Robert Streit Email & Phone Number

Austin, Texas Area

• Examining the design of parallel and distributed, or otherwise scalable, combinatorial optimization methods.
• Contributed first sublinear complexity parallel method for computing optimal basis of a binary matroid.
• Via rapidly mixing Markov chains, solving many problems – submodular minimization, max cut, and uniquecoverage – in parallel and universal manner by using algebraic and geometric representations.
• Constructing distributed algorithms for solving semidefinite programs with complexity varying in sparsity.
• Using the calculus of variations to analyze a user alignment in Bayesian multi-armed bandit recommender systems.

San Francisco, California, United States

• Engineered Python library for data driven optimization like Metropolis-Hastings walks, conjugate gradientdescent, quasi-Newton methods, and geometric methods and validate on real world dynamic pricing data.
• Used contributions to develop risk factor estimation and model calibration program for user pricing ML models.
• Collaborated with ML infrastructure team to standardize optimization in data pipelines across company.
• Evaluated ML models in online stochastic pricing experiments with SQL and contributed sampling bias correction method.

Greater Seattle Area

• Created a robust system for streaming security analyses from unreliable data sources in Elastic stack for evaluation.
• Increased security team’s positive influence by tooling the translation of data-driven security insights into accessible developer facing reports, contextualized by automatically generated recommendations and fixes for.

• Designed deep learning network hardware accelerator using data locality and hardware parallelization.
• Compared approach to more traditional parallel linear algebra processors like systolic arrays.
• Wrote Linux kernel drivers and modified PyTorch tools to use accelerator on Xilinx Zynq SoC running Ubuntu.
• Led senior design team by assigning tasks, tracking milestones, compiling reports, and liaising with professors.

Austin, Texas Area

• Invented new fast automatic synchronization algorithm for parallel computing using incremental computation.
• Researched competing algorithms and improved on their shortcomings.
• Analyzed complexity and proved lower bounds on problem to show algorithm has tight worst case complexity.
• Formalized custom language extending C++ and modified Clang compiler to support new paradigms.
• Supplemented with empirical work, and compiled findings and commentary into undergraduate honors thesis.

Austin, Texas Area

• Developed tool used to visualize and understand decisions made by deep learning neural networks.
• Researched algebraic methods for decomposing AI systems and evaluated their usefulness to company needs.
• Implemented methods such as gradient based class activation mapping and deconvolutional networks.

Austin, Texas Area

• Made debugging & performance test tool interacting with 2000 devices concurrently in a network
• Amended network drivers to support the parallel redundancy protocol in QNX-RTOS

Doctor Of Philosophy - Phd, Electrical And Computer Engineering

Bachelor’S Degree, Biomedical/Medical Engineering

Activities and Societies: IEEE Computer Society, UT ECE Undergraduate Advisory Board, Eta Kappa Nu IEEE Honor Society