Bee Rosa Davis

Bee Rosa Davis

Applied mathematician, security engineer, and independent researcher developing geometric frameworks for AI, physics, cybersecurity, and medicine. Overall Mother of the House of Diwa.
MS Digital Forensics — Brown University 27 years aerospace & security engineering IBM X-Force Red · NASA Johnson Space Center #1 Amazon Bestselling Author
ORCID LinkedIn Zenodo Contact
30+
Publications
25
Patents Filed
8
Books Published
27
Years Engineering
Research Program

Theory Without Implementation Is Speculation

My research develops rigorous mathematical frameworks for understanding, predicting, and preventing AI system failures — and then I build them. This work bridges differential geometry, category theory, and machine learning to provide explanatory rather than merely empirical accounts of how transformer architectures reason — and fail.

Every framework I build includes compositional error budgets, auditable failure modes, and explicit validity assumptions. I ship production systems validated against real-world data — from 2.3TB/day telemetry pipelines at NASA to adversarial AI platforms at IBM X-Force Red.

The unifying thread is the Davis Manifold: a Riemannian state space with bounded geodesic-Euclidean distortion that provides reusable blueprints for safety-critical ML. From semantic coherence in transformers to constraint satisfaction on GPUs, from viral surveillance to cancer detection — geometry is the common language.

Career

From Pandora to NASA

Education

Formal Training

Self-taught: differential geometry, spectral theory, category theory, gauge theory

Technical

Tools & Languages

Languages

Python, Rust, C++, SQL, Bash

ML / Scientific

PyTorch (rebuilt from scratch as DavisTensors), NumPy, SciPy, JAX

Infrastructure

Kubernetes, gRPC, AWS, Azure, CUDA

Mathematics

Differential geometry, spectral theory, category theory, gauge theory

Intellectual Property

Patent Portfolio

25 U.S. provisional patent applications filed spanning geometric computation, security, AI, and fundamental physics.

Curvature-Guided Wavefront Execution for GPU-Accelerated Constraint Satisfaction
App. No. 63/977,565
PSYCHOHISTORY: Topological Conflict Prediction via Geopolitical Helicity
App. No. 63/972,955
Curvature-Aware PageRank via Geometric Mixing Time Prediction
App. No. 63/962,557
Curvature-Aware Adaptive Algorithm Selection for SSSP
App. No. 63/962,503
Vulnerability Discovery via Riemannian Manifold Embedding
App. No. 63/950,401
Bidirectional Spectral Methods for Exploitability Assessment
App. No. 63/949,418
Geometric Attack Surface Mapping via Spectral Graph Theory
App. No. 63/949,177
Manifold Native Deep Learning with Geodesic Optimization
App. No. 63/944,885
GEODESIC Data Storage: O(1) Semantic Retrieval
App. No. 63/943,643
GEODESIC Hash Functions: Quantum-Resistant Cryptographic Hashing
App. No. 63/943,640
Modulation of Quantum Vacuum Topology via Non-Abelian Gauge Fields
App. No. 63/933,299
TESSERA: Antimicrobial Resistance Surveillance via Fiber Bundles
App. No. 63/933,236
Geometric Verification via Topological Cache Mapping
App. No. 63/933,103
Fixed-Size Reasoning State via Topological Residue in Neural Networks
App. No. 63/927,445
Effective Context Length via Holonomy Horizons in Transformers
App. No. 63/927,434
Phase Transition Detection & Heat-Kernel Attention Head Scoring
App. No. 63/926,936
Geometrically Stable Generative Reasoning via Residual Adapters
App. No. 63/925,372
Functorial Transformers with Holonomy-Based Training
App. No. 63/924,487
HERALD: High-Resolution Early Recognition of Antigenic Landscape Divergence
App. No. 63/919,595
HELICITY: Topological Risk Detection in Financial Markets
App. No. 63/935,782
Extending Transformer Reasoning Horizons via Curvature-Based Residual Damping
App. No. 63/928,121
Differential Diagnosis & Location-Specific Treatment of Transformer Pathologies
App. No. 63/928,125
Context-Keyed Patch-Twin Discovery with Calibrated PU Learning
App. No. 63/919,584
Multi-Horizon Expert Feedback Integration for Real-Time Decision Systems
App. No. 63/908,646
GEODESIC: Genomic Evolution on Davis-Embedded Surfaces for Cancer Detection
App. No. 63/931,845
Author

Published Books

Geometric Intelligence Series
Hidden Variable
From a childhood IQ diagnosis to NASA and algorithmic justice — a manifesto on finding what systems hide.
Amazon →
Geometric Intelligence Series
The Geometry of Sameness
Proves production ML and Riemannian manifolds tell the same story, yielding error guarantees that survive coordinate changes.
Amazon →
Geometric Intelligence Series
The Geometry of Medicine
Reimagines health as geometric coherence on the Davis Manifold — stability as a path, not the absence of disease.
Amazon →
Geometric Intelligence Series
The Geometry of Fuel
From the Davis Law to topological vacuum rectification — a unified framework connecting inference, physics, and energy itself.
Amazon →
Astralis Series · Science Fiction
Fly Into The Sun
Hard sci-fi exploring consciousness, identity, and the geometry of interstellar travel.
Amazon →
Astralis Series · Science Fiction
A Pale Jewel
The continuation of the Astralis saga — where geometry meets the stars.
Amazon →
Astralis Series · Science Fiction
Murder Me Lovely
A genre-bending thriller woven through the Astralis universe.
Amazon →
Standalone · #1 Amazon Bestseller
Motion to Be Seen
One Black trans woman's fight for algorithmic justice.
Amazon →