Welcome! I'm Ronald Doku, Ph.D.

Data Scientist & Machine Learning Engineer

I'm a data scientist and machine learning engineer who thrives at the intersection of innovative research and practical application.

This space is where I share my latest projects, articles, some possibly bad app ideas, and advancements in fields like NLP, big data analytics, blockchain, and cybersecurity.

Whether you're here to explore projects I've done, discover insights from real-world projects, or explore what's possible, I invite you to join me in making sense of today's technology, and revolutionizing it for tomorrow!

I specialize in
10+
Publications
5+
Years Experience
5+
Projects/Articles
Ronald Doku
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About Me

Ronald Doku

Hello! I'm Ronald Doku. My life has been guided by a deep love of technology and the belief that it can transform our world for the better. This platform is where I share my ideas, projects, and sparks of inspiration, all centered on using technology to make a meaningful impact.

Academic Journey

I'm proud to share that I became the first person at Howard University to earn a bachelor's, master's, and Ph.D. in Computer Science. When the Ph.D. program launched in 2015, I was in the midst of my master's degree. After completing it, I took a one-year co-op to gain industry experience. Upon returning, I had the unique opportunity to make history as the department’s first triple-degree graduate. With many of my graduate-level courses already completed from my the master's program, I was able to focus heavily on research and accelerate my progress, completing the Ph.D. between 2017 and 2020. Outside of academia and work, I'm a lifelong soccer fan and captain of a recreational league team called AfroBeatz. Off the field, you'll often find me writing short stories, playing FIFA, or getting lost in a great book.

Personal Values

Family is at the heart of who I am: my wife, my mother, and my two sisters are a constant source of love and support. Their encouragement fuels my drive.

Below, you'll find a timeline of my journey in technology. Thank you for stopping by—I hope you'll join me in exploring the limitless potential of innovation, creativity, and collaboration!

Experience Timeline

Click on any timeline item to view detailed information

Stealth Startup

Machine Learning Engineer/Data Scientist

Oct 2024 - Present

  • Developing AI-powered partnership platform with LLMs & RAG
  • Building ML models & AI agents for partner matching
  • Implementing end-to-end data pipelines with Python & AWS

Oracle Advertising

Senior Data Scientist

Aug 2020 - Jul 2024

  • ↑7% ad relevance, ↑10% campaign efficiency
  • ↓25% processing time with PySpark pipelines
  • ↑12% targeting precision with NLP keyword tool
  • ↑15% conversion rates through A/B testing

ConsenSys

Software Engineer Intern

Jun 2018 - Aug 2018

  • Developed smart contracts on Ethereum blockchain
  • Integrated front-end interfaces with blockchain back-end
  • Built decentralized applications (dApps)

Howard University

Ph.D. Computer Science

Aug 2017 - May 2020

  • Specialized in Cybersecurity & Blockchain
  • Published research on decentralized data sharing
  • Achieved first BS+MS+Ph.D. in CS at Howard

Featured Projects

Neural Networks Demystified: Transformations Through Embedding Spaces
Machine Learning Deep Learning Data Science
2025

Neural Networks Demystified: Transformations Through Embedding Spaces

This article unpacks how neural networks work by exploring the hidden layers that transform raw data into rich, abstract representations. It explains how neurons act as pattern detectors, how weigh...

Python PyTorch
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Beyond Semantics: A Value-Driven Approach to Word Embeddings
Deep Learning Machine Learning Data Science NLP
2025

Beyond Semantics: A Value-Driven Approach to Word Embeddings

This article introduces a novel value-driven word embedding model that transcends traditional semantic approaches. By incorporating continuous external metrics such as price, the model aligns word ...

Python PyTorch
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The Company Words Keep: Building Meaningful Embeddings from Scratch
Deep Learning NLP
2025

The Company Words Keep: Building Meaningful Embeddings from Scratch

Intuitive approach to understanding word embeddings and its implementation.

Python PyTorch Embeddings
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Analyzing Declining Metrics
Data Analysis Product Analytics A/B Testing Data Science
2025

Analyzing Declining Metrics

This guide helps diagnose metric drops using MECE-based hypotheses, segmentation, stats, and A/B tests—empowering data pros to turn unexpected shifts into actionable business insights.

View Details
Introduction to Product Analytics
Data Analysis Product Analytics
2025

Introduction to Product Analytics

This article kicks off a series on product analytics, highlighting the importance of data-driven strategies like A/B testing, KPI analysis, and metric frameworks to boost engagement and business growth.

View Details
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Skills & Expertise

Programming Languages

Python 95%
R 85%
SQL 90%

ML & AI

TensorFlow 90%
PyTorch 85%
scikit-learn 95%

Research Publications

10
Publications
700
Citations
5
Research Areas

Research Focus

Blockchain & Security

Decentralized frameworks for secure data sharing and privacy

Federated Learning

Data-driven security and poisoning attack mitigation

IoT & Smart Cities

Resilient architectures for IoT and smart systems

Featured Publications

220 citations

Cybersecurity in big data era: From securing big data to data-driven security

DB Rawat, R Doku, M Garuba
IEEE Transactions on Services Computing 14 (6), 2055-2072
2019
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154 citations

Blockchain technology: Emerging applications and use cases for secure and trustworthy smart systems

DB Rawat, V Chaudhary, R Doku
Journal of Cybersecurity and Privacy 1 (1), 4-18
2020
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66 citations

Towards federated learning approach to determine data relevance in big data

R Doku, DB Rawat, C Liu
IEEE 20th International Conference on Information Reuse and Integration
2019
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Recent Publications

Mitigating data poisoning attacks on a federated learning-edge computing network

R Doku, DB Rawat 2021

Novel approach for identifying and mitigating data poisoning attacks in edge computing environments using federated learning techniques.

42 citations Read Paper

Iflbc: On the edge intelligence using federated learning blockchain network

R Doku, DB Rawat 2020

This paper proposes iFLBC edge, a framework combining blockchain and federated learning to address data quality issues in AI applications. Using a mechanism called Proof of Common Interest (PoCI), the system identifies relevant data from diverse sources, trains local models that are then aggregated and stored on blockchain. This approach enables network members to provide AI services at the edge, enhancing privacy and reducing latency while making intelligence more accessible to end-users.

48 citations Read Paper
View Complete Publication Record on Google Scholar

Insights & Innovation

Practical Tech Ideas

Exploring practical application ideas and technological solutions with real-world implementation potential

Occasio

Users post about their mood or a special event, and businesses respond with tailored offers based on set criteria.

Read Article

SyteMatch

Where You Are Is Who You Meet. SyteMatch is the newest revolution in the world of dating apps. Taking location-based...

Read Article

VibezOnTheGo: Revolutionizing Your...

VibezOnTheGo is an idea for a smart music app that personalizes and syncs your favorite tunes to any shared space you enter.

Read Article
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ML Research Horizons

Exploring future directions and innovations in machine learning and data science research

No ML research articles yet.

Explore All Insights

Get in Touch

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