Research Interests
I am a PhD student at Southern Methodist University specializing in world models grounded in physics with applications in robotics. My primary research focuses on making world models more robust and scalable for real-world, continuous control tasks.
Beyond this core focus, I actively explore several parallel research areas:
- Self-supervised learning
- Graph representation learning for quantum chemistry
- Explainable AI
- Biometrics & face recognition, specifically regarding bias and error analysis
Publications
- Harper, C., Laird, E., et al. (2026). Differentiable Resizing: Resolution Layers. ICASSP 2026.
- Laird, E., Clark, C. (2026). On Memory: A comparison of memory mechanisms in world models. World Model Workshop 2026. arXiv:2512.06983
- Laird, E., Thornton, M.A. (2025). Generative Flow Networks with Parameterized Quantum Circuits. IEEE 18th Dallas Circuits and Systems Conference (DCAS). PDF
- Madushanka, A., Laird, E., et al. (2024). SmartCADD: AI-QM Empowered Drug Discovery Platform with Explainability. Journal of Chemical Information Modeling (JCIM). PDF
- Nzalasse, K., Rishav, R, Laird, E., et al. (2024). SIG: A Synthetic Identity Generation Pipeline for Generating Evaluation Datasets for Face Recognition. ICPR FAIRBio Workshop. arXiv:2409.08345
- Laird, E., et al. (2024). Message-Passing Joint Embedding Predictive Architectures. (Under Review)
- Laird, E., et al. (2023). XInsight: Revealing Model Insights for GNNs with Flow-Based Explanations. xAI 2023. arXiv:2306.04791
- Howard, J.J., Laird, E.J., et al. (2022). Evaluating Proposed Fairness Models for Face Recognition Algorithms. ICPR 2022. arXiv:2203.05051
- Howard, J.J., Laird, E.J., Sirotin, Y.B. (2022). Disparate impact in facial recognition stems from the broad homogeneity effect: A case study and method to resolve. ICPR 2022. PDF
Education
Southern Methodist University
PhD in Computer Science | 2023 — 2026 (Expected)
- Graduate Research Fellow: O'Donnell Data Science and Research Computing Institute
- Advisor: Dr. Corey Clark
- Dissertation: "Robust and Scalable World Models grounded in Physics"
University of Cambridge (St. John's College)
Visiting Researcher | Jan 2025 — Mar 2025
- Focus: Graph-based World Models with Dr. Matthias Doerrzapf
Southern Methodist University
MS in Computer Science | 2021 — 2023
- Track: Biometrics & Data Science
BS in Computer Science | 2017 — 2021
- Track: Machine Learning & AI
- Honors: Departmental Distinction Award
Professional Experience
Worlds
Part-time Machine Learning Engineer | Dallas, TX | Aug 2025 — Present
- Focused on discovering, tracking, and modeling behavior from live camera feeds.
- Designed a tool to build interaction graphs automatically from a camera feed
- Tracked object behavior through hidden Markov models and neural ODEs.
Machine Learning Research Intern | Dallas, TX | May 2025 — Sep 2025
- Designed and implemented a custom behavior tracking model from live airport/facility feeds for autonomous behavior tracking analytics.
O'Donnell Data Science & Research Computing Institute
PhD Student & Graduate Research Fellow | Dallas, TX | 2023 — Present
- Developing novel graph-based self-supervised learning methodologies using PyTorch Geometric (PyG).
- Designing SmartCADD, an open-source virtual drug screening platform combining AI-based filtering with Quantum Mechanical methods.
- Training equivariant GNNs to filter chemical compounds by quantum properties.
ISABEL Lab @ SMU
Design & Scientific Lead | Dallas, TX | 2023 — Present
- Leading the Synthetic Identity Generation (SIG) pipeline for creating face recognition evaluation datasets (published in ICPR 2024).
- Training distributed ResNet-based face recognition models over Slurm clusters.
- Designing contrastive loss functions to reduce demographic bias in embedding spaces.
Maryland Test Facility (SAIC)
Data Scientist | 2020 — 2023
- First author on two publications proposing the GARBE metric for biometric equitability, now included in ISO/IEC 19795-10:2024 standards.
- Designed GoLang/Python pipelines for processing live biometric data on Kubernetes.
- Operated biometric rallies with 500-600 human subjects to study bias in commercial systems.
Amherst InsightLabs
Intern | Austin, TX Area | June 2018 — Aug 2018
- Built C# applications to download, format, and write raw datasets to SQL Server for housing market analysis.
- Authored technical documentation for data table schemas.
- Gained hands-on experience developing internal software applications.
Teaching Experience
Southern Methodist University
Undergraduate Teaching Assistant | 2018 — 2020
- Facilitated Data Structures lab sessions and help desks.
- Taught C++ programming principles, including memory management and File I/O.
- Mentored students on project implementation strategies and debugging.
C++ Teaching Assistant (Study Abroad) | Weimar, Germany | May 2018 — June 2018
- Assisted in teaching C++ programming for the SMU study abroad program.
Awards
- Research Fellow: O'Donnell Data Science Institute (2024)
- Dean's Award: Research & Innovation Week (2024)
- Departmental Award: Computer Science (2021)
- Winner: National Academy of Sciences Idea Competition (2020)