Hey, I'm Immanuel Peter! 👋
This summer, I'm diving deep into PyTorch, C++, CUDA, CARLA, Docker, and Linux while interning at a quantum computing startup. I'm building toward deep AI/ML expertise through engineering, experimentation, and system-building.
Need a quick crash course on my background and experience? Check out my resume.
Want to dive deeper into my journey? Let's have a chat with
"Engineering the future, one line of code at a time." 🌍💻
Skills & Technologies
Programming Languages
Full Stack Engineering
Machine Learning & Artificial Intelligence
Data Science
Cloud Computing & DevOps
Knowledge Skills
Experience
Software Engineer Intern
Quantum Rings
June 2025 - August 2025
Chicago, IL
- Delivered 19 PRs, 43 contributions, and 15 completed GitHub issues across the internship, adding ~15K LOC and removing ~3.6K LOC while reviewing code and driving schema refactors.
- Diagnosed and fixed critical backend reliability issues by repairing Docker container startup failures, restoring stability in the dev environment.
- Migrated execution data from the user entity to a dedicated relational table with FKs, modularizing schema and ensuring test suite stability with no performance regression.
- Developed full-stack admin analytics dashboards with NestJS, Next.js, and Recharts to track user growth, active usage, and execution volume; integrated SQL time-bucket aggregation and timezone-safe filtering.
- Implemented a telemetry aggregation background worker (AWS SQS + TypeORM) to asynchronously roll up user execution activity, improving scalability and simplifying downstream analytics queries.
- Designed and deployed queue-driven execution processing to decouple heavy telemetry operations from the API, reducing request latency and enabling horizontal scaling.
- Integrated HubSpot CRM sync with fault-tolerant background workers, ensuring user and execution data flowed reliably into marketing/sales automation pipelines without impacting core app performance.
- Overhauled the admin dashboard UI/UX into a fullscreen carousel design with real-time charts, responsive layouts, and dark-mode support, enabling low-friction public demos and investor-facing displays.
- Added developer-facing features including public profile pages with badges and UUID-based certifications, strengthening community visibility and recognition.
- Introduced circuit execution metrics (complexity, duration, backend usage %) to surface workload patterns and highlight developer skill levels.
- Designed and launched a KPI dashboard for UTM-based marketing attribution, building an analytics pipeline and pie-chart visualizations that provided actionable insights for growth strategy.
Data Analyst Intern
Cornerstone Business Solutions
June 2022 - August 2022
Bentonville, AR
- Analyzed sales data for over 500 products using Excel dashboards, identifying top-performing items and contributing to a 15% increase in inventory efficiency.
- Developed a Python web scraper to monitor real-time in-stock availability of 100+ Walmart items, improving restocking decisions and reducing stockouts by 20%.
Volunteer Tutor
Schoolhouse.world
January 2021 - Present
Remote
- Conducted over 170 hours of free peer-to-peer tutoring, assisting students in various subjects and supporting fellow tutors.
- Facilitated over 160 engaging online sessions, fostering a dynamic learning environment for students worldwide.
- Directly influenced the academic growth of over 730 learners, significantly contributing to global education.
- Expanded global reach by impacting learners across nearly 40 countries.
- Amassed over 325 followers on the Schoolhouse.world platform, ranking among the top 0.1% of tutors in terms of follower count.
- Led the SAT Mega Review Session, a popular preparatory session helping students improve their SAT scores.
- Moderated the History subworld, a forum facilitating academic discussions and providing resources for history enthusiasts.
Projects
AutoMoE
A modular, multi-task self-driving system based on a Mixture-of-Experts (MoE) architecture. This approach uses specialized neural networks for specific perception tasks and a gating network to combine their outputs, aiming for a more modular, interpretable, and efficient model for navigating complex environments.
CARLA Autopilot Multimodal Dataset
A large-scale open dataset for autonomous driving research, featuring 82K+ synchronized samples with RGB camera views, semantic segmentation, LiDAR point clouds, 2D bounding boxes, and detailed ego-vehicle states. Built in CARLA with varied weather, maps, and traffic to support tasks like object detection, sensor fusion, imitation learning, and reinforcement learning.
CARLA Autopilot Images Dataset
An open, multi-camera dataset (~188 GB, 68k frames) generated in CARLA with synchronized images, vehicle kinematics, control signals, traffic density, and collision logs. Designed for imitation learning, vision-to-control benchmarks, and multimodal self-driving research. Released with a reproducible collection pipeline and Hugging Face integration.
Mini JAX ViT
A compact Vision Transformer implemented from scratch in JAX/Flax. Includes patch embedding, multi-head self-attention, MLP blocks, and a clear training loop for image classification, focused on readability and educational value.
GovHub
GitHub for Government!
AI Commit
A bash script that uses OpenAI's GPT-4.1-nano model to automatically generate meaningful commit messages based on your staged changes.
LocalRAG
LocalRAG is a terminal-based LLM chat tool that provides infinite memory via local vector search. Designed as a privacy-first alternative to ChatGPT/Claude, it embeds chat history into FAISS and retrieves relevant past context for smarter replies. Users can save conversations, switch models mid-session, and continue prior chats seamlessly. Built with modular CLI components and persistent local storage, LocalRAG demonstrates RAG principles, efficient context injection, and LLM interfacing — all without sending data to any external server.
Semantic Image Search Engine
A full-stack semantic image search application using FastAPI, PyTorch, and Next.js. The project leverages OpenAI's CLIP model to enable efficient text-to-image querying. Users can search for images from a preloaded random dataset based on natural language queries. The application showcases API integration with the Unsplash API for random image loading and features a responsive frontend built with Tailwind CSS.
CodingOH Twitter Bot
The CodingOH Twitter Bot is a Python-based bot designed to engage the developer community on Twitter with programming insights, tips, and humor. By leveraging OpenAI's GPT-4 model and the Tweepy library, this bot generates and posts tweets every 12 hours, providing a blend of educational and entertaining content.
Portfolio Website
This portfolio website highlights my projects, skills, experience, and certifications. It features ImmanuelAI, an interactive component that provides personalized answers to visitor inquiries about me. The site is developed with React and styled using Tailwind CSS, and it is hosted on Vercel.
Education
Computer Science
Bachelor of Science
University of Chicago
September 2024 - June 2028
Relevant Courses:
- Introduction to Computer Science I
- Introduction to Computer Science II
- Systems Programming I
- Systems Programming II
- Mathematical Foundations of Machine Learning
- Discrete Mathematics
Mathematics
Bachelor of Arts
University of Chicago
September 2024 - June 2028
Relevant Courses:
- Introduction to Proofs in Analysis
- Abstract Linear Algebra
- Analysis in Rn I
- Analysis in Rn II
- Mathematical Foundations of Machine Learning
Physics
Bachelor of Arts
University of Chicago
September 2024 - June 2028
Relevant Courses:
- Mechanics
- Electricity and Magnetism
- Waves, Optics, and Heat
- Intermediate Mechanics
Get In Touch
Whether you want to reach out for inquiries, collaborations, or just a friendly hello, feel free to drop me a line or connect with me on social media!
Email Me