Hi, I'm Michael Shteynberg
I am a passionate and driven Computer Engineering and Mathematics student at Northeastern University with a strong interest in artificial intelligence, embedded systems, and data-driven technologies. I enjoy taking on challenges that push me to grow, whether that means building a new system from scratch, learning a tool I've never used before, or exploring how AI can be applied in creative ways.
About Me
I am a Computer Engineering student passionate about applying AI and engineering to solve real-world challenges and deliver meaningful solutions.
My experience ranges from writing efficient code in Python to building backend systems with Flask, working with embedded devices, and experimenting with data visualization and analysis. I'm eager to keep learning, solving complex problems, and contributing innovative solutions that connect curiosity, persistence, and technical expertise.
When I’m not studying or working on projects, you can find me developing at ZOR!, a biotech startup, or building AI-powered solutions with Northeastern’s AI Club. Outside of tech, I enjoy training for triathlons, playing soccer and tennis, and building LEGO.
Software Development
Full-stack development and mobile apps
Machine Learning
AI algorithms and neural networks
Data Engineering
Meaningful visualizations and manipulation
Featured Projects
A showcase of my technical projects spanning embedded systems, web development, and machine learning
Experience & Education
Shaped by a strong academic foundation and diverse professional experiences in computer engineering.
Professional Experience
Designing and building AI powered solutions and data pipelines for real-world application and clients
Designed and developed a Python/Flask backend for ZOR!, a non-invasive, predictive epilepsy management app that securely collects health and environmental data from iOS devices
- •Build 15+ REST API endpoints enabling efficient data ingestion, offline sync, and interactive collection modes
- •Create HealthKit manager for collecting health, location, and Apple Watch data using Swift
- •Feed collected real-time device and behavioral data into supervised AI models for predictive analytics
Helped develop and test a portable eddy current inspection device, now used by leading aerospace companies to identify structural fatigue and material degradation in aircraft wings
- •Created and automated Python test scripts and JSON action files to validate embedded system functionality
- •Developed Bash scripts for port tunneling of prototype devices over secure networks using SSH and SCP
- •Enhanced a custom C++ testing framework with JSON-C and macros to support I/O, alarm, and LED testing
- •Debugged signal integrity issues using oscilloscopes to verify voltage behavior and analog gain accuracy
Improved data analytics and AI processes at Acadia, an LSEG Company, enhancing the efficiency and accessibility of financial insights for institutional clients
- •Redesigned Power BI dashboards for major financial institutions, driving increased usage by 10%
- •Accelerated data queries using PostgreSQL in pgAdmin, reducing dashboard run times by 99%
- •Created prompt engineering guidelines and comprehensive documentation for new internal AI product
Spearheaded the development of an investor notification interface for Percent, a FinTech startup, enhancing real-time communication and user engagement on its Private Credit platform
- •Produced SQL and Python based reports to extract and analyze data, providing actionable insights
- •Developed wireframes in Balsamiq and enhanced final designs in Figma, delivering a polished interface
Education
Relevant Coursework:
Get In Touch
I'm always open to discussing new opportunities, collaborations, or just having a chat about technology