Conducting in-depth research and software development focused on network science. My work heavily involves developing and analyzing link prediction algorithms and extracting complex graph metrics.

• Graph Theory
• Link Prediction
• Algorithm Evolution
• Python

Exploring the performance and behavior of automated code-evolution systems tasked to obtain machine-designed methods for link prediction. Our evolved algorithms outperform human-designed methods and show improved computational efficiency. Read on arXiv →

Investigating the interplay between algorithm efficiency and network structures using suitably-designed synthetic graphs that incorporate both micro-scale motifs and meso-scale communities. We derive theoretical upper bounds for link prediction performance to estimate predictability. Read on arXiv → | Published Article →

Gemini Agentic Capabilities: Conducted research and engineering focused on enhancing the reasoning and autonomous task execution abilities of Gemini agents.

Google Workspace AI Classification: Led machine learning initiatives and architected high-scale backend infrastructure for advanced document classification.

• Machine Learning
• Backend Architecture
• LLMs (Gemini)
• Agentic Systems