JULIAN CARVAJAL RICO
San Antonio, Texas 78249
(210)· 935· 6775
jcarvajalrico@gmail.com
Ph.D Student – Graduate Research Assistant
The University of Texas at San Antonio
Vascular Biomechanics and Biofluids Laboratory
I am a Ph.D. candidate in Mechanical Engineering at The University of Texas at San Antonio (UTSA), specializing in Machine Learning for computational biomechanics and healthcare applications. My research focuses on developing predictive models for Abdominal Aortic Aneurysm (AAA) assessment using patient-specific geometric and biomechanical data. I employ Graph Neural Networks (GNNs) to predict wall stress distributions and classify rupture risk based on node-level features extracted from 3D vascular meshes—offering a more localized and informative alternative to traditional diameter-based methods. Prior to my current focus on AAA, I developed GNN-based frameworks for the predictive modeling of multiple chronic conditions, integrating clinical patient specific data to support personalized risk forecasting. Before entering academia, I worked in instrumentation and data acquisition at DAQ Solutions, a National Instruments partner, and later founded a consultancy supporting medical device development, including a food image analysis tool for caloric monitoring and a high-flow oxygen delivery system for pulmonary care.
RESEARCH EXPERIENCE
Fall 2024 – Present / San Antonio, TX
Vascular Biomechanics and Biofluids Laboratory – UTSA – Graduate Research Assistant I
· Investigate the relationship of node specific Geometric Indices in Abdominal Aortic Aneurysm (AAA) and Rupture Potential Index(RPI), using Graph Neural Networks (GNNs).
Spring 2022 – Fall 2024 / San Antonio, TX
Advanced Data Engineering Laboratory – UTSA – Graduate Research Assistant I
· Developed a novel Graph Neural Network (GNN) model augmented with graph Laplacian regularization to analyze complex relationships between multiple chronic conditions (MCC) and individual risk factors. Focused on holistic analysis of prevalent conditions such as diabetes, obesity, cognitive impairment, hyperlipidemia, and hypertension within the Cameron County Hispanic Cohort.
· Enhanced MCC prediction by creating a two-stage graph generative model, incorporating a Graph Variational Auto-Encoder (GVAE) and a Laplacian Regularized GNN. Aimed at optimizing patient data representation and improving early identification of at-risk individuals, emphasizing refined graph structure for precise pattern recognition in medical data.
· Investigate the influence of object shape on leeway drift using a deep learning model trained on a unique dataset incorporating physical and environmental variables. Demonstrated superior predictive performance in estimating leeway speed and drift components, outperforming traditional machine learning models.
ACADEMIC EXPERIENCE
Margie and Bill Klesse College – UTSA Spring 2022 – Fall 2024
Graduate Teaching Assistant San Antonio, TX
· Engineering Practice and Graphics (Fall 2024).
· Dynamics (Summer 2023).
· Dynamics & Controls Laboratory (Spring 2023 – Fall 2022 – Spring 2022).
· Thermodynamics II (Summer 2022).
The University of Texas at San Antonio May 2024
NFU Summer Camp Short Courses San Antonio, TX
· Instructor for Machine Learning and Data Analytics for Manufacturing.
The University of Texas at San Antonio June 2022
DoD High School Workshop San Antonio, TX
· Instructor for Introduction to Machine Learning Workshop.
ACHIEVEMENTS AND AWARDS
·First place in the UTSA Transdisciplinary Team Grand Challenge. Project: The use of AI and machine learning models to augment vocal communication for individuals with disabilities to improve social and emotional wellbeing. San Antonio, Texas 2023.
·Completion of the NSF National I-Corps Program with the Intelligent Behavior Analytics team. Recognized for innovation in AI technology aimed at supporting individuals with Autism and their caregivers. Acknowledged by The University of Texas at San Antonio, The Congress of the United States, The State of Texas, Texas State Representative, and the NSF. San Antonio, Texas 2023.
INDUSTRY EXPERIENCE
KUTAI – Lambda Devices June 2021 – October 2021
Freelancer – Design, Prototyping and Manufacturing Medellín, Antioquia, Colombia ´
· Redesign and prototyping wearable device to monitor daily calories intake.
· Redesign humidifier with integrated flow generator to treat lungs medical conditions.
DAQ Solutions Equipment S.A.S July 2018 – August 2019
Commercial and Project Engineer Rionegro, Antioquia, Colombia
· Mechanical stirrer design, including material selection and calculations. The Shaker’s purpose is to create excitation on beams or columns for fatigue tests.
· Participation in the working group responsible for the instrumentation and data acquisition in a concrete C-wall test with high precision equipment and one of the first of its kind in the country.
EXTRA CURRICULAR
Extreme Robotics National/Extreme Robotics International Tournament October 30 2019 – February 27 2020
Judge and Teams Mentor Medellín, Antioquia, Colombia ´
· Judge of the national and international Extreme Robot Tournament by Fundacion GLOBAL y VEX Robotics.
IISE 2024 Annual Meeting. May 18 – 21 2024
Chair of Healthcare IV Session, Track: Data Analytics and Information Systems.
Montreal, Quebec, Canada
INFORMS 2024 Annual Meeting. Oct 20-23, 2024
Chair of Advances in Healthcare Analytics Session, Track: Data Mining. Seattle, Washington, USA