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Thomas J. James

Making the Best Better

Real-World Work Experience

Projects developed based-upon requests made by a client & information provided by the stakeholders

Role: Project Manager
Project: Adaptive AI Tutor for Refugee Education in Jordan (Currently Ongoing)
Employer: Omdena

  • Lead the development of an AI-powered adaptive tutoring & psychosocial support system to support the education learning-gaps & mental health of Syrian refugee students in Jordan
  • Provide project guidance which aligns with moral & professional standards
  • Develop benchmark metrics for LLMs (Llama3 & Mistral) & APIs (Groq & OpenAI) to manage project progress
  • Oversee data governance, prompt engineering, data pipeline development, RAG integration, & authoring of AI Agents capable of personalizing the user experience through application of SMART, SCRUM & Notion
  • Provide guidance, direction, and exchange ideas during weekly project team meetings

Links coming soon — project is ongoing.

Role: Lead Machine Learning Engineer
Project: Predictive Modeling and Forecasting of Malaria-Spread in Liberia
Employer: Omdena

  • Create a Liberia malaria-forecasting application to aid in the optimal distribution of malaria vaccinations
  • Develop ensemble and time-series analysis models to predict malaria cases & death-counts grouped by county
  • Conduct multivariate data analysis & observe what is causing 3,548 annual malaria-deaths per year
  • Provide motivation when-needed to fellow project leaders and members
  • Present Liberian community with a malaria-forecasting application to improve malaria survival rates
Malaria Spread Liberia — Github Malaria Spread Liberia — Omdena Certificate

Role: Machine Learning Engineer / Project Co-Leader
Project: AI-Powered Warning System for Extreme Weather Conditions in Tanzania
Employer: KESHO AI

  • Develop an extreme weather forecasting app to assist the Tanzania Meteorological Agency
  • Determine which feature-variables can provide the most accurate predictions using EDA & feature-engineering
  • Preprocess satellite-imagery into numerical-vector embedding using segmentation, masking, banding, and development of a convolutional neural network
  • Synthesize CNN-LSTM & ConvLSTM models for comparison of model-performance strengths & weaknesses
  • Lead semiweekly meetings & provide feedback for fellow project members' progresses
  • Provide Tanzanian citizens a Streamlit application capable of predicting extreme weather events 20% faster than currently available applications
Extreme Weather Predictions — Github Extreme Weather Predictions — Omdena Certificate

Role: Machine Learning Engineer
Project: Developing Personalized AI Travel Advisors for Paris Olympics 2024
Employer: Omdena

  • Design & develop a personalized AI-Travel-Advisor for Paris tourists attending the 2024 Olympic Games
  • Guide team through proper methods of data-security while performing data-collection
  • Perform Prompt-Engineering on multiple LLM models; including Llama3, Gemma, and Mistral
  • Retrieve external CSV & PDF file data using Retrieval Augmented Generation (RAG)
  • Develop multiple multi-AI agent models which use RAG, APIs, & LLMs to personalize the user-experience
  • Exchange ideas with project teammates to promote collaboration & teamwork
  • Deliver the Paris 2024 Olympics AI Travel Advisor application prior to the Olympics' official start
Paris Olympics — DagsHub Paris Olympics — Omdena Certificate

Role: Junior Machine Learning Engineer
Project: Mapping Seagrass Meadows with Satellite Imagery & Computer Vision
Employer: Omdena

  • Develop predictions of where the highest decline of Posidonia oceanica seagrass meadows will occur next in Italy and Greece regions of the Mediterranean Sea
  • Collect & preprocess satellite imagery using Google Earth Engine, masking, segmentation, banding, histogram analysis, data augmentation, and image-resolution adjustments
  • Experiment & analyze application of multiple computer-vision deep-learning models such as UNet, Unet+, UNet++, and DeepLabV2
  • Fine-tune & apply the UNet++ convolutional neural network capable of pixel-level classification
  • Forecast locations of species' disappearance-rates to help support Mediterranean-seagrass restoration efforts
Mapping Seagrass Meadows — DagsHub Mapping Seagrass Meadows — Omdena Certificate