SENIOR APPLIED SCIENTIST · DANDY
I work on multimodal generative models for the 3D design of bespoke prosthetics at Dandy. These models require precision at the scale of tens of microns, and feed directly into complex manufacturing lines with little or no human intervention. Previously, I led applied machine learning work at Celonis and held research roles at Microsoft Research, J.P. Morgan, and Spotify.
01 / SELECTED WORK
Selected problems, approaches, and outcomes from my work in applied machine learning.
Dandy / Senior Applied Scientist
Building multimodal models that combine 2D and 3D information for bespoke dental prosthetics. I developed diffusion-model sampling and optimization pipelines that moved a prosthetic design workflow from 0% to 80% automation, and trained point-cloud transformers to identify anatomical structures in jaw scans.
Celonis / Senior Applied Scientist
I led technical teams bringing large language models into process mining. The work ranged from research on tokenizers for process data to enterprise agentic applications designed for high concurrency and global deployment.
Related publicationsEARLIER EXPERIENCE
Researched neural and graph-based methods for fileless attack detection, including a weakly supervised model trained on billions of shell commands.
Research InternDeveloped computational methods for stochastic differential equations and options pricing, improving the accuracy and efficiency of long-term forecasts.
Quantitative Research Summer AssociateBuilt a podcast recommendation approach based on sequential listening behavior, improving accuracy by up to 75% over naïve approaches.
Research InternNew York University / Ph.D. in Computer Science
My doctoral work, advised by Andrew Gordon Wilson, studied how to give Gaussian processes and neural networks useful structure: uncertainty over kernels, learned invariances, and more diverse model ensembles. Those ideas became papers at NeurIPS and ICML and still shape how I approach applied research.
02 / PUBLICATIONS
Work from my Ph.D. and industry research spans process intelligence, uncertainty, forecasting, and the structure of deep learning models.
Browse publications Google Scholar03 / ABOUT
I earned my Ph.D. in computer science at NYU and a B.S. and M.S. in applied mathematics at the University of Colorado. I’m drawn to problems where strong research has to survive contact with complex data and real world constraints.
Outside work, I enjoy reading, coffee, weightlifting, and running. I’ve also completed two 90-mile endurance canoe races.
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