Education
Columbia University
- MS in Applied Mathematics (Computer Science Concentration) — In Progress
- Research Focus: Neural Stability, Evolutionary Intelligence, and Homeostatic Regulation.
- Evolutionary Biology Foundation
- Bachelor’s Thesis: "Genetics and the Consumer" — An investigation into the ethical and regulatory landscape of consumer genetic data, establishing the foundational principles of data sovereignty and DNA as personal property.
Experience
NEnterprise AI | Lead Researcher & System Architect
- Designed the NEnterprise Forensic Suite, an 8-module auditing ecosystem built on computational neuroscience principles.
- Engineered real-time model veto protocols utilizing Leaky Integrate-and-Fire (LIF) logic to prevent "neural over-excitation" in autonomous agents.
- Developed cryptographic audit trails and "Integrated Variance" checks to ensure sovereign data provenance.
Technical Skills
- Languages & Frameworks: Python, PyTorch, TensorFlow, Cryptographic Hashing.
- Quantitative Specializations:
- Forensic Auditing: Utilizing Kullback-Leibler (KL) Divergence to measure algorithmic drift from sovereign baselines.
- Neural Topology: Calculating clustering coefficients to audit the "Structure to Function" integrity of neural networks.
- Stochastic Modeling: Implementing Bayesian Inference and Markov Decision Processes for rational agent decision-making.
- Regulatory Compliance: Expertise in the EU AI Act, NIST frameworks, and emerging Data Sovereignty laws.
Key Research Projects
The NEnterprise Forensic Suite: From Biological to Neural DNA
- Applied Principal Component Analysis (PCA) to neural data matrices to reduce dimensionality and track evolutionary trajectories in low-dimensional manifolds.
- Implemented Shannon Entropy as a metric for quantifying information integrity within proprietary neural codes.