Wesonga Mangeti

I am a multidisciplinary researcher and technical analyst with extensive experience in data analysis, quantitative research, optimization modelling, and professional academic writing across a range of technical and analytical domains. My work focuses on transforming complex datasets, theoretical frameworks, and technical problems into clear, evidence-based insights and structured analytical outputs. Over time, I have developed strong expertise in designing and executing research projects that combine rigorous statistical analysis with practical decision-support methodologies.

My experience includes conducting advanced quantitative analysis using statistical and analytical tools such as Python, SPSS, Stata, and Excel. I have worked extensively with econometric models, including multiple linear regression, demand estimation, price elasticity analysis, and time-series analysis, enabling the evaluation of relationships between economic and financial variables. In addition, I have experience working with large datasets and applying descriptive statistics, hypothesis testing, and model interpretation to produce research findings that support strategic decision-making.

I also possess strong expertise in optimization modelling and operations research. I have developed and implemented multi-objective optimization models using IBM ILOG CPLEX Optimization Studio, applying methods such as the Weighted Sum Method and Epsilon-Constraint Method to analyze trade-offs between competing objectives, including cost efficiency and environmental impact. These models are applied in logistics planning, supply chain decision-making, and sustainability-focused optimization problems.

In the field of artificial intelligence and data science, I have worked on projects involving machine learning model development, anomaly detection, and intelligent decision systems. My technical experience includes developing analytical frameworks for network security monitoring and intrusion detection, as well as designing data-driven models that integrate statistical analysis with machine learning techniques for predictive and diagnostic purposes.

Additionally, I have technical experience in electronic circuit analysis and digital system simulation, including CMOS inverter and logic gate design using NI Multisim and SPICE modelling techniques. This work involves transient analysis, DC analysis, power dissipation evaluation, and transistor sizing for digital circuit performance optimization.

Alongside my analytical expertise, I have developed strong capabilities in professional academic writing and research development. I regularly produce structured research outputs including dissertations, research proposals, methodological frameworks, technical reports, literature reviews, and analytical presentations. My writing integrates theoretical knowledge with empirical evidence, ensuring clarity, coherence, and methodological rigor.

My professional profile combines analytical problem-solving, quantitative modelling, and structured research communication, allowing me to work effectively across interdisciplinary fields such as business analytics, economics, artificial intelligence, sustainability research, and engineering systems analysis.