David Pugh
Instructional Assistant Professor at KAUST (King Abdullah University of Science and Technology)
Thuwal, Makkah Region, Saudi Arabia
Summary
👤
Senior🎓
Top SchoolDavid Pugh is an instructional assistant professor and seasoned research software engineer with 13 years of experience building and teaching applied AI and data science solutions. He directs training programs and has developed comprehensive workshop curricula that span Python tooling, ML/DL with Scikit-Learn and PyTorch, and scaling on HPC using Horovod—bridging reproducible research practices with production-ready workflow. At KAUST he led the SDAIA-KAUST AI Center of Excellence to match institutional problems with KAUST-developed AI solutions and previously delivered models that helped utilities identify anomalous consumption worth millions in recovered revenue. His open-source contributions include substantive quantitative-economics tooling—implementing analytical and calibrated Solow model features in the widely used QuantEcon.py library. Trained as an economist (PhD, Edinburgh) with a BS in mathematics, he combines rigorous modelling instincts with hands-on engineering, often working at the intersection of agent-based economics, scalable data pipelines, and deep learning.
13 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Economics, Doctor of Philosophy (Ph.D.), Economics at The University of EdinburghBS, Mathematics, BS, Mathematics at William & Mary
Stackoverflow
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462kreached
28answers
82questions
intellij-idea
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Github Skills (17)
python10
sympy10
mathematical10
numerical-methods10
scientific-computing10
modeling10
intellij-idea9
data-analysis9
pip6
scalatest6
tensorflow6
google-colaboratory6
openai-gym6
conda6
akka6
Programming languages (14)
Github contributions (5)
QuantEcon/QuantEcon.py
Jul 2014 - Feb 2015
A community based Python library for quantitative economics
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:222 commits, 4 PRs, 81 comments in 7 months
Contributions summary:David has primarily focused on the development of the Solow growth model within the quantecon library. They implemented an initial test suite for the `solow` module, added an analytical solution for the Cobb-Douglas production model, and added a method to compute the linearized solution for the model. They also worked on incorporating features for calibrating the model using data from the Penn World Tables, implementing a maximum likelihood estimation scheme, and implemented plotting methods.
python-librarycommunity-basedpythondata-sciencemachine-learning
kaust-rccl/conda-environment-examples
Mar 2020 - Sep 2021
Contributions:5 commits, 14 pushes, 7 branches in 1 year 6 months
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