Paola Pesantez-Cabrera

Paola Pesantez-Cabrera is a Research Assistant Professor in the School of Electrical Engineering and Computer Science at Washington State University. She is also the data manager/scientist for the AgAID Institute - AI for Transforming Workforce and Decision Support in Agriculture and the Soil Health Initiative (SHI). She is driven, innovative thinker, detailed oriented, and lifelong learner. She is a experienced team leader, researcher, and teacher with a proven track record of implementing unique methodologies to difficult problem sets to deliver exceptional results. She is interested in the development of artificial intelligence and machine learning applications with a direct impact in agriculture and its environmental and economical sustainability. She is an avid advocate of accessible education, generation of knowledge, respect for diversity, and visualization and engagement of Latin American women in STEM.

Favorite quotes:

“Knowledge, like air, is vital to life. Like air, no one should be denied it.” - Alan Moore, V for Vendetta
“Everybody is a genius. But if you judge a fish by its ability to climb a tree, it will live its whole life believing that it is stupid.” - Albert Einstein

Recent Publications

AIAFS (accepted)

Multi-Task Learning for Budbreak Prediction

Aseem Saxena, Paola Pesantez-Cabrera, Rohan Ballapragada, Markus Keller, and Alan Fern

2023

Bib

@article{saxena_grape_budbreak_2023,
  title = {Multi-Task Learning for Budbreak Prediction},
  publisher = {arXiv},
  author = {Saxena, Aseem and Pesantez-Cabrera, Paola and Ballapragada, Rohan and Keller, Markus and Fern, Alan},
  year = {2023},
  keywords = {Computer Science - Machine Learning},
  annote = {Comment: 4 pages, submitted to 2023 AAAI Workshop on Agriculture and Food Systems (AIAFS)},
}

AIAFS (accepted)

Persistent Homology to Study Cold Hardiness of Grape Cultivars

Welankar Sejal, Paola Pesantez-Cabrera, Bala Krishnamoorthy, Lynn Mills, Markus Keller, and Ananth Kalyanaraman

2023

Bib

@article{welankar_grape_2023,
  title = {Persistent Homology to Study Cold Hardiness of Grape Cultivars},
  url = {https://doi.org/10.48550/arXiv.2302.05600},
  publisher = {arXiv},
  author = {Sejal, Welankar and Pesantez-Cabrera, Paola and Krishnamoorthy, Bala and Mills, Lynn and Keller, Markus and Kalyanaraman, Ananth},
  year = {2023},
  keywords = {Computer Science - Machine Learning},
  annote = {Comment: 4 pages, submitted to 2023 AAAI Workshop on Agriculture and Food Systems (AIAFS)},
}

AAAI (accepted)

Grape Cold Hardiness Prediction via Multi-Task Learning

Aseem Saxena, Paola Pesantez-Cabrera, Rohan Ballapragada, Kin-Ho Lam, Markus Keller, and Alan Fern

2023

Bib

@article{saxena_grape_coldhardiness_2023,
  doi = {10.48550/ARXIV.2209.10585},
  author = {Saxena, Aseem and Pesantez-Cabrera, Paola and Ballapragada, Rohan and Lam, Kin-Ho and Keller, Markus and Fern, Alan},
  keywords = {Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences},
  title = {Grape Cold Hardiness Prediction via Multi-Task Learning},
  publisher = {arXiv},
  year = {2023},
  copyright = {Creative Commons Attribution 4.0 International},
}