Connor Faulkner

Akamai

Akamai threat-research writing on USPS-targeted phishing infrastructure and the scale of malicious traffic reaching it.

Akamai

A coauthored Akamai investigation into a hospitality-focused phishing campaign, with emphasis on DNS analysis and its broader global impact.

Akamai

Akamai security research on DGA families that use dynamic seeds, focused on how that behavior appears in DNS traffic and why it matters for detection.

An XGBoost classifier trained on 3,033 historical signal outcomes that doubles win rate in a live crypto trading system — from 24% to ~50% — by scoring each signal's confidence before execution. Deployed in dry-run with three parallel strategies and a delta-neutral carry layer.

Testing whether structures from physics — thermodynamics, renormalization group, lattice theory, and mean-field dynamics — can guide LLM compression. Five research directions validated on GPT-2 124M: entropy-based quantization (2.6× better than uniform), RG-guided pruning, lattice attention with a phase transition, GPTQ interaction analysis, and metastable cluster verification.

Seven anomaly detectors — from Isolation Forest to a conditional normalizing flow — running on public SDSS DR18 stellar spectra. Includes a physics-motivated PBH candidate screening pipeline, semi-synthetic evaluation harness, and a Streamlit dashboard. Scales to 50K+ spectra.

26 experiments compressing GPT-2 with physics-motivated k-means codebook quantization. Best result: PPL=84.2 at 0.836 bits per weight — 38× compression vs FP32. Null results triangulate the GPTQ design from first principles.

A publication-grade Monte Carlo simulation engine for classical spin models, achieving 0.01% accuracy on the 3D critical temperature. Supports three universality classes, GPU acceleration via CUDA, and finite-size scaling analysis — targeting Physical Review E.

Analysis of genetic substructure across global populations using genome-wide SNPs and principal component analysis on the 1000 Genomes Project dataset.