$ ls ~/projects --sort=date

< Projects />

Building the future, one commit at a time. Here are some of my open-source projects and research work.

50 total
STATUS:
ALL ACTIVE WIP COMPLETED ARCHIVED
TYPE:
ALL Research (19) Tools (10) AI/ML (10) Systems (9) Blockchain (2)
// AI/ML
ACTIVE
AI/ML

GoGameExplanation

CoNLL 2026 submission: Evidence-Based Dominance theorem proves evidence verification is theoretically optimal for elimi…

Python KataGo Stockfish DeBERTa-v3 +2
EXPLORE()
// Research
ACTIVE
Research

Interruptr

Multi-agent C/C++ vulnerability detection achieving ~96% detection rate vs Cppcheck 12%, with 95% cost reduction vs GPT…

Python AutoGen LangGraph
EXPLORE()
// AI/ML
ACTIVE
AI/ML

IntegriRef

Targeting JASIST/ACL: The first citation verification system that goes beyond existence checking to full semantic claim…

Python DeBERTa-v3 SciBERT ONNX +2
EXPLORE()
// AI/ML
ACTIVE
AI/ML

RecCache

ML-aware caching for recommendation systems: 45% cache hit rate, 85% latency reduction on hits, and under 3% NDCG degra…

Python PyTorch Redis online K-Means +1
EXPLORE()
// Research
ACTIVE
Research

CrystleLLM

Quotient space reasoning for LLMs: identifies 64-72% semantic redundancy and reduces token usage by 26.8%.

Python vLLM GSM8K MMLU +4
EXPLORE()
// AI/ML
ACTIVE
AI/ML

DeltaCache

KV cache optimization achieving 10-16x faster warm latency vs vLLM, validated across 84 tests on TinyLlama, Mistral-7B,…

Python vLLM PyTorch Prefix Trie +1
EXPLORE()
// Research
ACTIVE
Research

ROA-LLM

A systematic security study formalizing Persistent Semantic Entities (PSEs) as a new attack surface in tool-augmented L…

['Rust (PyO3)' 'Python' '15 LLMs from 7 vendors' 'Factorial Ablation Design' +1
EXPLORE()
// Research
ACTIVE
Research

EdgeCloud-Reasoning

Mechanism-designed belief aggregation for edge AI: VCG-based truthful elicitation achieves lower false negative rates t…

Python Mechanism Design DeepSets Transformer
EXPLORE()
// Research
ACTIVE
Research

EBM-Market

An energy-based / density-based risk modeling framework that challenges the anomaly=risk assumption in ML: GMM density …

['Python' 'scikit-learn (GMM)' 'CatBoost' 'FRED API' +2
EXPLORE()