Data Science - Dr. Ken Reid

About

I'm Ken Reid — a Senior Data Scientist at Rocket Mortgage with a Ph.D. in Artificial Intelligence from the University of Stirling. My research spans evolutionary computation, optimization, and machine learning, with publications at top venues including GECCO and IEEE SSCI. I design and build data-driven solutions across Python, Java, JavaScript, and more — from automated testing frameworks to large-scale optimization systems.

Research Interests

Data Science Optimization Evolutionary Computation Generative AI Machine Learning Genetic Programming Metaheuristics Deep Learning

Publications

Peer-reviewed research papers and preprints

54 citations

Heuristic hyperparameter optimization of deep learning models for genomic prediction

J Han, C Gondro, K Reid, JP Steibel

G3 11(7), jkab032 — 2021

52 citations

An interdisciplinary outlook on large language models for scientific research

J Boyko, J Cohen, N Fox, MH Veiga, JI Li, J Liu, B Modenesi, AH Rauch, et al.

arXiv preprint arXiv:2311.04929 — 2023

13 citations

Optimizing LLVM Pass Sequences with Shackleton: A Linear Genetic Programming Framework

H Peeler, SS Li, AN Sloss, KN Reid, Y Yuan, W Banzhaf

Google Scholar listing — 2022

13 citations

A hybrid metaheuristic approach to a real world employee scheduling problem

KN Reid, J Li, A Brownlee, M Kern, N Veerapen, J Swan, G Owusu

Proceedings of the Genetic and Evolutionary Computation Conference, 1311-1318 — 2019

9 citations

The Factory Must Grow: Automation in Factorio

KN Reid, I Miralavy, S Kelly, W Banzhaf, C Gondro

GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference — 2021

9 citations

Variable Neighbourhood Search: A Case Study for a Highly-Constrained Workforce Scheduling Problem

KN Reid, J Li, J Swan, A McCormick, G Owusu

IEEE SSCI 2016 — 2016

7 citations

Genetic improvement in the Shackleton framework for optimizing LLVM pass sequences

SS Li, H Peeler, AN Sloss, KN Reid, W Banzhaf

Proceedings of the Genetic and Evolutionary Computation Conference Companion — 2022

2 citations

Shift Scheduling and Employee Rostering: An Evolutionary Ruin & Stochastic Recreate Solution

KN Reid, J Li, N Veerapen, J Swan, A McCormick, M Kern, G Owusu

2018 10th Computer Science and Electronic Engineering (CEEC), 19-23 — 2018

1 citation

Metaheuristics For Solving Real World Employee Rostering and Shift Scheduling Problems

KN Reid

University of Stirling — 2019

BatchPlanet: Batch access and processing of PlanetScope imagery for spatiotemporal analysis in R

Y Song, AR Bevington, KN Reid, J Zhu, Y Liu, K Zhu

The Journal of Open Source Software 11(119):9268 — 2026

Benchmarking of the Shackleton Genetic Programming Framework for LLVM Compiler Optimization

WB Stella Li, Hannah Peeler, Kenneth Reid, Yuan Yuan, Andrew Sloss

Google Scholar listing — 2021

The Factory Must Grow: Automation in Factorio

CG Kenneth N. Reid, Iliya Miralavy, Stephen Kelly, Wolfgang Banzhaf

arXiv preprint version — 2021

View All on Google Scholar →

Doctoral Thesis

Metaheuristics for Solving Real World Employee Rostering and Shift Scheduling Problems

University of Stirling, Division of Computing Science and Mathematics — July 2019
Supervised by Dr Jingpeng Li · Funded by BT and EPSRC DAASE Project

This thesis addresses challenging real-world employee rostering and shift scheduling problems using state-of-the-art metaheuristic techniques. Novel approaches including Variable Neighbourhood Search, Evolutionary Ruin & Stochastic Recreate, and hybrid matheuristic methods combining metaheuristics with Integer Programming were developed and evaluated against real-world data provided by BT. The research demonstrates how computational optimization can solve complex, highly-constrained scheduling problems that arise in large-scale workforce management.

Read Full Thesis (PDF)

Interactive Tools

Try these data-driven web apps — no setup required

🎮 Steam Stats Visualized

Paste your Steam profile and get your gaming life roasted. Gaming personality, head-to-head comparisons, achievement stats, account value estimation, genre breakdown, and downloadable summary cards.

Plotly Steam API Streamlit

Try it → View Source

📚 GoodReads Reading Stats

Upload your GoodReads export and discover your reading personality, genre breakdown, rating analysis, fun page facts, and a quotes collection tool with themed PDF/HTML/Markdown export.

Plotly NLP Streamlit

Try it → View Source

💳 Debt Payoff Simulator

Compare Avalanche vs Snowball debt repayment strategies with interactive charts. Balance transfer analysis, sensitivity modeling, bi-weekly payments, and customizable summary cards.

Plotly Financial Modeling Streamlit

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🔥 Letterboxd Roasted

Upload your Letterboxd data export and get absolutely roasted. Film personality types, data-driven roast commentary, multi-user comparison, contrarian scores, and shareable summary cards.

Plotly TMDb API Streamlit

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Portfolio

Data science & research projects on GitHub

FactorioBeltProblemGECCO

Factorio game interface for optimizing belt balancer layouts using evolutionary computation. Companion code for the GECCO '21 paper.

Python Lua ★ 30

VAE for Molecule Discovery

Variational Autoencoder for drug discovery — generating novel molecular structures using deep generative models.

Jupyter Notebook

CNN X-Ray Classifier

Convolutional Neural Network for pneumonia detection from chest X-ray images — a deep learning tutorial for medical imaging.

Jupyter Notebook

NLP Text Analysis Toolkit

Generalized NLP pipeline — topic modeling, sentiment analysis, and text classification using modern natural language processing techniques.

Jupyter Notebook

Simulated Annealing

Interactive Google Colab demonstration of Simulated Annealing — reconstructing a target string with visualized convergence, temperature decay, and acceptance probability.

Jupyter Notebook

Introductory Data Science

Hands-on machine learning tutorials in Google Colab — covering classification, regression, unsupervised learning, MLPs, CNNs, and RNNs.

Jupyter Notebook

Debt Payoff Simulator

Python simulator for comparing debt payoff strategies — avalanche vs snowball methods with financial data analysis and visualizations.

Jupyter Notebook

Global Temperature Analysis

Data pipeline using R, SQL Server, and Tableau to analyze long-term global temperature trends and climate patterns.

R SQL

View All on GitHub →

Featured Talk

Presented through Michigan State University's BEACON Center for the Study of Evolution in Action. This talk accompanies the paper "The Factory Must Grow: Automation in Factorio" and has been viewed over 21,000 times.