Ryland Wittman
Tampa, FL | rylandscottwittman@gmail.com | (847) 714-3013
Objective
I build solutions by spotting flaws and finding better ways to fix them, diving into infrastructure as code, machine learning pipelines, and emerging tech like agentic AI. I thrive on learning through projects and want a team that values fresh ideas.
Skills
Programming: Python, SQL, BASH
Tools: Terraform, Docker, AWS, Google Cloud, AlloyDB, Cloud SQL, Kubernetes, Redis, Git
Strengths: IaC design, ML pipeline integration, adaptive problem-solving
Projects
These are things I tackled because I saw room for improvement.
CoPythonPro
Utilizing The Artificial Intelligence We Want On Our Team
Why I Built It: Social media's overrun with bots, and I realized those AI-generated accounts signal a bigger problem—attacks can scale so fast we need to be ten steps ahead, all hands on deck.
Abstract: Created CoPythonPro, a Python-based middleware to secure API ecosystems against rapid threats. Features AI-driven Data Loss Prevention with ML models to spot sensitive data, plus swarm intelligence for real-time coordination across nodes. Includes self-healing agents for uninterrupted service and adaptive rate limiting for high traffic. Scaled with a Kubernetes setup on AWS, using load balancers and auto-scaling groups for zero-downtime operation. With a few tricks up its sleeve.
LiminalGenix
Why I Built It: I started rethinking how we approach problems, tracing back thousands of years to design a mathematical algorithm based on deterministic chaos-theory with three states. Bioinformatics inspired me along the way, and I found uses in ancient DNA and rare diseases.
Abstract: Developed a web-based GUI using Python 3.11 Streamlit, modeling DNA loci with a chaos algorithm (Anchor, Liminal, Drift states) inspired by Thomson's Lamp paradox. Built MLOps on GCP with Terraform IaC, GKE, Cloud Build CI/CD, PyTorch for ML, Biopython/cyvcf2 for VCF handling, and Gosling.js for visualization. Processes ClinVar VCFs to output FASTA sequences; tests show 48.70% variant overlap (12.30% pathogenic) on 1000 variants, reducing errors by 35% and compute by 20%. Containerized with CUDA 12.1 GPU support, with a roadmap for broader genomic applications.
Water Infrastructure Optimization
Why I Built It: Working in agriculture business operations, I saw water delivery systems struggling to meet demand. I wanted a design that could double the daily amount deliverable for vital operations.
Abstract: Built a water reserve quick-fill station system while working in agriculture business operations, analyzing existing infrastructure to identify inefficiencies. Focused on structural improvements to double water delivery capacity, with a design that lowers maintenance requirements.
