact

  • Predicted case trends 14 days ahead with 85% accuracy
  • Visualized outbreak hotspots for multiple countries
  • Dashboard used by university for campus safety planning
Python Prophet LSTM Plotly Data Visualization

GPS-Controlled IoT Environment Monitoring Robot

Low-cost IoT robotic system for environmental monitoring using wireless sensors, GPS navigation, and real-time Android app interface.

Problem

Environmental monitoring in large or hazardous areas requires expensive equipment and manual data collection, which is time-consuming and risky.

Solution

Designed autonomous robot with ARM microcontroller, GPS module, and wireless sensors (temperature, humidity, air quality). Programmed with Python on embedded Linux and created Android app for remote control.

Impact

  • Built prototype for under $200, 80% cheaper than commercial alternatives
  • Real-time data streaming to mobile app with GPS mapping
  • Autonomous navigation to pre-set locations with ±2m accuracy
IoT Python C++ ARM Android GPS

Additional Projects

Credit Card Fraud Detection
Lung Cancer Prediction
Hospital Database Management System
Stock Market Forecasting
Heart Disease Diagnosis with ML
Face Recognition System
Uber Data Analysis
Student Information Management (Java)

Kaggle Achievements

Active data science practitioner on Kaggle, contributing notebooks, datasets, and competing in machine learning competitions.

Kaggle Profile

@mohaiminul101

Visit My Profile
Active Competitor
Multiple Notebooks
Datasets Contributed
ML & AI Expertise

Featured Notebooks & Projects

Healthcare & Medical Data Analysis

Machine learning models for disease prediction and medical diagnosis including breast cancer classification, pneumonia detection, and heart disease identification.

Healthcare AI Classification Deep Learning

Time Series Forecasting

Advanced forecasting models for COVID-19 outbreak prediction, stock market analysis, and indoor air quality prediction using LSTM, Prophet, and ensemble methods.

Time Series Forecasting LSTM

Computer Vision Projects

CNN-based models for image classification including pneumonia detection from X-rays, face recognition systems, and medical image analysis.

Computer Vision CNN Image Processing

Fraud Detection & Anomaly Analysis

Detecting fraudulent transactions in credit card data using anomaly detection algorithms and imbalanced dataset handling techniques.

Fraud Detection Anomaly Detection Imbalanced Data

Technical Skills Demonstrated on Kaggle

Python (Pandas, NumPy, Scikit-learn)
Machine Learning Algorithms
Deep Learning (TensorFlow, Keras)
Data Visualization (Matplotlib, Seaborn)
Data Cleaning & Preprocessing
Feature Engineering
Model Evaluation & Validation
Version Control (Git)

Areas of Expertise

🏥

Healthcare Analytics

Disease prediction, medical imaging, patient outcome analysis

📈

Financial Analytics

Stock market forecasting, fraud detection, risk assessment

⚽

Sports Analytics

Performance tracking, injury prediction, player metrics

🏢

Real Estate Analytics

Market analysis, ESG metrics, property valuation

Research Publications & Google Scholar

7+ peer-reviewed publications in IEEE and Springer conferences, focusing on healthcare AI, data analytics, and human-computer interaction.

Google Scholar Profile

MD Mohaiminul Islam (Emon)

Publications 7+
Research Focus AI & Healthcare
Venues IEEE & Springer
View Google Scholar Profile
01

"HIØF Easy Navigator: An Augmented Reality App Which Guides a User to Reach Their Destination"

Safayet Anowar Shurid, Mahta Moezzi, Mohaiminul Islam, Pritam Das, Juan C. Torrado

25th International Conference on Human-Computer Interaction (HCII 2023), Copenhagen, Denmark

Publisher: Springer | December 2023

DOI: 10.1007/978-3-031-49215-0_29
02

"Detection of Pneumonia from Chest X-Ray Images Using Convolutional Neural Network (CNN)"

Mohaiminul Islam, Fathima Jubina Pathari

3rd International Conference on Applied Artificial Intelligence (ICAPAI), Halden, Norway

Publisher: IEEE | August 2023

DOI: 10.1109/ICAPAI58366.2023.10194027
03

"Comparative Study to Identify the Heart Disease Using Machine Learning Algorithms"

Rezaul Karim, Wang Chengliang, Mohaiminul Islam

IEEE 2nd International Conference on Big Data, AI and IoT Engineering (ICBAIE), Chengdu, China

Publisher: IEEE | April 2021

DOI: 10.1109/ICBAIE52039.2021.9390032
04

"A Research on Big Data Analytics in Healthcare Industry"

Mohaiminul Islam, Rezaul Karim, MST Asha Khatun, Shamim Reza

International Conference on Information Science and Communications Technology (ICISCT), Tashkent, Uzbekistan

Publisher: IEEE | November 2020

DOI: 10.1109/ICISCT50599.2020.9351494
05

"The Methods, Benefits and Problems of The Interpretation of Data"

Mohaiminul Islam, Anower Hossain, Rakibul Hasan, Abu Rayhan Soton

International Conference on Information Science and Communications Technology (ICISCT), Tashkent, Uzbekistan

Publisher: IEEE | November 2020

DOI: 10.1109/ICISCT50599.2020.9351400
06

"An Overview of Data Visualization"

Mohaiminul Islam, Shangzhu Jin

International Conference on Information Science and Communications Technology (ICISCT), Tashkent, Uzbekistan

Publisher: IEEE | November 2019

DOI: 10.1109/ICISCT47635.2019.9012031
07

"Big Data Analytics in Healthcare"

Guorong Chen, Mohaiminul Islam

2nd International Conference on Safety Produce and Information (IICSPI), Chongqing, China

Publisher: IEEE | November 2019

DOI: 10.1109/IICSPI48186.2019.9095872
View on Google Scholar View on ResearchGate

Technical Skills & Tools

Comprehensive toolkit spanning data analysis, machine learning, visualization, and database management.

Programming Languages

Python Expert
SQL Expert
R Advanced
C/C++ Intermediate

Machine Learning & AI

Scikit-learn Expert
TensorFlow Advanced
PyTorch Advanced
XGBoost/LightGBM Advanced

Data Analysis & Visualization

Power BI Expert
Pandas/NumPy Expert
Matplotlib/Seaborn Advanced
Excel (Advanced) Expert

Databases & Cloud Platforms

Snowflake Advanced
PostgreSQL/MySQL Advanced
Alteryx Advanced

Domain Expertise

Real Estate Analytics ESG Reporting Sports Analytics Healthcare AI Time Series Forecasting Computer Vision Explainable AI (XAI) IoT Systems Statistical Analysis A/B Testing

Tools & Platforms

Git/GitHub
Linux
Windows
Jupyter
VS Code
Tableau

Education

Master of Applied Computer Science

Østfold University College (HIØF)

Halden, Norway

Aug 2022 - Sep 2024

Specialization: Machine Learning & Interaction Design

Grade: B (Very Good)

Master's Thesis: "Predicting Injuries in Norwegian Women's Soccer Players: A Machine Learning Approach"

Key Courses:

  • Advanced Machine Learning
  • Deep Learning & Neural Networks
  • Data Mining & Analytics
  • Human-Computer Interaction
  • Applied Artificial Intelligence

Bachelor of Computer Science and Technology

Chongqing University of Science and Technology

Chongqing, China

Sep 2017 - Jun 2021

Grade: 85.58% (2nd out of 32 students)

Bachelor's Thesis: "A Research on Breast Cancer Prediction Using Different Kinds of Machine Learning Model"

Achievements:

  • 4-Year CQUST Scholarship for Excellent Performance
  • CQUST President Scholarship (Outstanding)
  • 2nd Prize in "Nade Cup" English Document Writing (2017, 2019)
  • 1st Prize in "Nade Cup" English Document Writing (2018)
  • 2nd Prize in Micro-Lecture Competition (City Level, 2018)
  • Silk Road Software Technology Innovation Certificate (2018)

Get In Touch

I'm always interested in hearing about new opportunities, collaborations, or research projects. Feel free to reach out!

Email

mohaiminul100@hotmail.com

Phone

+47 46 24 69 32

Location

Oslo, Norway

Connect With Me

GitHub @Mohaiminul036 Kaggle @mohaiminul101 Google Scholar Publications & Citations ResearchGate Research Profile