Research Portfolio · 2025

Sarder Junaid
Ahmed

PhD Applicant in Computational Science

Machine Learning Researcher · Statistical Rigor · Methodological Innovation

Research Focus Advancing methodological rigor at the intersection of machine learning and governance analytics. Developing statistically valid frameworks for computational science, fairness-aware ML, and causal inference in observational studies.

94%

Classification Accuracy

127-country validation

95.4%

Consistency Score

100 configurations

94.1%

Crime Classification

p < 0.001

Under-Review Papers

First-author

Publications & Awards

🏆

Multi-Dimensional Statistical Similarity for Governance Classification: Beyond Arbitrary Thresholds

Best Research Paper · APMEE 2025

Oral presentation at 6th Annual Paper Meet, December 2025. Recognized for methodological rigor and novel statistical framework in governance classification.

📄

Under Review Manuscripts — First Author (3 Papers)

Currently Under Peer Review

· Democracy's Financial Paradox · ML for Crime Classification (Fairness-Aware) · Economic Development Classification

Core Research Areas

∑

Computational Science

Probability theory, Measure-theoretic foundations, Bayesian inference, Mathematical methods in data science

⚙

Machine Learning & AI

Ensemble methods, Fairness-aware classification, Feature engineering, Class imbalance handling, Uncertainty quantification

◈

Governance Analytics

Institutional quality assessment, Multi-dimensional similarity testing, Comparative politics, Development economics

≡

Statistical Rigor

Causal inference, Hypothesis testing, FDR correction, Bootstrap validation, Assumption validation

Major Research Initiatives

Political Science · Statistics

Political Regime Classification

127 nations · 94% accuracy

Statistical framework classifying governance across 127 nations using hypothesis testing with FDR correction and bootstrap validation. 95.4% consistency across 100 randomized configurations.

Machine Learning · Ethics

Crime Classification System

94.1% accuracy · Fairness analysis

Ensemble system achieving 94.1% accuracy on 6-class crime prediction using XGBoost. Includes fairness analysis revealing demographic parity gaps requiring human oversight.

View on GitHub

Economics · Deep Learning

Economic Development ML

98.3% accuracy · 150+ countries

ML system classifying countries as developed/developing using World Bank indicators. Addresses high-dimensionality through principled feature selection with robust generalization.

View on GitHub

Data Analysis · Visualization

Annual Enterprise Survey EDA

55,620 records · 117 industries

Rigorous exploratory data analysis on New Zealand survey data. One-Way ANOVA testing with p < 0.001 across categorical variables. Professional visualizations & data pipeline.

View on GitHub

Technical Stack

Category	Expertise
Statistical Methods	Probability theory, Bayesian inference, Causal inference, Hypothesis testing (Mann-Whitney U, K-S, Shapiro-Wilk), FDR correction, Bootstrap validation
Machine Learning	TensorFlow, Scikit-learn, XGBoost, Random Forest, Ensemble methods, Feature engineering, Cross-validation, SHAP analysis
Programming	Python, C/C++, SQL, Git, Docker, Linux, LaTeX
Data Visualization	Matplotlib, Seaborn, Plotly, Jupyter Notebooks
Deep Learning	TensorFlow, PyTorch, LSTM, BiLSTM, Neural network optimization

Education & Credentials

🎓

Bachelor of Science

Computer Science & Engineering

RUET · February 2025
CGPA: 3.08/4.00 · Thesis: A+ · Seminar: A+

📋

English Proficiency

IELTS Academic

Band 7.0 · January 2026
L: 7.5 · R: 6.5 · W: 7.0 · S: 6.5

Recognition & Awards

🏆

Best Research Paper

APMEE 2025

Recognized for methodological rigor and novel statistical framework in governance classification.

🎖

Esteemed Alumni Award

YLLR, RUET (2024)

Recognition for exceptional research dedication and achievement during tenure.

✦

Research Mentorship

Excellence Certificate (2024)

Certificate of Appreciation for mentoring 5+ junior researchers in Bayesian & causal inference.

⭐

Academic Excellence

Perfect GPA (5.00/5.00)

HSC & SSC national examinations with perfect academic performance.

Research Leadership

Senior Researcher & Executive Member

Young Learners' Research Lab · 2022–2024

Conducted machine learning and statistical analysis
Mentored 5+ researchers on Bayesian & causal inference
Led hypothesis testing with FDR correction
Established reproducible research standards
Awards: Esteemed Alumni Award (2024), Mentorship Excellence (2024)

Current Researcher

Royal Scientific Publications · 2026–Present

Mathematical research on applied problems
Measure-theoretic & probabilistic frameworks
Peer-reviewed publication synthesis
Novel solutions to open problems

Statistical Rigor

Data-Driven

ML Innovation

Fairness-Aware

Award-Winning

Published Researcher

Methodological Focus

Complete Materials

Google Drive Portfolio

CV Published Paper Under-Review Manuscripts (3) Research Poster Certificates Transcripts IELTS Report

Access Drive