My messaging is built on the intersection of accessible data interpretation and agentic AI storytelling. I bridge the gap between complex bioacoustic sensors and intuitive human action.

  • Who I am: A UX Engineer and AI Architect specializing in “data storytelling” for marine conservation.
  • What I do: I build integrated layers that allow for a “multi-dimensional read” of environmental conditions—combining live audio, machine learning detections, and human sightings into actionable insights.
  • What people should hire me for: Developing AI-driven research assistants (RAG/Agentic AI), designing high-fidelity data visualization dashboards, and building full-stack IoT-to-cloud pipelines.

Demos from the last few months:

  • Demo 1: The Agentic AI Researcher: Showcasing use of the LlamaIndex agentic framework to perform natural language to SQL queries against the Orcasound database.- - Demo 2: WebAudioAPI Visualizer: A technical deep dive into building live spectrograms, waveforms, and oscilloscopes in React.
  • Demo 3: IoT to Dashboard: demonstrating the ESP32 stack—from on-device MicroPython to a FastAPI/PostgreSQL backend and React frontend.

Planned topics:

  • Multi-Modal AI Orchestration: Documenting how the OrcaAgent agentic AI can “reason” across different inputs—integrating PTZ camera fin-detections with acoustic clips to increase localization confidence.
  • The “Conservation Coach”: A series on using LLMs to provide personalized recommendations for users based on their location and observations, moving the “Take Action” feature from sketch to deployment.
  • RAG for IoT: Exploring the evolution of the ESP32 project into a more robust “hydrophone deployment kit” that performs semantic analysis.
  • Data Storytelling through “Bouts”: Showcasing high-fidelity “storymaps” that combine human commentary, AI detections, and AIS vessel tracks into a shareable narrative for policy makers.
  • React State Management: Implementing Zustand on Orcasound Live, unlocking maps, search, and historical data views