Eli Laird

About Me ​

I'm a PhD student at Southern Methodist University specializing in Artificial Intelligence and Machine Learning. My research focuses on physics-grounded world models for robotics and continuous control. I'm fascinated with training neural nets to learn physical principles and dynamics from data alone and deploying them in the real world.

Alongside my core research, I've previously worked on:

• Self-supervised learning on graph-structured data.
• Explainable AI (XAI) for scientific discovery.
• Biometrics, specifically focusing on bias mitigation and synthetic data generation.

Dallas AI Volunteer Program Lead ​

I serve as the Volunteer Program Lead for the Dallas AI community. We aim to provide a hands-on introduction to AI for students and professionals in the Dallas area.

I co-lead the Dallas AI Summer Program, an 8-week bootcamp where participants hear from industry experts and build their own AI-based projects. Since launching in 2024, we have grown to over 150 participants and anticipate hosting 200+ participants in Summer 2026.

Recent Publications & Presentations ​

• 2026:
  • Differentiable Resizing: Resolution Layers - ICASSP 2026
  • On Memory: A comparison of memory mechanisms in world models - World Model Workshop 2026
• 2025:
  • Generative Flow Networks with Parameterized Quantum Circuits - IEEE 18th Dallas Circuits and Systems Conference
• 2024:
  • SmartCADD: AI-QM empowered drug discovery platform - Journal of Chemical Information and Modeling
  • SIG: A Synthetic Identity Generation Pipeline - ICPR Workshop on Fairness in Biometrics
• 2023:
  • XInsight: Revealing model insights for GNNs - World Conference on Explainable Artificial Intelligence (XAI2023)
• 2022:
  • Evaluating proposed fairness models for face recognition - ICPR Workshop on Fairness in Biometrics
  • Disparate impact in facial recognition stems from the broad homogeneity effect: A case study and method to resolve - ICPR Workshop on Fairness in Biometrics