About me
I am a graduate student in computer science. I'm a pre-doctoral fellow at the IdBIS research group at the University of Granada (UGR). My research lies at the intersection between machine learning (ML) and natural language processing (NLP). The main goal is twofold: (1) tackle the challenge of working jointly with heterogeneous data in specialized-domain applications where data of any kind and detail level is involved; (2) the development of intelligent systems for domain adaptation applied to several scenarios, such as nutrition, health, and well-being.
Before starting my Ph.D. I worked for three years as a hired CS researcher at the H2020 Project Stance4Health in the development of an intelligent nutrition service. During this time, I got a Ms. Degree in computer engineering and a Ms. Degree in Data Science, both carried out at UGR as well.
My journey into data science started during my bachelor's degree in computer engineering at the UGR when I discovered that developing models and analyzing results were the topics I enjoyed the most. I ended up specializing in computing and intelligent systems, and my eagerness to learn and work with data models has continued until this day.
Scientific communication I actively participate in dissemination and scientific communication activities, such as s artificial intelligence workshops and international conferences. I also have participated in the dissemination of research activities intended for the general public (such as European Researchers' Night 2022), universities, and secondary schools. I have been selected as an oral speaker/workshop at the national conference on Python Programming (PyConES), organized by the Spanish Python Association. I also was recently invited as an oral speaker in PyData-Granada to share my recent research activities with the open-source Python community in Granada.
Journal papers
- Morales-Garzón, A., Gutiérrez-Batista, K., & Martin-Bautista, M. J. (2023). Link prediction in food heterogeneous graphs for personalised recipe recommendation based on user interactions and dietary restrictions. Computing, 1-23.
- Morales-Garzón, A., Gómez-Romero, J., & Martin-Bautista, M. J. (2021). A Word Embedding-Based Method for Unsupervised Adaptation of Cooking Recipes. IEEE Access, 9, 27389-27404.
Conference papers
- Morales-Garzón, A., Sánchez-Pérez, G. M., Sierra, J. C., & Martin-Bautista, M. J. (2023, September). The Promise of Query Answering Systems in Sexuality Studies: Current State, Challenges and Limitations In International Conference on Flexible Query Answering Systems (pp. 39-49). Cham: Springer Nature Switzerland.
- Morales-Garzón, A., Morcillo-Jimenez, R., Gutiérrez-Batista, K., & Martin-Bautista, M. J. (2023, September). How Tasty Is This Dish? Studying User-Recipe Interactions with a Rating Prediction Algorithm and Graph Neural Networks In International Conference on Flexible Query Answering Systems (pp. 107-117). Cham: Springer Nature Switzerland.
- Morales-Garzón, A., Gómez-Romero, J., & Martin-Bautista, M. J. (2022, July). Contextual sentence embeddings for obtaining food recipe versions In International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems
- Morales-Garzón, A., Gómez-Romero, J., & Martin-Bautista, M. J. (2021, April). Semantic-aware transformation of short texts using word embeddings: An application in the Food Computing domain. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop (pp. 148-154).
- Morales-Garzón, A., Gómez-Romero, J., & Martin-Bautista, M. J. (2020, June). A word embedding model for mapping food composition databases using fuzzy logic. In International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (pp. 635-647). Springer, Cham.
Grants
Awards
