Curriculum Vitae
Senior AI Research Engineer & Scientist
Professional Experience
Senior AI Research Engineer
Leading research in mechanist interpretability and circuit representation inside deep transformer networks. Designed alignment guardrails for reasoning agents, reducing hallucination rates by 24%. Co-authored patent-pending safety evaluation methods for LLM alignment.
Machine Learning Engineer
Optimized training pipelines for custom 7B-70B parameter foundational models using PyTorch and Megatron-LM. Scaled training runs across 512+ GPUs. Integrated retrieval-augmented generation (RAG) frameworks inside enterprise reasoning pipelines.
Education
M.S. in Computer Science (Artificial Intelligence)
Thesis: "Information Bottleneck in Deep Autoencoders and Cognitive Mapping." Advisor: Dr. Raymond Vance. Graduate Teaching Assistant for Machine Learning and Complex Networks.
B.S. in Computer Science
Summa Cum Laude. Focused on Algorithms, Computational Math, and Discrete Structures. Received the Outstanding Graduate Award.
Selected Publications
Probing the Latent Geometry of Sparse Autoencoders
Investigates the structural topology of neural activations using dictionary learning techniques, showing that sparse autoencoder features reside in distinct low-dimensional manifolds.
Self-Reflective Loops in Reasoning Agents
Presents a framework for reinforcement learning from feedback via closed-loop self-critique networks, establishing convergence bounds on text generation policies.