On Lounge since Oct 2026
Andrew Bond
Member #914DeveloperL2Lecturer, Researcher, Computer Engineering Department at San José State University
Philosophy Engineering - Consumer-aware compression - AI Safety - Moral evaluation is not a number. It is a tensor on a stratified manifold.
How karma works. Everyone starts with 5. You get +1 each time another member upvotes one of your posts or comments (your own upvotes don't count), and lose it if they take the upvote back. Post what you're building, answer questions and help other members to earn more.
Achievements
Plugged In ×4Connected sources: GitHub, Hugging Face, LinkedIn, X, website.How: Connected 4 sources (GitHub, LinkedIn, X or a website) in Settings
Plugged In×4Featured
Shipper ×2Projects on your profile.How: Added 5 projects to their profile
Shipper×2
Pinned projects
Atlas AI — self-hosted multi-agent AI research platform: Ego/Superego/Id cognitive stack over a NATS event fabric, verified teaching loop (Primer), thermal-managed compute, NRP cloud bursting
agiai-safetycognitive-architecturehpcmulti-agent-systems
AI-powered WCAG 2.1 AA document accessibility checker and fixer, built on pandoc + Claude — designed for CSU faculty accessibility compliance
accessibilityalt-textdocument-processingpandocwcag
ErisML is a modeling language for governed, foundation-model-enabled agents operating in pervasive computing environments
agentsai-governanceai-safetydecision-makingmodeling-language
Geometric deep learning for content moderation — hyperbolic policy embeddings, manifold decision boundaries, and distributional fairness
content-moderationfairnessgeometric-deep-learninghyperbolic-embeddings
Moral Spectrum Analyzer — measures the moral coverage of AI content-evaluation, moderates where validated, escalates where not, and discovers missing dimensions. GTC 2026 prototype (Pillar A).
ai-ethicscontent-moderationevaluationllmmoral-reasoning
Consumer-aware compression for embedding indexes and LLM KV caches — compress by the metric the downstream consumer actually uses. PCA-Matryoshka + TurboQuant (27x @ 99.8% recall@10), asymmetric K/V, CUDA/Triton kernels, vLLM plugin, replayable CI-gated claims. MIT.
compressionembeddingskv-cachellm
pytorch
Stack
About
SJSU Computer Engineering: CMPE 148, 180b, 272/282 297; SSU Computer Science: CS 115, CS 480, CS 385
Experience
Technical Leader · Cisco Systems
Software Engineer · Cisco Systems
Software Engineer · Fujitsu Network Communications
Systems Engineer · Applied Innovation, Inc
