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Alejandro Alvaro

@alejandroalvaro

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PhD student specializing in deep learning for ocean engineering.

United States

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What I'm looking for

I seek a collaborative environment that fosters innovation and allows me to apply my research in practical applications, particularly in ocean engineering and machine learning.

I am a dedicated PhD student in Ocean Engineering at Florida Atlantic University, focusing on deep learning and reinforcement learning applications for developing physics-informed logic controllers for Autonomous Underwater Vehicles (AUVs). My academic journey has been marked by a strong commitment to research, as evidenced by my active participation in various projects and publications.

Throughout my studies, I have successfully identified mechanisms that enhance propulsive efficiency during undulatory locomotion and developed machine learning tools for classifying wave-breaking types. My research has been presented at prestigious conferences and is currently in preparation for publication. I hold an active Secret security clearance, which underscores my dedication to contributing to the field of ocean engineering.

In addition to my academic achievements, I have gained practical experience as an Acoustic Subject Matter Expert at the Naval Oceanographic Office, where I modernized and automated acoustic analysis processes, significantly reducing modeling time. My technical skills encompass a wide range of proficiencies, including programming in Python and C++, machine learning frameworks like TensorFlow and PyTorch, and advanced modeling software such as SolidWorks and OpenFOAM.

Experience

Work history, roles, and key accomplishments

Acoustic SME

Naval Oceanographic Office

Sep 2024 - Sep 2025 (1 year)

Modernized and automated existing acoustic analysis processes, reducing modeling time by over 50%. Developed new methods for ASW analysis and integrated software for acoustic applications.

ASW Analysis Integration Automation Python

Acoustics Research Intern

SURIEA University of Washington

May 2021 - Aug 2021 (3 months)

Developed a machine learning model for ship detection using passive hydrophone recordings and processed OOI/AIS data for labeling. Successfully built a ship classification model for large commercial vessels, presenting the research at the Acoustical Society of America meeting.

Machine Learning OOI Data AIS Ship Classification Python Keras PyTorch TensorFlow

Education

Degrees, certifications, and relevant coursework

Florida Atlantic University

PhD, Ocean Engineering

Activities and societies: Exploring Undulatory Swimming Behaviors with Deep Reinforcement Learning; Classifying Breaking Waves Using Machine Learning; RMSs Array design improvement via Machine Learning.

Currently pursuing a PhD with a focus on deep learning and reinforcement learning applications. Research involves developing physics informed logic controllers for AUVs.