Ariel Sulton

Google Student Ambassador working to improve AI literacy among university students and promote Google's AI technologies.

• ▸Created 10 educational content pieces to improve AI literacy among university students
• ▸Delivered hands-on sessions on Gemini AI and its five key features
• ▸Produced content and supported the Google Student Ambassador Inauguration Event

Conducting research on AI applications for environmental monitoring, specifically mangrove health assessment using multispectral imagery and water quality data.

• ▸Conduct monthly collection of water-quality measurements and multispectral drone imagery
• ▸Research and build an AI pipeline for mangrove health assessment from the collected data
• ▸Apply computer vision, time-series forecasting, and LLM-based summarization (RAG)

Independent study program focused on machine learning and deep learning with comprehensive soft skills development.

• ▸Completed independent study modules focused on machine learning and deep learning
• ▸Strengthened soft skills via sessions on Personal Productivity, Growth Mindset, Flexing Under Pressure, Communication and Networking, Business Presentation, and Personal Branding
• ▸Implemented a product recommendation system using popularity-based and collaborative filtering approaches

Community leadership role focused on expanding data science community engagement and mentoring students.

• ▸Expanded community event reach and participation by 20% year-over-year
• ▸Mentored the data science division for competitions held by the community
• ▸Recorded and edited weekly community meeting videos

Leading software development for autonomous boat navigation systems with advanced sensor fusion and computer vision.

• ▸Led the team's software roadmap, code-style standardization, and technical documentation
• ▸Built a ROS2 stack for autonomous boat navigation with two control-method approaches
• ▸Implemented obstacle avoidance via sensor fusion across camera (computer vision), GPS, and LiDAR
• ▸Developed YOLOv11-based object detection and optimized inference & data pipelines
• ▸Evaluated model performance and mitigated false positives (color similarity, thresholding, augmentation)