# Zixiong Feng

> Full Stack Engineer @ Brilliant Home Technology

Location: Mountain View, California, United States
Profile: https://flows.cv/zixiong

## Work Experience
### Full Stack Engineer @ Brilliant Smart Home
Jan 2023 – Present | San Mateo, California, United States
● Built smart energy capabilities including user onboarding setup and animated solar savings dashboard using Python, C++(Qt), and Javascript for 80k Brilliant control panels. Interfaced with the backend, utilizing weather API and energy consumption data to enable real-time solar savings and production efficiency monitoring for solar panel builders and users.
● Optimized loading performance of the bluetooth smart device diagnostic screen for large homes with 70+ devices by redesigning the data model architecture/layers with Qt proxy models.
● Established the entire regulatory domain WiFi configuration for Brilliant controls. Utilized C++ and Javascript to build its UI setup flow, and Asyncio python for the backend logic of the embedded application that interfaced with connman.
● Handled edge case errors for device startup. Implemented error notification pop-ups for various wifi connection issues and
configuration timeout issues to allow users resolve the errors.
● Participated in building an analytical logging system that generates logs around screen views and button clicks behaviors.
Utilized these logs on Mixpanel to monitor feature engagement and traceback bugs.
● Investigated and resolved Sentry errors and bugs caused by race conditions, complicated dependencies, etc. resulting in a ~1000 error reduction per month.

### Software Engineer @ Mount Sinai Health System
Jan 2022 – Jan 2023 | New York, United States
● Built a 3D interactive web visualization tool that combined node edge graph with heat map using React and Three.js. Enabled biological science researchers to find data patterns in a high dimensional multi-omics environment with a team of 2 engineers and designers.
● Conducted user research through 6 qualitative interviews; pitched and presented the product demo to industry leaders and researchers to gather feedback for product prototyping

### Full Stack Engineer @ Brilliant Smart Home
Jan 2022 – Jan 2022 | San Mateo, California, United States
● Developed Home Screen Shortcut Navigations for Brilliant’s embedded home control with QML module and C++ to increase efficiency on accessing specific rooms and smart home devices; features deployed on over 50k Brilliant controls.
● Refactored the home control’s error notification system and home menu data structures with object-oriented design to increase its capability of handling large number of error states and diverse home device data categories.
● Collaborated with product managers and technical leads to define Brilliant home control’s functionalities and UI
● Design test suites and worked with the QA team to test functionalities on real hardware

### Frontend Developer @ ClassTranscribe
Jan 2020 – Jan 2021 | Champaign, Illinois, United States
A platform for students to watch lecture recordings uploaded by instructors with synchronous transcriptions in different languages
● Designed website user interface and developed the front-end features including the user sign up and video playlist page with React. Worked around cookies manipulation and designing customized UI components suitable for video steaming applications.
● Collaborated with a team of 20 using Git source control to review codes, test, and deploy changes to the server

### Research Assistant @ National Center for Supercomputing Applications
Jan 2019 – Jan 2021 | Champaign, Illinois, United States
• Utilized R to clean over 400GBs of Zillow housing assets and transaction data; merged housing transaction data with census tract and school district geographic data; stored data in PostgreSQL database; used QGIS to analyze these geospatial data and delivered results to a legal team as evidences of a complaint regarding the 2015 Flint water pollution incident
• Employed machine learning models and neural network with Python to help the Illinois Home Weatherization Assistance Program predict the housing energy consumption; improved the previous models and reduced the least square error by 20%
• Applied LASSO feature selection and used machine learning models on Python to implement unbalanced multi-class classification on ethnicity; discovered potential racial discrimination toward renters in rental processes


## Education
### Master of Science - MS in Computer Science and Information Science
Cornell Tech

### Bachelor of Science - BS in Statistics and Computer Science
University of Illinois Urbana-Champaign


## Contact & Social
- LinkedIn: https://linkedin.com/in/zixiong-feng

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Source: https://flows.cv/zixiong
JSON Resume: https://flows.cv/zixiong/resume.json
Last updated: 2026-04-05