Resume

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Experience

Exactrics, Inc. • Founder & CTO • Jul 2018 — Dec 2019

Exactrics lets you scan clothes with your phone, then search, filter, and compare by fit while shopping online

• Built a pipeline for converting sets of smartphone photos into millimeter-precision clothing scans
• Built custom fit-search, look-search, and fit-comparison engines for use with our scan data
• Built and maintained our backend server and cloud deployment infrastructure
• Collaborated on the frontend, including development of client SDKs and custom data visualizations

Palantir Technologies • Member of the Technical Staff • Oct 2015 — Feb 2018

• Adapted modern math, stats, and CS techniques to build solutions for Palantir’s most critical customers and product teams. Selected projects include:

  • A personalized document feed used by intelligence analysts to surface urgent new reports
  • A viewership model used by a TV network to simulate and optimize promotional campaigns
  • A customer churn model used by a major payment processor to prioritize CRM efforts

Schlumberger • Software Engineering Intern • Jun 2015 — Oct 2015

• Developed algorithms to leverage autocorrelations in time-series data for predictive maintenance
• Created a time-series-oriented data visualization library for internal use
• Configured and documented a Spark cluster for use by Schlumberger’s various data analytics teams

Education

• Stanford University • PhD, Mathematics • MS, Statistics • 2012 — 2017

  • Thesis: Covariance estimation and graphical models for infinite collections of random variables
• Cambridge University • MASt, Mathematics • Churchill Scholar • 2011 — 2012
• University of Michigan — Ann Arbor • BS, Mathematics • 2007 — 2011

Selected Projects

Clothing Fit Scan Pipeline (Exactrics)

• Reconstruct multiple surface views with traditional photogrammetry techniques
• Use output masks from CV models to stitch reconstructions into item surface:
• Use custom U-Net to segment clothing from background in each view
• Use a Siamese CNN to identify surface correspondences
• Compute geodesic-based vectors for fit-based search and recommendation

Intelligence Document Recommendation Engine (Palantir)

• Vectorized documents using various domain-specific features:

  • Custom word vectors built from domain corpus
  • Sparse named entity features (using domain-specific NER refinements)
  • Geographic features from a hidden layer of an auxiliary network with lat/lon inputs
• Combined document vectors with user interaction data to build user vectors
• Recommended documents by predicting interaction for (user, document) pairs

Skills

Machine Learning and Data Science

• Have deployed models in numerous domains:

  • TV advertising, drug discovery, fraud detection, remote sensing, O&G predictive maintenance, etc.
• Experienced with various forms of unstructured data: images, audio, time-series, text, etc.
• Experienced writing data processing pipelines of various complexities and sizes (up to terabyte-scale)
• Experienced with out-of-core techniques for “big” data, and optimal inference techniques for “small” data

Computer Vision and Augmented Reality

• Have used CNNs, U-Nets, and custom neural nets to automate various image-processing tasks
• Extensive experience using scikit-image and OpenCV for 2D image pre-processing and manipulation
• Have used OpenCV, Open3D, AliceVision, CGAL, etc., to solve various 3D mesh geometry problems
• Experienced working with raw RGB-D data from Intel RealSense cameras and dual-camera phones
• Understand the capabilities and limitations of the high-level mobile AR toolkits (ARKit and ARCore)

High-Performance Python

• Deeply familiar with scientific python, including numpy, scipy, matplotlib, pandas, scikit-learn, etc.
• Experienced using Cython and C++/PyBind11 to write various high-performance extensions
• Experienced orchestrating streaming processing jobs on non-server nodes with celery
• Experienced using Apache Spark to perform large-scale analytics jobs on a dedicated cluster

Web APIs, Frontend, and DevOps

• Experienced designing, developing, and deploying APIs for web and mobile front-ends
• Extensive experience with python’s ASGI server ecosystem, including contributions to pydantic, fastapi, and starlette
• Experienced with frontend frameworks: React and Vue on the web; UIKit and SwiftUI on iOS
• Familiar with typical infrastructure requirements and security concerns for public-facing web services
• Experienced using Docker to develop and deploy containerized web services to multiple cloud providers

Agile Development

• At Palantir, used scrum to establish a reputation of consistently delivering high-quality results on time
• Understand the importance of communication; high-frequency iteration with stakeholders is a top priority
• Methodical about formulating, testing, and confirming/rejecting business hypotheses

Articles and Publications

• Machine Learning

  • Algorithmic Trading of Futures via Machine Learning (Stanford CS229 Project)

• Math

  • Graphical Markov Models for Infinitely Many Variables
  • 5 other mathematics papers

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davwmont@gmail.com • +1 (650) 842 0413
928 Mouton Cir, East Palo Alto, CA 94303

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