ADEDAPO EMMANUEL ADENIRAN

Award-Winning Data Scientist | Certified AI Engineer | AI Software Developer
Lagos, NG.

About

Top (Kaggle) Ranked Data Scientist, Microsoft MVP Award-winning AI Developer and certified Azure AI Engineer with deep expertise in Microsoft tools, machine learning, and C#.NET MAUI development. Proven ability to design and deploy advanced AI solutions, drive data-driven decision-making, and lead complex projects from concept to deployment. Eager to leverage a strong background in predictive modeling, data visualization, and scalable software development to exceed organizational goals in a competitive environment.

Work

Spiritual Data
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Data Scientist

New York, New York, USA

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Part Time

Summary

Contributed to AI model development and quality assurance at Spiritual Data through data labeling, source code testing, and collaborative improvements.

Highlights

Selected and accurately labeled data points within the database, crucial for grounding and enhancing the retrieval augmented generation (RAG) model.

Performed rigorous source code debugging and field testing of compiled code, ensuring software quality and performance.

Contributed actively to team collaboration platforms (Notion, Discord), providing actionable suggestions for product and process improvements.

Data Scientists Network
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Data Scientist

Lekki-Ajah, Lagos, Nigeria

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Seasonal

Summary

Applied expertise in machine learning and software development to enhance community engagement, mentor junior data scientists, and deliver external data science solutions.

Highlights

Leveraged machine learning, Python scripting, C#.NET MAUI software development, and data visualization/wrangling expertise to successfully deliver diverse data science projects.

Delivered data-driven solutions for external clients, applying advanced data analysis, visualization, and modeling to solve complex business problems.

Mentored junior data scientists, guiding them through project development, data analysis, and ML techniques, fostering their growth and ensuring code quality through regular reviews.

Coordinated and hosted data science webinars featuring industry experts, managing all logistics, marketing, and technical aspects to ensure successful execution and knowledge dissemination.

Contributed to the strategic growth of the Data Scientists Network community, fostering member connections and shaping organizational direction through active participation in strategic planning.

Emlaj Group
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Data Scientist

Lekki, Lagos, Nigeria

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Contract

Summary

Led data science initiatives at Emlaj Group, delivering actionable insights, predictive models, and robust data pipelines to drive business growth and optimize resource allocation.

Highlights

Developed and deployed interactive Tableau dashboards and reports, generating actionable insights into sales trends, customer behavior, and market dynamics that informed data-driven decision-making across the organization.

Engineered and deployed machine learning models (regression, clustering, time series) to accurately predict property prices, sales volumes, and crop yields, optimizing resource allocation and driving business growth.

Designed and implemented robust data pipelines, integrating disparate sources (property listings, customer databases, weather APIs) to ensure data quality, consistency, and scalability for advanced analytics.

Executed clustering analysis to segment high-value customer segments, directly informing targeted marketing campaigns that boosted revenue growth and customer loyalty.

Created and maintained comprehensive BI reports and dashboards, providing stakeholders with real-time KPI insights that facilitated data-driven strategic decisions.

Volunteer

Microsoft Copilot & Agentic AI Summit
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Virtual Mentor (Fellow)

EMEA

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Summary

Mentored winning teams at the virtual Microsoft Copilot & Agentic AI Summit, engaging with over 30,000 participants from EMEA.

Highlights

Mentored winning teams, coordinated activities, and answered questions for over 30,000 participants at the Microsoft Copilot & Agentic AI Summit.

Contributed to the development of emerging AI talent by providing guidance and support to teams in a high-profile virtual summit.

Agentcon Lagos
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AMA Expert at Azure AI Booth

Lagos, Lagos, Nigeria

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Summary

Served as an Ask Me Anything (AMA) Expert at the Azure AI Booth during AgentCon Lagos, contributing to the global AI community.

Highlights

Provided expert guidance and answered questions at the Azure AI Booth, supporting attendees at a major global AI community event.

Education

Indiana University
Indianapolis, Indiana, USA

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MSc

Applied Data Science

Imo State University
Owerri, Imo, Nigeria

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BSc

Computer Science

Grade: 4.0/5.0

Starfield College
Agege, Lagos, Nigeria

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High School Diploma

High School Diploma

Grade: 5 A1, 1 B2, 2 B3

Awards

Guinness World Records Holder

Awarded By

Guinness World Records

Achieved record for participating in the 'most users to take an online Multi-level artificial intelligence lesson in 24 hours', highlighting global engagement in AI education.

Microsoft MVP (Most Valuable Professional) Award

Awarded By

Microsoft

Recognized for significant contributions in Development Tools (.NET Category), demonstrating exceptional technical expertise and community impact.

LinkedIn Community Top Data Science Voice Q4

Awarded By

LinkedIn

Recognized as a Top 5% voice in the LinkedIn Data Science community for Q4 2024, indicating significant influence and thought leadership.

LinkedIn Community Top Data Mining Voice Q4

Awarded By

LinkedIn

Recognized as a Top 5% voice in the LinkedIn Data Mining community for Q4 2024, highlighting expertise and engagement in data mining discussions.

Top 0.5% Data Scientist on Kaggle (Dataset Category)

Awarded By

Kaggle

Ranked among the top 0.5% globally out of 14,000 data scientists in the Dataset category, showcasing excellence in data curation and feature engineering.

Top 0.3% Data Scientist on Kaggle (Notebook Category)

Awarded By

Kaggle

Ranked among the top 0.3% globally out of 59,000 data scientists in the Notebook category, demonstrating superior analytical and modeling skills.

GitHub Stats

Awarded By

GitHub

Achieved 130+ Stars and 1500+ followers on GitHub, reflecting strong open-source contributions and community recognition for technical projects.

Languages

English

Fluent

Yoruba

Conversational

French

Basic

Certificates

Python

Issued By

Sololearn

Artificial Intelligence A-Z Build 7 AI

Issued By

Udemy

Social/Behavioral Researchers

Issued By

CITI Program

IRB Members

Issued By

CITI Program

SQL Intermediate

Issued By

Sololearn

C# Intermediate

Issued By

Sololearn

Machine Learning A-Z AI Python

Issued By

Udemy

Data Science A-Z Hands On

Issued By

Udemy

Research Security Training

Issued By

CITI Program

Social and Behavioral Responsible Conduct of Research

Issued By

CITI Program

Microsoft Azure AI Engineer Associate

Issued By

Microsoft

Skills

Data Science & Machine Learning

Machine Learning, Python Scripting, Data Visualization, Data Mining, Data Wrangling, Predictive Modeling, Forecasting, Clustering Analysis, Customer Segmentation, Business Intelligence, KPI Monitoring, Sentiment Analysis, Text Classification, Hyperparameter Tuning, AutoML, ML.NET, LightGBM, SQL, Excel, Gretl, Tableau, MSVS SSDT (SSIS, SSAS, SSRS).

Artificial Intelligence & NLP

AI Engineering, Natural Language Processing (NLP), Retrieval Augmented Generation (RAG), Multi-agent Systems, AI-powered Recommendations.

Software Development & Platforms

C#, .NET MAUI, C#.NET MAUI Software Development, XAML, Mobile Development (iOS, Android, MacOS, Windows), Shell MVVM Architecture, GitHub, Debugging, Field Testing, Code Reviews, Scalable Architecture, UI/UX Design.

Projects

AI Calculator - Intelligent AI-Powered Calculator Application

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Summary

An intelligent AI-powered calculator application with multi-platform compatibility and advanced mathematical functions. Platform: iOS, Android, MacOS, Windows Framework: .NET MAUI, ML.NET, LightGBM, AutoML Developed an intelligent AI calculator application using .NET MAUI, enabling the app to run seamlessly across iOS, Android, MacOS, and Windows, ensuring consistent performance and user experience on all platforms. Implemented machine learning models for basic arithmetic operations: Stochastic Dual Coordinate Ascent (SDCA) for addition and subtraction, and LightGBM for multiplication and division, enhancing accuracy and performance for mathematical calculations. Designed a flexible architecture using .NET MAUI and ML.NET, which allowed each arithmetic operation to be handled by its own dedicated machine learning model, ensuring modularity and ease of future expansion. Utilized the AutoML functionality within ML.NET to automatically fine-tune the model hyperparameters, optimizing training accuracy and reducing the manual tuning effort for each machine learning model. Developed a dynamic ModelCall class to handle the logic of selecting and applying the appropriate machine learning model for each operation, providing a seamless integration of ML models with the user interface built using .NET MAUI. Trained separate machine learning models using seperate datasets for building seperate model of the different arithmetic operations, ensuring reliable performance for a variety of user inputs, and adapting to edge cases for both simple and complex calculations. Optimized performance by incorporating LightGBM for efficient, high-speed multiplication and division operations, ensuring that the app could handle large datasets and complex calculations in real-time. Integrated trigonometric functions (sine, cosine, and tangent) and power/root functions to broaden the app’s capabilities, offering a wide range of mathematical operations beyond basic arithmetic. Delivered a smooth, cross-platform user experience by developing the front-end interface using XAML in .NET MAUI, ensuring the app was intuitive, responsive, and visually appealing across all supported platforms. Tested the application thoroughly, performing real-world usability tests and ensuring all mathematical operations and machine learning models provided accurate results across various devices and input scenarios.

Barbara - Multi-Agentic AI Application

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Summary

A multi-platform AI application for mental health insights, leveraging smart device data and AI models. Platform: iOS, Android, MacOS, Windows Framework: .NET MAUI (Shell MVVM Architecture) Hackathon Submission: 2025 Microsoft AI Skill Fest (Winners to be announced) Developed a multiplatform AI application using .NET MAUI, ensuring compatibility across iOS, Android, MacOS, and Windows platforms while maintaining consistent user experience through Shell MVVM architecture. Integrated data from smart devices (i.e smart watch) to gather user-specific health metrics, allowing the application to provide highly personalized mental health insights based on both journal entries and health data. Designed and implemented an intelligent multi-agent system that mimics a well-read psychologist and data analyst, processing and analyzing users' journal entries and health metrics to provide actionable recommendations. Collaborated with cross-functional teams to create a seamless journal app integration, allowing users to record daily reflections and provide mental health insights that are both data-driven and psychologically sound. Participated in the 2025 Microsoft AI Skill Fest Hackathon, submitting the project as a proof of concept for AI-driven mental health improvement, while keeping the codebase optimized and scalable for future development. Established an intuitive user interface using XAML and C# , with a focus on accessibility and ease of use, enabling users to track their mood, mental health progress, and receive motivational prompts. Trained AI models using ML.NET to analyze textual and numerical data from users, delivering actionable insights based on sentiment analysis and health condition trends, aiming to reduce pandemic-related depression symptoms.

Talking Stage - Multi-Platform QnA AI Application

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Summary

A multi-platform QnA AI application for automating romantic relationships question answering, utilizing NLP and ML.NET. Platform: iOS, Android, MacOS, Windows Framework: .NET MAUI, ML.NET, LightGBM Developed a multi-platform QnA AI application using .NET MAUI framework, enabling the app to run seamlessly across iOS, Android, MacOS, and Windows, ensuring consistent functionality and design on all devices. Leveraged NLP techniques from the ML.NET framework to process and understand natural language queries from users, allowing the AI to engage in meaningful, context-aware conversations during the "talking stage" of romantic relationships. Integrated LightGBM's multiclass classification algorithm for text classification, enabling the app to predict and match user queries with predefined responses based on the most accurate classification of the user input. Engineered a machine learning prediction engine that intelligently matches user queries to a predefined dictionary of responses, offering users a personalized, AI-driven experience while reducing the burden of repetitive conversations. Designed and implemented a dynamic response system using machine learning models to handle varied user inputs and provide tailored responses, thus improving the user experience during the early stages of romantic conversations. Optimized the performance of the application by incorporating efficient data processing pipelines for real-time NLP query analysis, significantly reducing response times and enhancing the app’s responsiveness. Collaborated with cross-functional teams to refine the user interface and experience, ensuring the application was both intuitive and engaging for users seeking a conversational AI to assist with the "talking stage" in relationships. Achieved a seamless user experience through XAML to craft an intuitive and accessible UI, enabling users to interact easily with the app without technical hurdles, and making sure the app could scale as new features were added.

Bumble Formula - Classification AI Application

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Summary

A classification-based AI application for predicting user behavior on dating apps. Platform: iOS, Android, MacOS, Windows Framework: .NET MAUI, ML.NET Developed a classification-based AI application using ML.NET and .NET MAUI, enabling a multiplatform solution for predicting user behavior on dating apps such as Bumble, Tinder, and Badoo, providing insights into trends and patterns of Nigerian women. Utilized the AutoML toolkit from ML.NET for hyperparameter tuning, optimizing the classification model to accurately predict a variety of behaviors based on publicly available profile data, ensuring improved prediction accuracy for different user profiles. Designed and implemented a custom classification model to identify behavioral patterns and trends in users' profiles, offering data-driven insights that could assist men in navigating the online dating environment more effectively. Maintained rigorous data privacy standards by anonymizing personally identifiable information (PII) and ensuring compliance with the Nigeria Data Protection Regulation (NDPR), adhering to best practices for ethical data use and protection. Trained and tested the machine learning models using diverse datasets, ensuring the model could handle a range of behaviors and responses while remaining focused on ethical use, with no sensitive or personally identifiable data being processed. Leveraged ML.NET’s classification algorithms and feature selection techniques to ensure that the model could categorize user behavior accurately, improving the ability to predict and understand user preferences based on their public dating profiles. Presented findings and insights from the project in a clear, accessible format, demonstrating the potential for machine learning to assist in customer segmentation and enhance decision-making processes in a business or social context. Explored the potential for future development by creating a roadmap for automating behavior classification and streamlining the online dating experience, with the long-term goal of helping users find better matches more efficiently through AI-powered recommendations.

Interests

Artificial Intelligence
Robotics
Quantum Computing
Psychology
Documentaries
Mindfulness Meditation
Reflection/Gratitude/Journaling
Spotify/Netflix
Professional Affiliations

ACM SIGAI, Microsoft Expert Network, Black In AI.