About

I am a computational biophysicist and machine learning researcher with over 20 years of experience at the intersection of AI, computational methods, structural biology, and autonomous experimentation. I am currently a Staff Scientist at Lawrence Berkeley National Laboratory, where I lead ML and computational programs in life and imaging sciences.

My work focuses on developing accountable and reliable AI systems for scientific applications, with particular emphasis on uncertainty quantification, conformal prediction, and adaptive control for experimental facilities. I am passionate about creating AI systems that scientists can trust to make critical decisions in high-stakes experimental environments.

Current Research Focus

I lead Activity 3 of the LAMBDA project, developing federated AI-ready data infrastructure across DOE facilities. I also work on foundation models for scientific imaging through the SYNAPS-I (reSIFT) project funded by NIH.

My methodological research centers on:

• Conformal Prediction: Developing Small Sample Beta Correction (SSBC) for tight PAC guarantees in data-limited settings
• Uncertainty Quantification: Operational rate estimation for accountable automation
• Autonomous Experimentation: Adaptive data acquisition achieving 20-100× efficiency gains

Key Innovations

Small Sample Beta Correction (SSBC): A novel approach to conformal prediction that provides tight PAC guarantees even in small-sample regimes, enabling accountable automation in scientific settings where data is expensive or limited. arXiv:2509.15349

Conformalized Quantile Regression: Framework for autonomous experiments combining quantile-based predictive control with conformal guarantees, with applications in hyperspectral imaging and mass spectrometry. arXiv:2505.08176

Research Domains

• Conformal Prediction & Quantile Regression
• Uncertainty Quantification & Model Evaluation
• Deep Learning for Scientific Imaging
• Autonomous Experimentation & Adaptive Control
• Structural Biology & Crystallography
• Synchrotron & Free Electron Laser Science
• High-Performance & Exascale Computing

Recent Highlights

• Director’s Award for Exceptional Achievement in Technology Transfer (2021)
• Principal Investigator on NIH and DOE AI/ML projects (CAMERA, EcoTwins, ML-Exchange, Autonomous IR Spectroscopy)
• Participant in Department of Homeland Security Fentanyl Taskforce workshop
• Chair, Laboratory Conflict of Interest Advisory Committee
• Member, EMSL STAC, EWALD Advisory, Promotions Committee

Background

PhD, Chemistry - University of Amsterdam, The Netherlands (1999-2003)
Computational & Theoretical Crystallography at EMBL Hamburg

MSc, Physical Chemistry & Crystallography - University of Amsterdam (1995-1999)