Biography

I am a first-generation college graduate who earned my bachelor’s degree in mathematics from Colombia’s National University in 2020, breaking free from societal expectations for women. Then, I began a master’s in applied mathematics and taught at the same institution. Currently, I am pursuing my Ph.D. in Mathematics and Statistics with Interdisciplinary Applications at The University of Texas, Rio Grande Valley. I serve as the president of the UTRGV chapter of the American Statistical Association. While my roots are in mathematics, my current research interests include statistics, data science, and applied mathematics, focusing on using Machine Learning techniques particularly in medical and environmental applications. I am dedicated to working with underrepresented groups in STEM, especially women, and as a person from a developing country, I hope to contribute to education and inclusiveness. I currently work as a Graduate Research Assistant at the ECS Lab at UTRGV. Outside of work, I have several interests that I really enjoy. I love dancing, reading, and exercising. CrossFit, cycling, and hiking are some of my favorite activities. I’m a friendly person, so I value spending time with my family and friends.

Academic Status

PhD Student - 4th

Research Area/Department

Computer Science; Data Science; Machine Learning/AI; Mathematics

Major/Specialty

My major is in Mathematics. My specialty is in statistics, data science, and applied mathematics, with a focus on machine learning techniques, particularly for medical and environmental applications.

Degrees Earned or in Progress

Degree in Mathematics / Mathematics/ 2020 Masters in science-Applied Mathematics/ Mathematics and Statistics with Applications to Medical data/ 2025 PhD. in Mathematics and Statistics with Interdisciplinary Applications/ Mathematics, Machine learning and Environmental Science/ Expected to graduate by 2026

Academic Preparation

I have completed several academic courses that prepare me for this summer internship experience. Within these courses I have taken (and which are relevant to this internship) are Machine Learning, Deep Learning, Introduction to Statistical Learning, Image Processing, Statistical Methods, Numerical Analysis, Linear Models, Mathematical Modeling, and Advanced Data Science. In these courses I improved my programming skills in languages such as Python and R, which prepare me to work in this internship with any type of data in interdisciplinary fields. In addition to this, I have worked in several projects that have helped me develop skills to work on my own independent research and become creative with new ideas to solve real world problems with mathematics.

Research/Publications

1) I worked on a project to develop a Convolutional Neural Network to classify gene images into four experimental groups, using data augmentation and preprocessing to enhance model performance. From this project I got the publication "IFIT3 activation significantly contributes to HIV-1-associated neurodegenerative disorder-mediated neuroinflammation" in the journal frontier in immunology. https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2025.1532318/full. 2) I worked analyzing medical data to estimate the variance after using cross-validation and imputation techniques in classification problems, with this project I got the Best Poster Award, 3rd place, at Student Poster Competition with the master project ” Theory & Application of ROC Curves with Cross-Validation Estimators for Clinical Data with Missing Observations”. https://drive.google.com/file/d/15qwAATuC7x7yCm92On1DLnN8mtL4TbcF/view?usp=sharing, 3) Collaborated with Kwaai AI Lab to design and implement homomorphic encryption methods for privacy-preserving vector search, co-developing two novel algorithms in the Mathematical Problems in Industry Workshop. https://www.siam.org/conferences-events/workshops/2025-graduate-student-mathematical-modeling-camp/

Research/Academic Interests

While my roots are in pure mathematics, my current academic research interests include Statistics, Data Science, and applied mathematics, with a focus on Machine Learning and Deep Learning, particularly in medical and environmental applications. My Ph.D. dissertation topic focuses on using machine learning to model the temporal variability in CO2, CH4, and N2O fluxes from human made aquatic-systems such as hydropower, and fishponds. In particular, my research aims to elucidate drivers and patterns of temporal variability in greenhouse gas (GHG) emissions from these distinct aquaculture production systems in Brazil using machine learning. In my undergraduate program, I worked in pure mathematics, so I never imagined that my background would one day allow me to work on real-world problems. Over time, I have discovered how computational applications can be both fascinating and powerful tools for addressing practical challenges. In my master's program I worked on Applied mathematics and Statists and analyzed medical data to estimate variance after using cross-validation and imputation techniques in classification problems. During my research, I have worked with large datasets and images, which require advanced tools like high-performance computing. Right now, I am particularly interested in high-performance computing, I took a free course in Argonne in AI-driven Science on Supercomputers, and a Hands-on in Supercomputing at Oak Ridge Computing facility to enhance my skills in this area.

Computational and Data Science Areas

Applied Computer Science; Applied Mathematics; Climate and Global Dynamics; Clinical Medicine; Health Sciences; Statistics and Probability

Motivation

I am currently a fourth-year PhD student of Mathematics and Statistics at the University of Texas Rio Grande Valley (UTRGV), expecting to graduate in 2026. I completed my undergraduate program in Mathematics in Colombia in 2020 being the first in my family to earn a college degree. When I immigrated here during the initial stages of my PhD, I focused on my comprehensive and candidacy exams. However, last year I became aware of the valuable opportunities' internships provide for PhD students, especially during the summer. Since then, I have been actively looking for an internship that aligns with my aspirations, which have been difficult due to the restriction of some institutions with international students. I found out about the SPR summer program from a friend two years ago, and also at SIAM CSE BE Program 2025. They mentioned that it's a great program for graduate students, offering mentorship and opportunities to learn new skills. This made me interested, and after exploring the website, I was convinced that this SPR program is the right fit for me and could significantly contribute to my career. Although I have never participated in an internship before, I am eager to learn and willing to improve to advance my career. I think this is an amazing opportunity to have a different experience outside of academia and will enhance my education and professional background. As I mentioned before, my research interests are focused on mathematics, machine learning, and applications to environmental science. It's been challenging to clearly demonstrate how these fields intersect and their collective importance. I believe this program, with its interdisciplinary research areas, will help me better understand and feel more confident about my work. Also, I think I can see how people are addressing their interdisciplinary work and learn from them. Over the past year, I have had the opportunity to work with interdisciplinary applications, focusing on predicting greenhouse gas emissions in human-made aquatic ecosystems using machine learning, as well as developing statistical models for medical data. I have found fascinating the intersection between Mathematics and real world-problems that have global impact. I think being part of an internship program will be an incredible opportunity to learn more about it. Additionally, although I have experience with Python and R, an internship would enable me to further develop my programming skills and potentially support my ongoing research. Furthermore, participating in an internship will allow me to connect with more people to collaborate with and learn new techniques that can be also helpful for my dissertation project. On the other hand, I attended the BE Program in March at SIAM CSE25 and I believe this was one of the best experiences that I have had before. I had the opportunity to meet a lot of mentors from different National Labs and get mentoring from them. I am sure that every program at Sustainable Horizon Institute will provide me with this guidance and contribute to my career goals. In addition, one of my friends who participated in this program in 2023 got a job due to her participation. I strongly believe that the SPR program can definitely help me and contribute to the future of my career. Finally, as I'm getting close to finishing my PhD, meeting new collaborators in my field is really important. The SPR program looks like a great place to connect with others who have backgrounds in science and interdisciplinary research. It's a chance to meet new people to collaborate with. I strongly believe the SPR Summer Internship Program is an ideal fit for me. I believe having the opportunity to participate in such a program before my graduation will help me to increase the possibilities to get a job and make contributions after the graduation of my PhD program.

Lightning Talk Title

PhD Candidate Harnessing AI and Sparse Data for Life Sciences

Keywords (Maximum 20 words)

Machine Learning; Greenhouse Gas emissions; Environmental Modeling; Clinical Data, Mathematics; AI; Geospatial Data; Bayesian Models; Data Science for life sciences.