Muhammad Saad Babar
CS Student | Seeking Technical & Business Internships for Summer 2025
Experience
Software Engineer Intern, Autonomous Systems
Noblis
June 2024 - August 2024
I developed and optimized an end-to-end pipeline for generating synthetic edge case images using technologies such as OpenAI API, Stable Diffusion, and PyTorch. This work significantly expanded training datasets for autonomous vehicle systems by leveraging generative AI to create complex edge cases for object detection models. I automated the ground truth labeling process for over 100 AI-generated images by developing Python scripts utilizing libraries like Openpyxl and Pandas, integrating YOLOv8 for accurate object detection and annotation. Additionally, I engineered a human-in-the-loop framework and introduced reinforcement learning techniques into the prompt optimization pipeline, improving system adaptability and decision-making for edge case scenarios. I presented the project's outcomes to senior executives, showcasing advancements in automation and AI-driven process efficiency, and demonstrating the measurable improvements made to the pipeline. This role was a mix of backend, computer vision, and machine learning engineering.
Data Entry Assoicate
RHB Laboratories
January 2022 - April 2022
Entered insurace CPT codes into database using company's software
Education
University of Michigan, Ann Arbor
Bachelor of Science in Computer Science
Graduation: May 2026
Relevant Courses
- Data Structures and Algorithms
- Operating Systems
- Practical Data Science
- Web Systems
- Human-Centered Software Design & Development
- Computer Organization
- Foundations of Computer Science & Computational Theory
- Applied Linear Algebra
- Discrete Mathematics
- Programming and Introductory Data Structures
- Probability and Statistics for Engineers
Skills
Projects
Leetcode Reminder
Developed Chrome Extension to send daily reminders to users to practice Leetcode problems using spaced repitition to retain knowledge
Wire Transfer Model
Made banking simulator to replicate how users are autheticated and how transactions are processed through using a priority queue to determine a custom order
WallStreetBets NLP Sentiment Analyzer
The main function of this program is to extract information from the latest posts on a subreddit and present the top-performing stocks for a given day, using Natural Language Processing (NLP) to analyze the content of the posts. This full-stack implementation integrates multiple APIs, processes data, and visually presents insights into stock trends on WallStreetBets. The program filters data to ensure that only stocks listed on US exchanges like the NYSE or NASDAQ are included, as it's specifically designed for the US markets. Additionally, I created custom functions to simplify data processing, such as recognizing company names as they are casually mentioned in the forum (e.g., identifying 'Rivian' instead of the full name 'Rivian Automotive, Inc'). I also implemented unit tests to validate the functionality of these custom parsing functions, ensuring the program works as expected.
Instagram Clone
I developed an Instagram clone with Flask, focusing on user authentication, post creation, and real-time updates. The application features client-side dynamic pages and REST API endpoints for CRUD operations, allowing users to create, edit, and delete posts or comments. I implemented logic to ensure users could only delete their own comments, and handled database updates accordingly. Additionally, I used JavaScript event handlers to create a double-tap 'like' feature, enhancing user interaction. The project includes multiple pages such as login, feed, account management, and more.