Hi, I'm Yair 👋
(like air with a y)
I'm a Computer Engineer based in Atlanta, GA, focused on software engineering.
I build end-to-end systems across full-stack development, IoT & edge solutions, big-data platforms, embedded systems, and computer hardware design — connecting real-world signals to reliable software people can trust.
About Me
I'm a computer engineer who loves building things where software meets hardware. My sweet spot is turning messy, real-world problems — noisy data, device constraints, clunky workflows — into clean, scalable systems people actually enjoy using.
I'm comfortable owning the whole lifecycle — data architecture, engineering, UI/UX, and stakeholder alignment — and I'm big on iterating: ship, demo, learn, improve. I've worked on projects ranging from internal reliability/experience tooling to V2X research that helped reduce roadside equipment TCO via IoT edge computing.
Skills
Python
Node
TypeScript
Next.js
C++
Figma
Embedded
IoT
JavaScript
React
HTML
CSS
Selected Projects
V2X Research
Developed a solution to reduce the Total Cost of Ownership (TCO) of Vehicle-to-Everything Roadside Equipment (V2X-RSE) using COTS components and open-source software. Innovated a proxy server connecting RSE & OBE networks with a web platform for developers to code, test, and deploy new functionality. Deployed COTS V2X-RSEs at multiple locations with Kubernetes deployment supporting IoT edge computing, including a custom Docker Registry (OwlBoxHub) with custom ARM containers.
2021 AT&T Symposium Hackathon
Used Commercial-Off-The-Shelf (COTS) components and open-source software to create smart IoT connected home lighting control and Light-Based Cues with AI to learn as you work in a WFH environment. The system adapts to the presence of the user and flashes lights to alert times for breaks from working as well as for various environmental changes, such as emergencies, holidays, and intruders.
Undergraduate Senior Project
Developed and managed a group of four engineers as Project Manager in creating start-up tech company TriFit. The project used COTS components, open-source software, proprietary printed PCB boards, and software to optimize bodybuilders' dietary recovery post-workout and meal plans using macronutrients. The main device features a gyroscope, accelerometer, heart rate, blood oxygen, and force sensors interfacing with a Raspberry Pi Zero W. It uses ML with a TensorFlow backend to transmit information over BLE to a mobile app and display nutritional regeneration information from a custom REST API.
Get In Touch
I'm open to discussing software engineering opportunities, cloud architecture, or collaboration on impactful projects. 😄
Say Hello