David Denny
Backend systems by day. Building Strive by night.
About
01 — About me

Hey, I’m David.
I’m a software engineer. Outside of work, you’ll catch me at the gym, on a pickleball court, or playing with my dog.
— Currently
- Building Strive — preparing for first release
- Wrapping up my M.S. in CS at UT Austin
- Always keeping up with the latest in AI — whether it's new model releases, tools for automation and productivity, or figuring out which models excel at different tasks. I make it a priority to research and experiment so I can stay on top of the ecosystem and get the most out of what's possible.
Featured Project
02 — Strive
— Strive
A place to stay on your path.
Strive is a social platform for self-improvement. Whether you want to set a personal goal, join a community, or just connect, Strive is built to help you grow and stay motivated. Share your progress, find people working on similar goals, or just meet others working on themselves.
I started building Strive after noticing I’d set big goals and lose momentum over time. Around the same time, I deleted my old social media. What stood out to me — aside from the time it gave back — was realizing how much I had tied my identity to being seen online.
Without it, I noticed how often I’d compare myself to strangers without meaning to. I caught myself doing things partly so I could post about them, instead of being in the moment.
Strive is what I wish I’d had then: the same gravity that makes social media work, pointed at genuine self-improvement and real community.
It’s about making it easier to come back and start again, and connecting with people who are on the same path — no matter where you’re starting from.
— What I’m doing on it
- Founded the company
- Designed and built the mobile app
- Shipped the marketing site
- AI video pipeline driving marketing
- Running the day-to-day
— Stack
— Where it started
Strive started as a class project I shipped on Android — same idea, simpler shape. I called it CommitPal. The original demo and source are still up if you want to see the first cut.
Where I’ve worked
03 — Experience
Dayton, OH
- Sole backend engineer on multiple mission-critical government applications — owning end-to-end from requirements to production.
- Built REST API endpoints and backend microservices, deployed across local, dev, and production environments.
- Tuned Elasticsearch analyzers, scoring functions, and field mappings to lift search relevance at scale.
- Built a RabbitMQ-based messaging layer between API and worker pods for async, event-driven notifications.
- Wrote a K3D bootstrap that cut local dev environment setup from 60 minutes to under 20.
- Built an interactive launcher to selectively start backend services and a Postgres reset tool to resolve Alembic migration drift.
- Owned production hotfixes, data migrations, and large-scale corrections end-to-end — diagnosing, scripting the fix, and validating in production.
- Lead daily standups to coordinate progress and unblock PRs; technical point of contact for government clients, demoing applications and gathering feedback for the next iteration.
PythonFastAPIElasticsearchRabbitMQPostgreSQLDockerK3DDallas, TX
- Wrote complex SQL queries and data extraction pipelines surfacing workforce insights for stakeholders across multiple business units.
- Built an internal automation service that generates, validates, and distributes offer letters at scale, replacing a manual workflow.
SQLPythonAutomationBoston, MA
- Developed a Java-based inventory tracking system with automated expiry detection, reducing inventory loss and improving supply chain traceability.
- Implemented real-time alerting for low-stock and expiring components, notifying teams proactively and preventing production delays.
JavaInventoryAlertingPalo Alto, CA
- Trained OCR and label-classification models in Keras, hitting 87% accuracy on patient intake forms and cutting manual data entry by ~60%.
- Wired the trained model into a cross-platform mobile app via REST so users could photograph forms and get digitized text in real time.
KerasTensorFlowOCRRESTMobile
Tap a role to expand
Education
04 — Education
UT
ActiveThe University of Texas at Austin
M.S. in Computer Science
Coursework: Deep Learning, Machine Learning, Android Programming.
Jan 2025 — Dec 2026
GPA 3.91
CMU
Carnegie Mellon University
Graduate Certificate — ML & Data Science
Recommender systems, optimized ML pipelines, PyTorch, TensorFlow.
2024 — 2025
GPA 3.84
UTD
The University of Texas at Dallas
B.S. in Computer Science
Academic Excellence Scholar (Full Ride).
2019 — 2022
GPA 3.82
— A few things to look at
Other Projects
05 — Projects
Transformer From Scratch
2025
UT Austin · Deep Learning
Built the full transformer architecture in PyTorch from the ground up — multi-head attention, positional embeddings, residual connections, layer norm. Trained end-to-end and benchmarked across attention configurations.
ML for Financial Forecasting
2025
UT Austin · Machine Learning
Forecasting stock-price movement on Nvidia and Tesla. Trained and compared decision trees, random forests, and gradient-boosted models against linear-regression baselines, then wrote up methodology and results end-to-end.
QA System on SQuAD
2025
CMU · 11-637 FCDS
Closed-domain question answering built up an escalating stack — Jaccard overlap → tf-idf → logistic regression → BERT — comparing accuracy and latency tradeoffs at each step.
CNN Image Classifier (Deployment)
2025
CMU · 11-637 FCDS
Trained and deployed a convolutional network for image classification, comparing CPU vs. GPU training cost and inference latency for the deployment pipeline.
Airbnb Analytics Site
2024
CMU · 11-637 FCDS
Pulled Airbnb listings and built a responsive helper site that computes analytic results on the fly. Picked data structures and caching strategies based on access patterns at scale.
Collaborative Filtering Recommender
2024
CMU · 11-637 FCDS
Built a collaborative-filtering recommender over product reviews. Compared sparse matrix representations and their storage / runtime tradeoffs.
Climate + Food Production EDA
2024
CMU · 11-637 FCDS
Joined climate and food-production datasets to surface correlations and prep features for predictive modeling. Heavy on cleaning, viz, and exploratory work.
OCR Patient Intake Pipeline
2022
Onymos Internship
Trained Keras OCR + label classification models (87% accuracy) to digitize hand-filled patient intake forms; wired through REST into a cross-platform mobile app.
Get in touch
06 — Contact
Let’s talk.
Quickest way to reach me is email. If it’s about Strive, mention that — I always make time for it.
© 2026 David Denny