HPC+AI Infrastructure · Neuromorphic Computing · Quantum-Centric Supercomputing · Forward-Deployed Engineering
Where infrastructure meets intelligence.
Palantir Foundry / AIPThree integrations — entity discovery + ontology enrichment, multi-modal targeting, and autonomous ontology generation via SymWisdom. |
LLM & Gen AI InfrastructurevLLM, GPFS KV cache sharing, semantic routing, Nemotron-120B reflection engine, multi-LLM orchestration at scale. |
Neuromorphic & Heterogeneous Compute10-chip AKD1000 hive mind, QPU+NPU+GPU+CPU orchestration, sub-millisecond edge inference across 12 silicon architectures. |
Autonomous Ontology DesignSystems that discover, name, and structure concepts from continuous perception — no human modeling required. |
Data Platform ArchitecturePetabyte-scale GPFS, mmap’d shared state across 11 nodes, experience lifecycle management, three-tier KV cache replacing Redis. |
Forward-Deployed Engineering13 years delivering to government, research, financial services, healthcare, and life sciences. |
Articles on AI infrastructure, neuromorphic computing, and the architecture of intelligence.
20 demonstrations built between December 2025 and March 2026.
| Date | Demonstration | Platforms |
|---|---|---|
| Mar 20 | SymWisdom: The Experiencing LLM — 10 AKD1000 chips perceiving across 7 modalities, Nemotron-120B reflecting every 45 seconds, 6 wisdom objects crystallized into Foundry from 1,646 reflections in 40 hours ▸ full writeup | NPU (AKD1000 x10), NVIDIA GPU (vLLM), Symphony, GPFS, Palantir Foundry |
| Mar 16 | NeuroDOOM: Hive Mind Learns to Play DOOM — 10 AKD1000 chips as hive mind playing DOOM; ~4ms per-chip inference, 35fps real-time at ~10W total. Plays DOOM so fast it’s hard to watch. ▶ video | NPU (AKD1000 x10), Intel N100, Symphony, GPFS |
| Mar 11 | Neuromorphic Hive Mind Music — 10 AKD1000 chips as ensemble, each trained on distinct catalog slices; played Pachelbel’s Canon in D and Ozzy Osbourne’s Crazy Train ▶ Canon ▶ Crazy Train | NPU (AKD1000 x10), Intel N100, Symphony, GPFS |
| Mar 4 | Non-Extractive Targeting with Symphony, Akida, and Foundry — 10-chip multi-modal sensor fusion across 7 modalities with Symphony emergence engine writing confirmed events to Foundry; built in five days ▶ video ▸ full writeup | NPU (AKD1000 x10), Symphony, GPFS, Palantir Foundry |
| Feb 20 | Neuromorphic Deepfake Voice MFA — Three-layer auth: KeyCloak OIDC/JWT, Akida voice biometric (109μs, 92.6%), adversarial training vs Qwen3-TTS ▶ video | NPU (AKD1000), NVIDIA GPU (Qwen3-TTS), Symphony, GPFS |
| Feb 18 | vLLM + GPFS KV Cache Sharing — 16 llm-d algorithms + 15 capabilities reimplemented on Symphony; three-tier GPFS cache replacing Redis; cross-model KV transfer Granite 2B to 8B to 34B | NVIDIA GPU (vLLM), Symphony, IBM Cloud, GPFS (three-tier KV cache w/ ILM) |
| Feb 10 | Akida Behavioral Biometrics — Voice emotion analysis of Palantir earnings livestream; 71μs inference, 89.3% confidence; detected vocal excitement 2-3 seconds before 15x volume spike ▶ video | NPU (AKD1000), Symphony, GPFS, Polygon.io |
| Feb 7 | Quantum-Neuromorphic Portfolio Pipeline — Four-tier workflow: PQFM quantum feature encoding (16-qubit Heisenberg), Akida regime classification, LLM risk narratives, z/OS COBOL settlement ▸ architecture | QPU (Heron R3), NPU (AKD1000), NVIDIA GPU (vLLM), z/OS, Symphony, IBM Cloud, GPFS |
| Feb 3 | Akida Market Regime Classifier — Real-time market regime classification: 93.47% accuracy, 622μs latency, 30mW on AKD1000 | NPU (AKD1000), Intel N100, Symphony, GPFS |
| Jan 20 | Symphony Mainframe: Conversational z/OS — Natural language interface for COBOL actuarial on Wazi aaS | z/OS (Wazi aaS), Symphony, IBM Cloud |
| Jan 17 | Neuromorphic Symphony: GPU HBM as Storage Tier — Spike-driven data lifecycle with GPFS + DMAPI + Norse LIF neurons | NVIDIA GPU, Symphony, GPFS |
| Jan 12 | Quantum-Classical Integration Suite — Four Qiskit applications on GPU simulation and IBM Quantum Heron R3; 2,560 hyperparameter combinations | QPU (Heron R3), NVIDIA GPU (6x A100), Qiskit, Symphony, IBM Cloud, GPFS |
| Jan 12 | KNN Semantic Router iPhone App Video Demo — Live iPhone/Android app; queries classified and routed across Granite model tiers with ELIM metrics ▶ video | NVIDIA GPU (vLLM), Symphony, GPFS |
| Jan 7 | PowerVS + Symphony Actuarial — Natural language interface for COBOL actuarial programs on IBM PowerVS; no COBOL rewrite required | IBM Power (PowerVS), Symphony, IBM Cloud |
| Jan 6 | Semantic Router / LLM Query Routing — KNN semantic classification routing queries to Granite model tiers for 30-50% cost reduction | NVIDIA GPU (vLLM), Symphony, GPFS |
| Dec 29 | Palantir + Symphony: Cognitive Infrastructure — Ontology Intelligence discovering 1,804 entities and 2,690 relationships from financial services data | Symphony, GPFS, Palantir Foundry, Granite LLM |
I work at the intersection of high-performance computing, AI infrastructure, and the data platforms that hold them together. Most of my career has been spent building and deploying these systems for organizations where downtime or bad answers aren’t an option. That includes financial services, government, defense, healthcare, and research.
I’m a Field CTO at IBM, focused on the HPC Cloud portfolio, which includes Spectrum Symphony, Storage Scale, and LSF. Before that, I spent over a decade in consulting engagements across the same stack. That work covered petabyte-scale parallel file systems, real-time workload orchestration, and the infrastructure underneath large-scale AI. Before IBM, I managed HPC biocomputing infrastructure at TGen, ran a specialty coffee company, and worked in storage virtualization and disaster recovery.
Lately, most of my independent work has been exploring what happens when neuromorphic hardware, large language models, and distributed orchestration frameworks are combined in ways their designers didn’t anticipate. The articles on this site come from that exploration.
I hold an MBA and a Master of Accounting in Finance from Keller Graduate School, an M.A. in Theology from Fuller Theological Seminary, and an M.A. in Global Technology and Development from Arizona State University, where I’m currently a Ph.D. candidate in Innovation in Global Development. My dissertation research focuses on distributed coordination architectures.
