Engineering the
Silicon Citadel.
Building Invisible Intelligence. Enforcing Absolute Privacy.
Liberating Physicians from the Technical Burden.
Modern First Principles Podcast
Conversations with innovators who reshape their fields through deliberate, first-principles thinking across technology, society, entrepreneurship, academia, philosophy, and creativity.
The Sovereign Thesis
The future of healthcare isn't "smarter" software.
It is Invisible Intelligence.
We have turned our healers into data entry clerks. The cognitive load of technical compliance has stolen the physician's attention from the patient. This is a failure of system design.
To build a better future, we must remove this burden. But we cannot ask doctors to trust "the cloud" with their patients' deepest secrets. Trust is a vulnerability.
I build Cryptographic Citadels—fortresses defined by physics, not promises. By isolating intelligence within impenetrable walls, we create a Digital Sanctuary where the machine handles the technical, so the human can handle the decisions.
Absolute Privacy
The CitadelWe reject 'Privacy by Design' policies. We enforce privacy via physics using cryptographic isolation. Data enters a sealed enclave, is processed in complete isolation, and is incinerated upon completion. No traces. No trust required.
Cognitive Liberation
The Invisible ScribeWe eliminate the documentation burden. Notes write themselves. Pre-charting happens before you arrive. Codes suggest themselves from context. Critical reminders surface when something is missed—gentle, adjustable, and easily silenced. When you need to think through a complex case, a reasoning partner is always ready.
Effortless Mastery
Revolutionary, Yet FamiliarThe most advanced technology is invisible. We build with obsessive care so the learning curve vanishes. You don't study - you just use. The interface meets you where you are, and grows with you as you demand more.
Portfolio
Featured Projects
A selection of recent work spanning AI research, data science, and innovative applications at the intersection of technology and human potential.
Computational Cognitive Modeling of Human Emotion
RoBERTa-large fine-tuning on GoEmotions (27 labels) with multi-GPU training and layerwise representation analysis
Fine-grained sentiment/emotion classification on GoEmotions dataset using RoBERTa-large
Inductive-Bias Study: CNN vs FCNN on MNIST (2-D Latent Evolution)
Equal-capacity CNN vs FCNN constrained to 2-D latent with embedding evolution videos showing CNN inductive bias
Didactic study comparing CNN vs FCNN architectures on MNIST with equal capacity (~19k parameters)
Fairness Audit of Jigsaw Toxicity Classifier
BERT/LSTM/GPT-2 models with subgroup AUCs, demographic/error parity, SHAP explainability, and custom SHarP fairness metric
Full pipeline to train toxicity classifiers (BERT/LSTM/GPT-2 variants) on Civil Comments
Code-Based Projects
Technical implementations spanning machine learning, data science, and AI research with real-world applications.
View All Code ProjectsVision Pieces
Thought leadership articles and philosophical explorations on the future of AI, human potential, and first principles thinking.
View All Vision PiecesFilter the Signal
from the Noise.
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