Irv Lustig
Optimization Principal
Miami, Florida, United States
Summary
🤩
Rockstar🎓
Top SchoolIrv Lustig is an Optimization Principal based in Miami with over 30 years of experience applying mathematical optimization, AI, and advanced analytics to commercial and research problems. He leads Princeton Consultants’ Optimization Center of Excellence and has a proven track record building optimization-driven marketing and sales practices for clients. Earlier roles at ILOG and IBM encompassed product leadership, worldwide sales engineering, and R&D where he developed core CPLEX algorithms, parallel infrastructure, and submitted multiple patent inventions. A PhD in Operations Research from Stanford, he blends deep numerical optimization expertise with practical deployment of analytics for business decision-making. Beyond consulting, he contributes to open-source Python tooling—improving pandas I/O, rounding behavior, and type stubs—demonstrating commitment to robust data tooling and type safety. He’s notable for bridging low-level solver development with commercial strategy, turning complex algorithms into production impact.
10 years of coding experience
25 years of employment as a software developer
Master of Science (M.Sc.), Applied Mathematics, Master of Science (M.Sc.), Applied Mathematics at Brown UniversityPhD, Operations Research, PhD, Operations Research at Stanford University
Github Skills (10)
data-manipulation10
pandas10
typehinting10
debug10
type-checking10
python10
testing10
data-science9
data-analysis9
pytest7
Programming languages (12)
Github contributions (5)
pandas-dev/pandas-stubs
Apr 2022 - Jan 2023
Public type stubs for pandas
Role in this project:
Backend Developer & Type Annotator
Backend Developer & Type AnnotatorContributions:1720 reviews, 127 commits, 615 PRs in 9 months
Contributions summary:Irv primarily contributed to the project by copying type stubs from the Microsoft project and adapting them for the pandas-stubs repository. These commits focused on enhancing type safety by adding and improving type annotations for various pandas modules, including `core/dtypes`, `core/frame`, and `core/series`. The user also added unit tests related to these additions. The majority of the work involved adding and modifying `.pyi` files, which are crucial for providing type hints.
pythontype-stubspandasstubs
pandas-dev/pandas
Oct 2015 - Dec 2022
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Role in this project:Back-end Developer & QA Engineer / Test Automation Engineer
Back-end Developer & QA Engineer / Test Automation EngineerContributions:677 reviews, 79 commits, 120 PRs in 7 years 3 months
Contributions summary:Irv contributed to the pandas library by fixing bugs related to the Excel I/O functionality, specifically addressing issues with multi-index columns and multi-index dates. Their work involved modifying code in `pandas/io/tests/test_excel.py`, `pandas/io/excel.py`, `pandas/core/format.py`, and `pandas/io/parsers.py`. Additionally, they implemented functionality for rounding operations in Series and DataFrames and implemented tests to validate correct behavior. These commits demonstrate a focus on improving data manipulation and I/O capabilities.
pythondatalabeled-datamanipulationdataframes
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