Caleb Bugg

About Me

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Caleb Bugg

Operations Analyst at ROSE.
Researcher in stochastic optimization, large-scale models, and policy recommendations.

About Me #

Hello! My work seeks to discover and implement quantitative methods with social, civic, and government applications. I aim to prescribe simple, actionable solutions at scale.

Publications

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2021 — C. Bugg & A. Aswani, Logarithmic sample bounds for Sample Average Approximation with capacity- or budget-constraints, Operations Research Letters, 49(2):231–238. https://doi.org/10.1016/j.orl.2021.01.007 oai_citation:2‡ScienceDirect
2022 — C. X. Bugg, C. Chen & A. Aswani, Nonnegative Tensor Completion via Integer Optimization, in Advances in Neural Information Processing Systems 35 (NeurIPS 2022). https://proceedings.neurips.cc/paper/2022/hash/40cf260d0c2df13e4286cc0fc0972618‑Abstract‑Conference.html oai_citation:3‡NeurIPS Proceedings

Contact

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Get in Touch #

ROSE & ROBE email:
cbugg@breastfeedingrose.org

Georgia State University email:
cbugg@gsu.edu

LinkedIn:
Caleb Xavier Bugg

Projects

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C. Bugg, Zezhi Zhang, Integer Programming Approaches to the Quadratic Knapsack Problem, Spr 2020, UC Berkeley.\

C. Bugg, Pelagie Elimbi Moudio, Uses and Extensions of the Ramsey-Cass-Koopmans Model, Spring 2018, UC Berkeley.\

C. Bugg, An Engineering Ethics Portfolio, Spring 2019, UC Berkeley.

Talks

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IEOR Visit Day at UC Berkeley, Policy Implications for Sample Average Approximation, March 2020. \

KPOO interview with DJ Marilynn. February 2020. \

C. Bugg, G. Elvin, Committee Selection with Approval Voting and Hypercubes, Summer 2015 at MSRI, UC Berkeley.

Teaching experience

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I currently serve as a Part-time Instructor of Mathematics at Georgia State University, Decatur Campus. \

I have served as a teaching assistant for the following courses at UC Berkeley:

Teaching Assistant (GSI) #

IEOR 115: Industrial and Commercial Database Systems (Fall 2018-20)
IEOR 265: Learning & Optimization (Spring 2020, 2021)
ENG 120: Engineering Economics (Spring 2019)