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

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Clinical AI
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Drug Discovery
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Epidemiology

Research Projects

Improving protein optimization with smoothed fitness landscapes
2024
Deep Confident Steps to New Pockets: Strategies for Docking Generalization
2024
Machine learning for antimicrobial peptide identification and design
2024
Integrating Technology into Undergraduate Medical Education: Can Affective Computing Help Teach Empathy?
2024
Adaptive Optimization for Prediction with Missing Data
2024
Probing the Limits and Capabilities of Diffusion Models for the Anatomic Editing of Digital Twins
2023
Wearable Technology in Clinical Practice for Depressive Disorder
2023
Discovery of a structural class of antibiotics with explainable deep learning
2023
Particle Guidance: Non-I.I.D. diverse sampling with diffusion models
2024
Improving influenza A vaccine strain selection through deep evolutionary models
2023
Effective Human-AI Teams via Learned Natural Language Rules and Onboarding
2023
A Deep Dive into Single-Cell RNA Sequencing Foundation Models
2023
Taking Off with AI: Lessons from Aviation for Healthcare
2023
Making the End-User a Priority in Benchmarking: OrionBench for Unsupervised Time Series Anomaly Detection
2023
Annotating metabolite mass spectra with domain-inspired chemical formula transformers
2023
Artificial intelligence for science in quantum, atomistic, and continuum systems
2023
De novo design of protein structure and function with RFdiffusion
2023
S(E3) diffusion model with application to protein backbone generation
2023
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