Hey, I’m Ernest…

Data Scientist | ML Engineer | AI Researcher

I turn complex data into intelligent systems that power decisions across enterprise tech, healthcare, fintech, media, and research. From building scalable ML pipelines to deploying LLM-based solutions, I apply machine learning, NLP, and cloud technologies to solve real-world challenges.

🧠 Winner of the 2025 RAISE AI Competition (1st out of 119 teams)
🎓 MS in Data Science (Montclair State University, Class of 2025)
🔬 BMS Science Scholars Grant Recipient | AMIA & IEEE Paper Author

When I’m not solving data challenges, you’ll find me mentoring, building, or learning something new. Let’s connect and create something impactful!

Learn more about me:

About Me…

Montclair State University

M.S. Data Science (Graduated: May 7th, 2025)

GPA: 3.97 | Thesis: Advancing Drug-Drug Interaction Prediction Using Graph Neural Networks

Key Achievements & Recognition

  • Alpha Epsilon Lambda Honor Society (Top 5% of graduate students)

  • Winner, RAISE 2025 AI Competition (1st Place out of 119 teams) – “Our Future With AI: Utopian or Dystopian?”

  • BMS Science Scholars Grant Recipient – $5,000 research grant for LLM-powered healthcare prediction

  • Outstanding Graduate Student Employee Award – Finalist, MSU 2024

  • Featured in MSU Communications, website, and social platforms for exemplary internship, research, and leadership

  • President & Founder, NextGen Tech Thinkers Club – MSU’s hub for AI, Data Science & Emerging Tech dialogue

  • Tri-Alpha Honor Society, Delta Chi Chapter, MSU

Mentorship & Leadership in Data Science

  • Graduate Research Assistant for AI and Healthcare projects (IEEE CBMS, BHI, AMIA paper acceptance)

  • Served as GLOBE IVSS Judge, reviewing global student research projects in science & sustainability

  • Member, Tri-Alpha Honor Society (Delta Chi Chapter, MSU)

  • Mentored 30+ students at the Hu-Au XR Lab in building VR training modules

  • Designed motion-tracking and simulation systems to enhance immersive learning

Data Solutions

  • Built AI-driven compliance systems for 220K+ medical app reviews, automating FDA, FTC, HIPAA risk assessments (paper)

  • Developed LLM-based predictive pipelines for ICU readmission modeling, reducing bias and improving equity (project)

  • Led GNN-based drug interaction research, integrating biomedical, semantic, and molecular embeddings (paper)

  • Created dashboarding and forecasting tools used by data leaders at the Port Authority of NY & NJ (project)

  • Designed data pipelines and optimized ML workflows across healthcare, fintech, and energy domains

Certifications & Skills

  • AWS Certified Cloud Practitioner (AWS)

  • Natural Language Processing Specialization (Coursera)

  • Machine Learning Specialization (Coursera)

  • The Complete Data Science Bootcamp (365 Careers)

  • Data Analytics OneCampus Academy (GATIP)

  • Bright Network Internship (Tech Track, UK)

  • Python, SQL, R, Java, Excel, C++

  • Machine Learning (TensorFlow, Keras, Hugging Face Transformers)

  • Cloud Computing (AWS, Azure, Google Cloud, Snowflake, Databricks)

  • Business Intelligence (Power BI, Tableau, QuickSight, SAS)

Projects & Publications

Optimizing Large Language Models (LLMs) for ICU Readmission Prediction

A personalized prediction framework for ICU readmissions, built using fine-tuned language models (PubMedBERT) and ML classifiers. The project enhances treatment equity for Black, Hispanic, and White populations through tailored modeling pipelines. Backed by Bristol Myers Squibb’s Science Scholars’ mission, this work demonstrates the real-world value of representation-aware ML in healthcare—improving both fairness and clinical accuracy for diverse populations.

View Project

Advancing Drug-Drug Interaction Prediction using Knowledge Graphs and Graph Neural Networks

This study combines Knowledge Graphs (KGs) and Graph Neural Networks (GNNs) to predict drug-drug interactions, improving safety in polypharmacy. By integrating DrugBank, PubChem, and PubMed data, the model enhances link prediction accuracy. A Graph Convolutional Network (GCN) outperforms other models, while ChemBERTa-based molecular encoding and literature mining improve predictions for unseen drugs.

View Paper

Sales Performance Dashboard: Analyzing Revenue, Orders, and Product Trends

I developed an interactive sales analytics dashboard that consolidates multi-source retail data to uncover trends in revenue, order volume, and product performance. The dashboard supports strategic decision-making by highlighting seasonal patterns, high-performing SKUs, and return rates across time. Built using Power BI, it empowers business teams to explore insights via dynamic filters and charts, enabling faster, data-driven responses to shifts in consumer demand and inventory performance.

View Project

Supervised Learning for Power Plant Energy Generation in the US

This project applies supervised machine learning techniques to predict power generation output across U.S. plants, using features such as plant location, capacity, fuel type, and climate region. I designed and trained multiple models—ranging from linear regression to XGBoost—to forecast energy generation with high accuracy. By analyzing the geographic and technical factors affecting plant performance, the study provides actionable insights for optimizing energy production, sustainability planning, and resource allocation in the energy sector.

View Project

Automated Regulatory Classification of Mobile

This study leverages AI and NLP to automate the regulatory classification of mobile medical apps, achieving 85% accuracy in detecting compliance risks. Findings show 54.8% of Google Play and 58% of Apple App Store apps lack proper oversight. The proposed framework enhances pre-publication screening and real-time monitoring, ensuring safer and more transparent healthcare apps.

View Paper

AI-powered financial crime prevention with cybersecurity, IT, and data science in modern banking

This paper explores how AI and data science methodologies are transforming financial crime prevention in banking, highlighting the superior detection rates and reduced false positives achieved through AI-powered solutions. It also identifies key challenges, including data privacy and regulatory compliance, while proposing future research directions to enhance these systems.

View Paper

Projects’ Code Files

Languages & Tools

What people have said…

"In addition to his technical skills and contributions to improve our management strategies, Ernest efficiently managed multiple projects, including website updates, all while maintaining high-quality work. His strong work ethic and problem-solving abilities made him a valuable asset, and I am confident he will excel in any future role."

Hanson Lee, Director, Operations Services, Port Authority of NY&NJ

"Ernest is not just hardworking but passionate at what he does, he is a team player and was an inspiration even at the time. He is calm, cool, collected and intelligent, knows why, how and when to deliver his responsibilities. He is an asset at what ever level or responsibility you hold him accountable for. I have no doubt he will continue to do awesomely well."

Emmanuel Nwaiwu, Project Manager, Business Intelligence.Operations Jumia Nig.

"Ernest’s focus on using data science in healthcare research and supporting clinical trials demonstrates his drive and innovation. His technical proficiency and passion for healthcare research make him a valuable asset, and I am confident he will make significant contributions to future healthcare projects."

Hao Liu Ph.D, Assistant Prof. Montclair State University

"Ernest’s positive attitude and unique ability in maintaining the highest quality in his work, together with his exceptional communication skills makes him an asset to any organization. I have no doubt that Ernest will continue to excel in his future endeavors and highly recommend him to any potential employer or partner."

Jennifer Odimgbe-James, Legal & Compliance Analyst

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