research/machine-learning
-
Essay
Verified Inference Between Adversaries Revised from 29 August 2026
An operator can fabricate execution logs and hold approved weights while running something else. VerInf investigates proofs of language-model inference that mutually distrustful parties can verify on their own hardware. This living document explains what the proof certifies, the system I started from, and my work on profiling, prover optimization, and scale-out during the MARS V fellowship.
Comprehensive update on the proof guarantee and current research.
-
Essay
As we approach AGI, the increase in the ability of Artificial Intelligence models to infer a robust specification from a sparse prompt will lead to a devastating trend of homogeneity. We argue that this is the primary concern regarding the interaction of AI and human intelligence, rather than blanket claims that “AI reduces human cognitive ability.”
-
Essay
3D pose-estimation and kinematic-analysis system for neurological-recovery research, developed in Liqi Shu’s laboratory at the Brown University Department of Neurology. Python/TensorFlow inference, MATLAB-based statistical post-processing, Rust backend with HTML/JS frontends. Four externally-funded sub-projects since 2023; clinical-implications manuscript in preparation.
-
Essay
A deep learning model using ICD-10-CM diagnosis codes with a permutation-invariant Deep Sets aggregator improved 30-day unplanned readmission (AUC 0.7496 vs 0.6553 for CCI) and 30-day postdischarge in-hospital mortality (AUC 0.8557 vs 0.7844 for age-adjusted CCI) compared with Charlson and Elixhauser comorbidity-index benchmarks in a national claims database of over 113 million adult hospitalizations.