Alexander D. Greenhalgh

agreenhalgh3@gatech.edu
ahalgh.github.io
CV PDF
github.com/ahalgh
LinkedIn
Google Scholar

Machine Learning, Representation Learning, and AI for Decision-Making

I am a Ph.D. student in Computational Science and Engineering at Georgia Tech, advised by Dr. Polo Chau. My research focuses on machine learning interpretability, representation learning, and visualization.

I am particularly interested in how large language models and agent-based systems can be analyzed and improved to enhance transparency, robustness, and decision-making under uncertainty.

Education

Aug. 2025 – Present
Ph.D. in Computational Science and Engineering
Georgia Institute of Technology, Atlanta, GA
Advisor: Duen Horng (Polo) Chau
  • Georgia Tech President's Fellowship.
Aug. 2023 – May 2025
M.S. in Computer Science
Georgia Institute of Technology, Atlanta, GA
Machine Learning Concentration • GPA: 4.00/4.00
  • Coursework: Machine Learning, Deep Learning, Graduate Algorithms.
  • Academic Integrity TA: Machine Learning for Trading, Software Development/Architecture Processes.
Aug. 2023 – Dec. 2024
M.Eng. in Industrial Engineering
New Mexico State University, Las Cruces, NM
Department of Industrial Engineering • GPA: 4.00/4.00
  • Coursework: Linear Programming, Stochastic Simulation, Optimization.
  • ORSA Military Applications Course: 14 Week Operations Research Training at Army Logistics University.
Aug. 2019 – May 2023
B.S. in Materials Science and Engineering
The University of Tennessee, Knoxville, TN
Minors: Computer Science and Mathematics • GPA: 3.88/4.00
  • Coursework: Materials, Thermodynamics, Algorithms, Scientific Computing, Machine Learning.
  • Additional: Summa Cum Laude, Distinction in Undergraduate Research, Cook Grand Challenge Honors.

Honors & Awards

August 2025
Presidential PhD Fellowship, Georgia Institute of Technology
April 2025
Civilian Service Commendation Medal, Department of the Army
April 2025
OMSCS Project Showcase Student's Choice Award Winner
May 2023
Undergraduate Researcher of the Year, University of Tennessee
March 2022
Goldwater Scholar, Barry Goldwater Scholarship Foundation
February 2022
ASM International Oak Ridge Chapter Undergraduate Poster Contest Finalist
April 2021
DOD Science, Mathematics, and Research for Transformation (SMART) Scholarship
March 2021
ETI Consortium Undergraduate Fellowship Award, Georgia Institute of Technology

Professional Experience

June 2022 – Aug. 2022; July 2023 – Sept. 2025
Operations Research Analyst
Maneuver Division – The Research and Analysis Center, Army Futures Command
  • Developed operational combat models for simulation in Python with Apache SVN version control in Linux environment.
  • Designed and built a large language model chatbot in Python for tactical Q&A using LangChain for vector embeddings and OpenAI API. Model trained on Army Doctrine Manuals scraped with BeautifulSoup.
  • Performed Design of Experiments to compare the effectiveness of several combat vehicle platforms through combat modeling. Results presented to Army leadership and used to inform Pentagon G-8 billion-dollar yearly acquisition budget.
  • Built interactive visualization dashboards in Bokeh package in Python to convey operational modeling results to Army Senior Leaders.
Oct. 2019 – May 2023
Computational Material Science Researcher
Advisor: Prof. David Keffer and Dr. Dayton Kizzire, UT-MSE
  • Research project #1: Developed method to statistically characterize chemical ordering in Atom Probe Tomography (APT) data sets of high entropy alloys. Created MATLAB program to visualize and quantify atomic ordering via Radial Distribution Function; analyzed APT data from ORNL to display nanoprecipitates in High Entropy Alloys.
  • Research project #2: Classical Molecular Dynamics simulations using LAMMPS on ISAAC HPC cluster to generate thermodynamic, mechanical, and transport properties for Aluminum and aluminum alloy Mg12Al17.
  • Research project #3: Automated interatomic potential property calculations with Python (NumPy, matplotlib, mpi4py) and VASP. Developed novel ML optimization algorithm to parameterize and discover Cerium interatomic potential.
June 2021 – Aug. 2021
DOE Science Undergraduate Laboratory Intern
Advisor: Dr. Yuanpeng Zhang, Oak Ridge National Laboratory
  • Continued development of the ADvanced DIffraction Environment (ADDIE), a GUI integrating the NOMAD Diffractometer into the Mantid framework at the Spallation Neutron Source.
  • Enabled access of raw neutron data to a scientific community of 1,000 yearly experimental SNS users with open-source project.
  • Integrated PyQt GUI data with backend Neutron Diffraction Fourier Transform codes for data reduction.

Projects

2023–2025
Tactical LLM Chatbot for Army Doctrine Q&A
  • Retrieval-augmented generation over Army Doctrine Manuals
  • Vector embeddings with LangChain, inference via OpenAI API
Spring 2023
High-Entropy Alloy Strength Prediction
  • XGBoost model for joint optimization of yield strength and ductility. Testing accuracy of 90.1%.
  • Trained on High-Entropy Alloy Database extracted from experimental literature.
Fall 2023
Neural Machine Translation: English to German
  • Implementation of LSTM, Seq2Seq, and Transformer Architectures with PyTorch for English to German Translation Task.
  • Transformer Attention mechanism from Vaswani et al.'s 'Attention Is All You Need'. Trained on dataset of 31,014 sentences with testing perplexity of 4.81.
Spring 2024
Autonomous AI Algorithms
  • A-star, PID control, Particle/Kalman Filters, Simultaneous Localization and Mapping (SLAM).

Training

Fall 2023
Army Logistics University
ORSA Military Applications Course
  • 14 Week Training covering foundations of military operations research.
  • Operational combat modeling, stochastic simulation, data analysis, probability/statistics.

Skills

Languages & Frameworks: Python (PyTorch, NumPy, Pandas, sklearn), C++, R, MATLAB, Linux, Bash, JavaScript, FORTRAN, Git
LAMMPS Classical Molecular Dynamics Software
OVITO Molecular Visualization Software

Publications

Journal Articles

2023
“Modified Embedded Atom Method Interatomic Potential for FCC γ-Cerium”
Kizzire, D.G., Greenhalgh, A.D., Neveau, M.L., Pekol, C.M., Thompson, M.J., Rios, O., Keffer, D.J.
Computational Materials Science, 230, article #112454, 2023, pp. 1–9. doi:10.1016/j.commatsci.2023.112454
2021
“Assessment of Local Observation of Atomic Ordering in Alloys via the Radial Distribution Function: A Computational and Experimental Approach”
Greenhalgh, A.D., Sanjeewa, L.D., Luszczek, P., Maroulas, V., Rios, O., Keffer, D.J.
Frontiers in Materials, December 2021.
2020
“Considerations for in situ, real time measurement of plasma-material interactions using Digital Holographic imaging”
Biewer, T., Smith, C., Gebhart, T., Greenhalgh, A.D., Ren, X., Thomas, C.
Journal of Instrumentation, 15(2), C02017, February 2020.

Conference Papers

2026
“Exploring Transitions of Graduates From an Online Master's in Computer Science Program to Doctoral Programs”
Greenhalgh, A.D., Deng, P., Yu, B., Lytle, N., Joyner, D.A.
Proceedings of the 57th ACM Technical Symposium on Computer Science Education (SIGCSE TS), February 2026, St. Louis, MO, USA. doi:10.1145/3770762.3772654

Presentations

Oral

May 2021
“Local Observation of Atomic ordering in Alloys via the Radial Distribution Function: A Computational and Experimental Approach”
SIAM Conference on Mathematical Aspects of Materials Science – MS 21, Madrid (virtual)
Sanjeewa, L.D., Greenhalgh, A., Rios, O., Luszczek, P., Maroulas, V., Keffer, D.J.
Nov. 2020
“Generating Intermolecular Potentials from Atom Probe Tomography Experiments”
AIChE Annual Meeting, San Francisco, CA
Keffer, D.J., Spannaus, A., Greenhalgh, A., Maroulas, V., Luszczek, P., Liaw, P.K.

Poster

June 2023
“Optimization of Refractory High-Entropy Alloy Strength and Ductility through a Predictive Development Process”
International Conference on High-Entropy Materials, Knoxville, TN
Alex Greenhalgh, Kylie Berry, Makenna Curcuru, Jonathan Landry, Baldur Steingrimsson, Peter Liaw
“Modified embedded atom method atomic potential for pure Cerium to facilitate AlCe characterization”
April 2023
EUReCA Research Poster Contest, Knoxville, TN
February 2023
Center for Materials Processing Student Poster Night, Knoxville, TN
Alex Greenhalgh, Dayton Kizzire, David Keffer
“Assessment of Atomic Ordering in Alloys”
April 2022
ASM International Oak Ridge Chapter Student Poster Night, Knoxville, TN
February 2022
ASM International Oak Ridge Chapter Student Poster Night, Knoxville, TN
Alex Greenhalgh, David Keffer
August 2021
“A New Data Reduction Environment for Neutron Diffraction Data”
ORNL SULI Poster Session, Oak Ridge, TN
Alex Greenhalgh, Yuanpeng Zhang
April 2021
“Energy and Entropy of Defect Formation in Crystalline Solids”
EUReCA Research Poster Contest, Knoxville, TN
Alex Greenhalgh, David Keffer
October 2020
“Material Properties through LAMMPS Molecular Dynamics Simulation”
ASM International Oak Ridge Chapter Student Poster Night, Knoxville, TN
Alex Greenhalgh, David Keffer
April 2020
“Visualization and Metrics of Atomic Ordering”
EUReCA Research Poster Contest, Knoxville, TN
Alex Greenhalgh, David Keffer
August 2019
“Simulation of Surface Damage by Laser Ablation to Material Targets as Proxy for Plasma Exposure Erosion”
ORNL Undergraduate Poster Session, Oak Ridge, TN
Alex Greenhalgh, Theodore Biewer

Built with Jekyll