Projects

Tools and frameworks for wildlife monitoring, conservation technology, and edge AI systems.

Academic Project Tracker

I built this project management tool after growing tired of tracking projects across Google Docs, Trello, and other fragmented tools. Notes, tasks, and priorities were scattered across platforms, often requiring subscriptions to unlock basic features. Drawing on my background in systems engineering and product management, I designed a lightweight workflow that centralizes planning, tracks progress, and supports the competing demands of academic research.

WildLabs Edge Computing Group

Edge Computing Workshop at ICTC 2025

Join us for hands-on learning and networking!

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Co-lead, 2025–2026 Group Leadership Programme

This group unites those working at the intersection of edge AI and conservation, focusing on real-time, on-device data processing for environmental monitoring. We facilitate sharing of tools, models, and strategies to overcome challenges in remote, low-connectivity areas.

Key Features:

  • Community-driven knowledge sharing
  • Curated resources for edge AI in conservation
  • Collaborative problem-solving for remote deployments
  • Best practices for low-power, low-connectivity scenarios

SmartWilds: Bridging Digital and Natural Worlds

Autonomous Drones and Edge AI for Wildlife Conservation

In collaboration with The Wilds, we are developing autonomous drones and edge AI systems for wildlife monitoring and conservation in this 10,000-acre non-profit safari park and conservation center in southeastern Ohio.

Project Overview:

  • Multi-modal wildlife monitoring dataset
  • Real-time behavior tracking and analysis
  • Edge computing for on-device processing
  • Integration with existing conservation workflows

Technologies:

  • Autonomous UAV systems
  • Computer vision and deep learning
  • Edge AI deployment
  • Multi-sensor data fusion

kabr-tools: Automated Framework for Multi-Species Behavioral Monitoring

Open-Source System for Wildlife Behavior Analysis

Watching wildlife at scale is hard—traditional field observations are slow and limited. That's why we built kabr-tools: an open-source system using drones + ML to automatically track multiple species and extract behavioral, social & spatial patterns.

Core Capabilities:

  • Automated multi-species detection and tracking
  • Behavioral pattern extraction
  • Social network analysis
  • Spatial movement analysis
  • Temporal activity patterns

Technical Features:

  • Drone-based data collection pipeline
  • ML-powered individual identification
  • Automated behavior classification
  • Scalable processing for large datasets
  • Integration with ecological research workflows

Use Cases:

  • Wildlife population monitoring
  • Behavioral ecology research
  • Conservation status assessment
  • Habitat use analysis

AI-Driven Animal Ecology Workloads at the Edge

Tool for Characterizing and Modeling ADAE Studies

This tool helps researchers characterize and model AI-Driven Animal Ecology (ADAE) studies at the edge. It provides insights into computational requirements, energy consumption, and deployment strategies for edge-based wildlife monitoring systems.

Key Features:

  • Workload characterization for edge deployments
  • Energy consumption modeling
  • Performance prediction
  • Resource allocation optimization
  • Interactive visualization tools

Applications:

  • Planning edge AI deployments
  • Optimizing hardware selection
  • Estimating field deployment requirements
  • Comparing different deployment strategies