Priyanshu Trivedi

Designed and deployed a production system to convert airport boundary polygons into optimal circles for flight-landing detection, scaling coverage from ∼120 to 1000+ airports; applied geometric algorithms (Welzl's + binary-search inner fit) to maximize accuracy and minimize false positives — ensuring reliability at scale. Personalized airport selection for up to 20 airports per user (iOS constraint) using travel signals, replacing a static region-based list; authored internal documentation to onboard new team members to the feature. Increased notification coverage from 30% to 47%, driving ∼1% uplift in airport bookings; validated via A/B experiments and debugged edge cases involving geofence misconfiguration and notification delivery failures.

Software Development Engineer I – Airports Team - Uber Technologies Inc.

• Bangalore, India

(2024-10)

• Designed and deployed a production system to convert airport boundary polygons into optimal circles for flight-landing detection, scaling coverage from ∼120 to 1000+ airports; applied geometric algorithms (Welzl's + binary-search inner fit) to maximize accuracy and minimize false positives — ensuring reliability at scale.
• Personalized airport selection for up to 20 airports per user (iOS constraint) using travel signals, replacing a static region-based list; authored internal documentation to onboard new team members to the feature.
• Increased notification coverage from 30% to 47%, driving ∼1% uplift in airport bookings; validated via A/B experiments and debugged edge cases involving geofence misconfiguration and notification delivery failures.
• Diagnosed that ∼20% of airport traffic represented low-conversion planning sessions — ride attempts abandoned before checkout; triaged root causes by analyzing ride-abandonment signals and user journey data.
• Built and deployed an event-driven Kafka producer-consumer pipeline that consumed ride-abandonment events, enriched them with contextual signals, and published to a downstream topic for ops-driven re-engagement; wrote and reviewed code to ensure accuracy, testability, and adherence to microservices best practices.
• Improved planning-session engagement coverage by ∼4% through targeted nudges; contributed to team documentation covering pipeline architecture and operational runbooks.
• Collaborated with cross-functional teams to integrate Delta Airlines APIs, ingesting real-time itinerary signals and producing enriched Kafka events to build per-user flight context across the travel lifecycle; participated in code review to ensure data consistency and fault tolerance.
• Triggered contextual notifications at each flight milestone and enabled personalized upsell (Premium / Black / XL) using passenger count, baggage signals, and membership tier; debugged integration issues across service and network boundaries.

B.Tech - Computer Science and Engineering - Indian Institute of Information Technology, Bhopal (2020 - 2024)