Hannah James

PhD candidate with a strong foundation in machine learning, electronics, and remote sensing, applying AI to real-world challenges in conservation, agriculture, and product development. Proven ability to build end-to-end systems—from data collection and modeling to deployment and field validation. Skilled in cross-functional collaboration, with a focus on scalable, user-driven solutions that bridge technical innovation and impact.

Virtual Fencing for Cattle Management Cornell University Erickson Lab, Fall 2023–Present; Advisor: Prof. David Erickson

• Led end-to-end design of a GPS-enabled AI-based virtual fencing system for livestock in low-income regions.
• Engineered IoT-based cattle ear tags with GPS-triggered speaker alerts for behavioral deterrence.
• Developed machine learning models to classify bovine behavior from accelerometer/gyroscope signals.
• Used AI image recognition to distinguish bovines from other objects in aerial drone video.
• Conducted iterative field testing and stimulus optimization to refine product effectiveness.
• Created infrastructure with Cornell Center for Advanced Computing to manage definitions and device updates

Invisible Fence: Satellite-AI Wildlife Monitoring Cornell Erickson Lab and College of Veterinary Medicine, Spring 2025–Present; Advisors: Prof. David Erickson, Prof. Steven Osofsky

• Explored use of satellite imagery and ML for real-time wildlife detection.
• Assessed feasibility of identifying elephants and buffalo in remote areas.
• Investigated data needs and technical constraints for scalable monitoring.
• Collaborated with conservation teams to define use cases and technical challenges

Science Buddies (Online)

• James, H. “Build a Wearable Device Using an Arduino to Keep Astronauts Safe on Mars.” Mar. 2025
• James, H. “Satellite Collision Detection: A Hands-On Coding Experience.” Jun. 2025
• James, H. “Simulating The Kessler Syndrome: How Satellite Collisions Could Spiral Out of Control.” Jun. 2025

Peer-reviewed / Academic

• Under Review : Advancing Standardized Cattle Behavior Classification with a Random Forest Model
• Under Review: Design & FEA Modeling of 3D-Printed Ear Tags for Virtual Fencing Applications
• In Prep: GPS-Enabled Virtual Fencing System for Cattle in Resource-Constrained Regions
• In Prep: Biologically Informed Algorithms for Modeling Cattle Response to Auditory Cues and Driving Simulations in Virtual Fencing Systems

Conferences

• MicroTAS 2024 – Poster Presentation, “Redefining Pastures: Innovating Grazing Systems with Affordable Virtual Fencing Solutions”, Published in 2024 MicroTAS Book of Abstracts, DOI: 10.70477/feyp3237
• BMES 2024 – Oral Presentation

• Foundations of Machine Learning
• Mechatronics
• Computational Physics
• Mathematical Methods in the Physical Sciences
• Digital Systems Design Using Microcontrollers

• British Mensa (since 2017)
• Fulbright Sutton Trust U.S. Scholar
• Society of Physics Students Distinguished Chapter (2020–21)
• Centennial Conference Winter Academic Honor Roll (2020)
• Penwith College Mathematics Award (2019)
• Sir Humphry Davy Prize (2016)
• Cornell BME Women
• SiGMA
• Cornell Rowing Club

• President, Cornell MAE 150th Anniversary Council | Fall 2023–Present
• Lead TA, Advanced System Dynamics | Fall 2023
• Committee Member, SiGMA Outreach & Professional Development | Fall 2023–Present
• Speaker, Cancer Literacy Presentation at McGraw House | Spring 2024
• Activity Leader, Girl Scout Engineering Day | Spring 2024