Applied AI & Machine Learning
Custom model development, LLM integration, and end-to-end data pipelines — engineered for production, not demos. We’ve worked on problems in NLP, recommender systems, affective computing, and information retrieval since before ‘AI’ was a marketing term.
Robotics Systems
Embedded control systems, sensor fusion, and full-stack robot engineering from prototype to field deployment. We design for the real world — where hardware fails, environments are unstructured, and uptime is non-negotiable.
Autonomous Drones & UAS
FAA-compliant design, autonomous navigation, custom payload integration, and real-time command-and-control systems for commercial and research applications. From airframe selection to flight software, we own the full stack.
R&D Partnerships
Embedded research engagements for organizations that need experimental capability without building a full internal lab. We work best with clients who have a hard problem and the flexibility to explore unconventional solutions.
SELECTED WORK
Open-source graph database & Prolog engine
Problem: Existing RDF stores lacked native Prolog reasoning and the performance needed for large-scale knowledge representation in production AI systems.
What we built: Designed and built VivaceGraph — a full graph database, RDF store, and Prolog implementation in Common Lisp. The codebase is open source and has been adopted by researchers in AI and knowledge engineering worldwide.
Outcome: Actively maintained; forked and used across multiple research institutions. Available at github.com/kraison/vivace-graph-v3.
Tags: Common Lisp · Graph Databases · Knowledge Representation · Prolog · Open Source
Affective agent architecture for goal-directed AI
Problem: Classical AI planning systems lack the flexible, affect-modulated decision-making that allows agents to prioritize and adapt under uncertainty.
What we built: Developed an affective agent architecture that uses emotion-inspired variables to modulate goal selection and planning behavior in multi-agent systems. Research was conducted in partnership with DePaul University.
Outcome: Presented at the Seventh Conference on Artificial General Intelligence (AGI-14). Published in Springer Lecture Notes in Computer Science.
Tags: AGI · Affective Computing · Multi-Agent Systems · Planning · Published Research
Automatic self-adaptation to mitigate software vulnerabilities
Problem: Critical infrastructure systems need to detect and respond to novel exploits in real time, without waiting for human intervention or a patch cycle.
What we built: Contributed to FUZZBUSTER — a DARPA-adjacent research program developing self-organizing systems capable of detecting and automatically adapting to software vulnerabilities without operator intervention.
Outcome: Published at the IEEE Conference on Self-Adaptive and Self-Organizing Systems (SASO 2012). Contributed to the foundational literature on self-healing systems.
Tags: Cybersecurity · Self-Healing Systems · Self-Organizing Systems · IEEE · DARPA
