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Our research focuses on creating and commercializing high-precision, affordable and scalable machine learning technologies and solutions across two key areas.

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Clinical AI
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Drug Discovery

Research Projects

Unified Brain Surface and Volume Registration
2026
CardioComposer: Leveraging Differentiable Geometry for Compositional Control of Anatomical Diffusion Models
2026
A Genetic Algorithm for Navigating Synthesizable Molecular Spaces
2026
When Style Breaks Safety: Defending LLMs Against Superficial Style Alignment
2026
Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification
2026
WRING Out The Bias: A Rotation-Based Alternative To Projection Debiasing
2026
SPG: Sandwiched Policy Gradient for Masked Diffusion Language Models
2026
GLASS Flows: Efficient Inference for Reward Alignment of Flow and Diffusion Models
2026
Forecasting left ventricular systolic dysfunction in heart failure with artificial intelligence
2026
Physical restraint use in a United States intensive care unit—a retrospective cross sectional, single center cohort study from 2008 to 2022
2026
Patient Outcome Predictions Improve Operations at Hartford HealthCare
2025
Personalizing prostate cancer education for patients using an EHR-Integrated LLM agent
2025
Autonomous discovery of functional random heteropolymer blends through evolutionary formulation optimization
2025
Learning the Wrong Lessons: Syntactic-Domain Spurious Correlations in Language Models
2025
Atom-level enzyme active site scaffolding using RFdiffusion2
2025
Opportunistic screening of type 2 diabetes with deep metric learning using electronic health records
2025
Barriers to translating continuous monitoring technologies for preventative medicine
2025
Aggregation Hides Out-of-Distribution Generalization Failures from Spurious Correlations
2025
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