Google Developer Student Club

Navjeet Hundal

209-***-**** ***************@*****.*** in/navjeet-hundal/ github.com/navjeethundal03 Education

University of California Davis June 2026

Bachelor of Science in Computer Science

Relevant Coursework: Programming Languages, Machine Learning, Computer Architecture, Probability and Statistical Modeling for Computer Science, Algorithm Design and Analysis, Assembly Language Programming, Discrete Mathematics, Computing Fundamentals, Advanced Programming with Data Structures in C++, Theory of Computation, and Operating Systems Experience

Machine Learning Intern Google Developer Student Club January 2024 - June 2024

• Designed and implemented a Python-based AI Chess Game featuring an AI opponent powered by the Negamax algorithm with Alpha-Beta pruning, achieving a 95% accuracy rate in identifying optimal moves up to a depth of 3 layers.

• Enhanced the AI’s strategic depth by allowing adjustable depth settings and implementing advanced chess rules such as en passant, castling, and pawn promotion, improving resource downloads by 25%.

• Optimized AI performance, reducing move computation time by 30% to an average of 0.8 seconds while ensuring precise move evaluations.

• Implemented features such as undo (hotkey: ”Z”) and reset options, utilized by 67% of players, improving gameplay accessibility and control.

Projects

Retinal Vascular Tree Extraction with Batch-Drop U-Net

• Designed and implemented a custom U-Net model with Batch Normalization and Dropout layers to optimize retinal vessel segmentation accuracy.

• Achieved notable metrics on the DRIVE dataset, including a Jaccard Index of 0.6766 and an F1 Score of 0.8069, marking a significant improvement in segmentation results.

• Utilized Python, TensorFlow, and Google Colab for efficient model development, training, and data processing, contributing to a published research study. Text-based Tumor Diagnosis AI Model

• Leveraged the TCIA dataset to build a classification model focused on identifying tumor types (malignant or benign) based on textual data.

• Developed a lightweight AI script using TensorFlow and Keras to process and classify tumor-related textual information.

• Achieved an impressive accuracy rate of 95.61%, highlighting the model’s effectiveness in supporting data-driven clinical insights.

Punjabi Farmer Awareness Website

• Built a website using HTML, CSS, and JavaScript to raise awareness about the Punjab farmer crisis, focusing on clear and engaging information.

• Designed and optimized an interactive platform with real-time statistics, improving resource downloads by 25% and reducing load times by 40%.

• Received 98% positive feedback in the first three months, attracting 100+ unique visitors. Target Shooting Game in Unreal Engine 5

• Developed a target shooting game with random target spawning and timer-based challenges, played by 20+ users.

• Designed scoring mechanics to evaluate accuracy, with 90% of users achieving over 70%.

• Reduced latency by 20%, reduced average input delay to under 50ms, and maintained 60 FPS performance across various systems using Blueprints and C++.

Technical Skills

Languages: Python, JavaScript, HTML/CSS, Java, C++, R, Swift Libraries/Frameworks: NodeJS, Pytorch, pandas, Matplotlib, scikit-learn, TensorFlow, Express, React, OpenCV

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