# Shane Cairns

> Ph.D. researcher in Computer Science focused on representation learning, continual learning, adaptive neural systems, and adversarial ML. First-author publication at IJCNN 2026, with two follow-up manuscripts in submission; experienced in building large-scale PyTorch experiments on GPU/HPC infrastructure. Seeking AI research and engineering roles in defense and AI safety.

- Location: St. Louis, MO
- Email: syre@duck.com
- LinkedIn: https://www.linkedin.com/in/shane-c-b5b948135/
- GitHub: https://github.com/syre-ai
- Website: https://shanecairns.com
- Resume (PDF): https://shanecairns.com/Shane_Cairns_Resume.pdf
- Seeking: AI research and engineering roles in defense and AI safety

## Highlights

- **IJCNN 2026**: First-author publication
- **2 papers**: In submission (ART-VQ, generative)
- **~10x**: Lower reconstruction MSE vs. VQ-VAE
- **DARPA**: Funded computer vision research
- **Kummer Fellow**: Innovation & Entrepreneurship

## Research Interests

- Continual and lifelong learning
- Representation learning (vector-quantized, prototype-based, discrete-continuous latents)
- Adaptive neural systems and Adaptive Resonance Theory (ART)
- Generative modeling on learned discrete representations
- Adversarial robustness of incremental learners
- AI safety and trustworthiness

## Education

### Ph.D., Computer Science
**Missouri University of Science and Technology** | Rolla, MO | Expected Dec 2027 | GPA: 3.75/4.0
Honors: Kummer Innovation & Entrepreneurship Fellow

### B.S., Computer Science
**Missouri University of Science and Technology** | Rolla, MO | Dec 2022 | GPA: 3.7/4.0 (Major)
Honors: Distinguished Scholar Award, Dean's List
- Graduated in 3.5 years

## Research Experience

### Graduate Researcher - Adaptive Resonance Theory & Machine Learning
**Missouri S&T, Computer Science Department** | Rolla, MO | Aug 2023 - Present

#### Adaptive Representation Learning & Generative Modeling
- Developed ART-VQ, a discrete-continuous latent layer replacing VQ-VAE point codebooks with Fuzzy ART hyperboxes to preserve discrete region identity and continuous within-box position; introduced a projection readout that prevents representational collapse, reducing error 35x versus midpoint training.
- Achieved ~10x lower reconstruction MSE than VQ-VAE at matched token count on CIFAR-10 (1.01 vs. 10.55); rate-distortion controls attributed most of the improvement to increased representational rate. Under MNIST class shift, ART-VQ limited forgetting to +0.24 MSE vs. +19.3 for VQ-VAE.
- Built a generative pipeline combining a transformer prior over hyperbox identities with diffusion modeling of within-box positions; a pre-registered 12-seed CIFAR-10 study improved FID by 3.0 points over matched VQ (p = .033).

#### Adversarial Robustness of Incremental Learners (First-Author Research)
- Developed WB-Softmax, a differentiable attack objective for non-differentiable prototype-based models, achieving 89-100% white-box attack success across USPS, MNIST, and Fashion-MNIST.
- Designed progressive two-stage selective adversarial training and separation-aware diagnostics using iCVIs; achieved best-in-class AURAC (28.2%, 64.5%, 41.3%) and improved high-perturbation USPS robustness 4x.

#### DARPA Computer Vision Research
- Integrated ART classifiers into YOLO and built modular PyTorch infrastructure for classifier-head swapping, feature visualization, automated checkpointing, and SLURM multi-GPU training.

## Publications & Manuscripts

- Cairns, S., Brito da Silva, L.E., Petrenko, S., Wunsch, D.C., & Liu, J. (2026). "Robustness of Fuzzy ARTMAP to Adversarial Attacks and Progressive Adversarial Training for Streaming Learning" *IJCNN 2026*. [arXiv (extended version)](https://arxiv.org/abs/2605.06902)
- Cairns, S., Wunsch, D.C., & Liu, J. (2026). "ART-VQ: Vigilance-Controlled Projection Quantization for Discrete-Continuous Latent Representations" *In submission*.
- Cairns, S., Wunsch, D.C., & Liu, J. (2026). "Generating from Regions: Modeling Discrete Hyperbox Identities and Continuous Within-Region Positions" *In submission*.

## Industry Experience

### Software Engineer Intern
**Ford Motor Company** | Remote | May 2022 - Aug 2022
- Modernized legacy flat-file workflows using a SQL datastore and Java API; delivered Qlik Sense dashboards to Ford Credit stakeholders.

### Software Developer Intern
**Howmet Aerospace** | Cleveland, OH | May 2021 - Aug 2021
- Improved shipping traceability across North American flow paths; maintained 10+ ASP.NET applications.

## Skills

**ML/AI:** Python, PyTorch, scikit-learn, NumPy/Pandas, TorchVision, OpenCV, YOLO
**HPC/Systems:** CUDA, SLURM, Linux, Bash, Multi-GPU Training, Git

## Site Map

- https://shanecairns.com/work : full resume (this content, rendered)
- https://shanecairns.com/life : personal story, interactive jungle game, photo galleries
- https://shanecairns.com/llms.txt : short machine-readable summary