Alexander Escobar

Global Challenge: Data Science/AI/Robotics

Abstract:

This senior design project proposes SmartTransit NYC, an AI-powered prediction system designed to improve rider decision-making through real-time analytics and machine learning. The system integrates MTA real-time feeds, historical performance data, weather conditions, and temporal ridership patterns to generate three outputs: delay probability predictions, crowding forecasts, and optimized alternative routes. Using ensemble machine learning techniques, including Random Forest classifiers and Long Short-Term Memory (LSTM) networks, the system aims to reach 75–85% delay prediction accuracy and 70–80% crowding estimation accuracy.

Feasibility analysis indicates strong technical viability due to available open data and established machine learning methods. By improving reliability information and rider confidence, SmartTransit NYC could encourage greater transit use and support sustainable urban mobility.

Bio:

Alexander Escobar graduated from the NYU Tandon School of Engineering in 2026 with a degree in Computer Engineering, bringing a strong interest in embedded systems, hardware design, and data-driven technologies that address real-world challenges. Through his coursework and projects, he developed experience working with programming languages such as Python and C++, as well as designing and debugging digital systems using tools like Verilog and microcontroller platforms. He enjoyed building systems that integrate hardware and software to collect, process, and interpret real-world data. Alexander also gained industry experience as an intern with HP, where he had the opportunity to learn from engineers in a professional technology environment and gain insight into how large-scale hardware and software systems are developed.

This experience further strengthened his interest in applying engineering skills to practical, real-world problems. Beyond his technical pursuits, Alexander remained committed to mentorship and community engagement. He worked as a teaching assistant helping Spanish-speaking students prepare for Algebra Regents exams and served as a peer mentor supporting first-year students as they navigated college life and academic planning. Through these experiences, he aimed to combine technical expertise with leadership and service to create meaningful impact in his community.