Mikel K. Ngueajio 🙋🏽‍♀️

I am Ph.D. (ABD) in Computer Science at Howard University, advised by Dr. Danda Rawat, with a focus on using machine learning to better understand human language and promote responsible, socially impactful AI.. I’m developing human-aligned systems to measure hate intensity in social media content for effective content moderation. You can find my publications on Google Scholar. I have served as conference reviewer for Black in AI 2024, Women in Machine Learning 2024, Deep Learning Indaba and IndabaX Cameroon(Organiser and Fund Raising). I am a Graduate Research Assistant for the CoE-AIML. Served as Adjunct Instructor at CMU-Africa, in Kigali, Rwanda. Back in Washington DC, USA September 2026, Full time PhD- Expected: May 2027.

CV/Resume

Accomplishments 🎯

First Technical Papers Accepted at top tier AI, NLP, ML conferences: ACL-WOAH Conference 2025, EMNLP findings 2025, WIML@NEURIPS 2025. First Time Journal publication at the ACM Csur Journal 2025

Selected as Machine Learning ad Systems Rising Star by ML Commons 2024. Presented research at Nvidia HQ in Santa Clara, CA.

Amazon AWS PHD Research Fellowship recipient 2023-2024; Awarded 69,000 for PHD research advancement. APPLE TMCF Scholarship Recipient 2023-2024: Awarded $15000 for PHD research advancement.

Third Place poster Winner at Richard Tapia Conference 2023. Poster titled: Towards Improving Chatbots for Multilingual conversations

Black ComputerHer Fellow 2022-2023

First Place Poster winner at ADMI Conference 2022

First Place Innovator Award Recipient at the 2021 CMD-IT Innovation Challenge

First place Research Poster Winner at the 2021 CCSC-Eastern Regional Conference

Experience 🎒

Adjunct Professor - CMU-Africa
Aug 2025 - Aug 2026
Featured Link
  • Teaching graduate-level courses in Programming for Data Analytics, Mobile Big Data Analysis and Mgmt.
  • Designed hands-on assignments and projects integrating theory with practical applications.
  • Support student research, review and publication guidance, and foster a collaborative learning environment.
Graduate Research Assistant - CoEAIML Lab
Aug 2024 - Present
Featured Link
  • Ph.D. dissertation topic: Building human-aligned systems to measure hate intensity in social media content for effective content moderation
  • Skills Acquired: Statistical Measures, Sentiment Analysis, Prompt Engineering and Optimization, LLMs; Explainable AI.
Graduate Research Assistant - ABLab
May 2020 - May 2024
Featured Link
  • Created a Microaggression dataset by extracting relevant content from TV shows, Blog posts, and social media.
  • Mentored 8 student in Research and development. Won Research prizes and competitions.
Machine Learning Engineering Intern - Apple
June 2023 - August 2023
  • Build a system for evaluating Siri dialogues integration with LLM.
  • Skills acquired: Python; data extraction and preprocessing, Software creation, Testing, Error Handling, and debugging; Version control and code management; Data Serialization and Parsing using NLP; API integration, request and response handling, Software Documentation, Prompt Engineering, Generative AI and LLM.
Web development Apprentice - Bloomberg
June 2021 - August 2021
Featured Link
  • Designed and built a website, “HBCU Tech Journeys” to help HBCU students network, and collaborate.
  • Skills acquired: CSS, HTML, Web Design, and Hosting: WordPress and GitHub Pages.
Data Scientist Intern - Amazon
August 2019 - November 2020
  • Build a customer subscription database using DataGrip to decide on subscription services available to customers, thus reducing inquiry and operation time by 20% as compared to standard web scraping techniques
  • Annotated data used to create the multiclass dataset and Used it to build model for assessing customer sentiment thus facilitating user satisfaction and retention
Kaggle conpetitor and content creator - Kaggle
June 2020 - present
Featured Link
  • Women in Data Science Datathon (2024): Equity in HealthCare: Task to predict if the patients received metastatic cancer diagnosis within 90 days of screening. Used ML-based data cleaning and supervised ML -CatBoosting Model. (Rank: top 35%).
  • Santander Customer Transaction Prediction (2019): for predicting if a customer will make a transaction. Used the Light gradient boosting method with 15-fold cross-validation and achieved a score of 90.07%. (Rank: Top 37%).
  • Women in Data Science Datathon (2019): An image classification problem to determining the chances of deforestation due to oil palm fields. Used Deep and Transfer learning techniques yield 79% prediction accuracy. (Rank: top 87%).

Education 🎓

Expected: May 2027
PHD Candidate - Computer Science
Howard University
GPA: 3.8/4.0 (currently)

Research Focus

  • LLM evaluation and Benchmarking
  • Natural Language Processing
  • Machine Learning
  • Human Centered AI/AI for Society
Masters of Science in Computer Science
Howard University
GPA: 3.6/ 4.0
Got Published at the Association for the Advancement of AI titled " ABL-Micro: Opportunities for Affective AI Built Using a Multimodal Microaggression Dataset"
Bachelor of Science in Mathematics
University Of Buea
GPA: Second Class Upper

Contact 📧

Have a question?, Looking to collaborate? or say hi?!
Email me