Dat Nguyen
Post‑doctoral Fellow in Computer Science, Harvard SEAS · Basis Research Institute
Short bio
I am a Joint Postdoctoral Fellow at Harvard’s Programming Languages and Formal Methods groups and the Basis Research Institute.
My research focuses on program synthesis and probabilistic programming, with a track record in graph-based learning for code and documents. I completed my PhD at the University of Melbourne and previously worked at Cinnamon AI Lab on visually rich document information extraction.
At Harvard, I work on proof automation in Lean and causal systems for drug repurposing. At Basis, I contribute to MARA and R-ADA.
Research interests
- Program synthesis and probabilistic programming
- Graph-based learning for code and documents
- Neuro-symbolic systems with LLMs and SMT
- Reliable and explainable ML for software
News
- Awarded Gold Reviewer at ICML’26. Thanks to the area chairs and to the authors whose submissions were a pleasure to read.
- Preprint, follow-up to NeuroSymbolicDG. We re-formulated image classification as spatial predicate induction over learned image primitives! arXiv.
- ExoPredicator learns symbolic state and causal processes (agent actions plus exogenous mechanisms) via variational Bayesian inference with LLM proposals. Accepted at ICLR’26. arXiv, openreview.
- AutumnBench featured on the Basis Research Institute blog.
Technical blogs
- Grammars that generalize. Combining a small DSL with a neural network for domain-invariant bird recognition.
- Bayesian Synthesis. Probabilistic programs for automatic data modeling.
- All posts.
Project demos
| | NeuroSymbolicDG Domain-invariant classifier head for fine-grained bird recognition, via a PCFG over spatial layouts. code · paper · blog · checkpoints |
| VRDSynth (ISSTA '24) Program synthesis for multilingual document information extraction. code · paper |
| | Autumn.cpp (ICML '26) Autumn interpreter in C++. Powers MARA and AutumnBench. Try it live ← code · AutumnBench paper · blog · playground ↓ to spin droplet, click cloud & sun to interact |
| ExoPredicator (ICLR '26) Learning abstract models of dynamic worlds for robot planning. paper · openreview |
| VirDA (TMLR '25) Unsupervised domain adaptation by reusing the backbone with visual reprogramming. code · paper |
| GNNInfer (ICSE '22, arXiv '24) Inferring properties of graph neural networks. paper |
| FFL (ICSME '22) Fine-grained fault localization for student programs. code · paper |
Positions
2025 to present
Joint Post-doctoral Fellow
2021 to 2024
PhD, School of Computing & Information Systems
University of Melbourne · Melbourne Research Scholarship
2016 to 2021
AI Research Engineer
Cinnamon AI Lab
Selected Publications
- arXiv '24Inferring Properties of Graph Neural Networks. .
- ICSME '22FFL: Fine grained Fault Localization for Student Programs via Syntactic and Semantic Reasoning. .
- ICSE '22Toward the Analysis of Graph Neural Networks. .
- ICPR '20End-to-End Hierarchical Relation Extraction for Generic Form Understanding. .
- MAPR '20PCA-based 3D Facial Reenactment From Single Image. .
- BMVC '19End-to-End Information Extraction by Character-Level Embedding and Multi-Stage Attentional UNet. .