Emilio Luz-Ricca

Emilio Luz-Ricca is a PhD student in Zoology at the University of Cambridge, supervised by Andrew Balmford, Anil Madhavapeddy, and Tom Swinfield. He is part of the AI for Environmental Risks Centre for Doctoral Training and the Cambridge Centre for Carbon Credits, and a member of Churchill College. His research focuses on predictive modeling for biodiversity conservation, leveraging machine learning and remote sensing.

Education includes a BS in Data Science (Phi Beta Kappa, Summa Cum Laude) from William & Mary and an MRes in Environmental Data Science (Distinction) from Cambridge. He also studied Computer Science at the University of Oxford as a visiting student.

Research interests span biodiversity conservation, federated learning, and deep learning applications in ecology. His work emphasizes quantifying species responses to human disturbance and optimizing environmental monitoring methods.

Key awards include the 2023 Outstanding Undergraduate Student in Data Science award, James Monroe Scholar distinction, and multiple hackathon prizes. His technical expertise includes Python, R, deep learning (PyTorch/TensorFlow), and remote sensing.

Experience includes leading workshops on machine learning, consulting for conservation organizations, and research on automated wildlife monitoring. He is funded by the Cambridge Centre for Carbon Credits and affiliated with the Conservation Science Group.