Technical & Research Consulting
I help researchers and technical teams turn complex scientific questions into structured, actionable projects.
How I can help
AI/ML for experimental research
Choosing appropriate modeling approaches for small, noisy, or heterogeneous experimental datasets.
Experimental data strategy
Structuring data, defining meaningful targets, and identifying what additional experiments would be most informative.
Research problem formulation
Turning broad technical questions into tractable research problems, hypotheses, and decision frameworks.
AI-enabled experimental workflows
Identifying where machine learning, active learning, or automation can meaningfully improve an experimental workflow.
Technical landscape research
Synthesizing scientific literature, technologies, and emerging approaches to support research or strategic decisions.
Example projects
- Evaluate whether machine learning is appropriate for an experimental dataset
- Design an active-learning strategy for selecting the next experiments
- Review and improve an experimental data pipeline
- Structure an AI-for-science research project
- Map technologies and research trends in an emerging scientific field
- Translate experimental challenges into computational or data-driven workflows
Areas I know particularly well
Materials science, semiconductor materials, energy materials, experimental science, machine learning for scientific data, Bayesian modeling, uncertainty quantification, active learning, and autonomous experimentation.
Interested in working together?
If you have a technical problem or research project you would like to discuss, feel free to reach out.