Jerjes Aguirre-Chavez is a Data Science PhD student at the Halıcıoğlu Data Science Institute, University of California, San Diego. His research interests include responsible machine learning, data mining, and the application of artificial intelligence in clinical decision-making and scientific discovery. Currently, he is performing a rotation in the AiDA Lab with Professor Albert Hsiao, working on visual-language models as tools for clinical decision-making. Previously, he conducted a rotation in the Smarr Lab, where he researched the detection, classification, and characterization of COVID recovery patterns. Before that, he was part of the Voytek Lab, exploring the use of Large Language Models (LLMs) to advance neuroscience research. Prior to his PhD, Jerjes worked as a Data Scientist II at ClimateAi, focusing on climate risk management, hurricane forecasting, and flood forecasting.

Interests
  • Artificial Intelligence
  • Precision Healthcare
  • Responsible Machine Learning
  • AI for Scientific Discovery
Education

  • PhD in Data Science, 2029 (expected)

    University of California, San Diego

  • BSc in Engineering Physics, 2022

    Tecnológico de Monterrey

Experience

 
 
 
 
 
Graduate Student Researcher
Halıcıoğlu Data Science Institute, University of California San Diego
September 2024 – Present La Jolla, CA
  • Conducting research on vision-language models for medical imaging data detection and interpretation.
  • Created vision-language models for scientific discovery based on neuroscience literature.
  • Investigated the effects of long covid through the study of individual health states and transitions.
 
 
 
 
 
Data Scientist II
ClimateAi
February 2024 – September 2024 Remote
  • Designed and implemented custom dashboards tailored to client requirements, covering critical topics such as wildfires, hurricanes, and various agronomic issues.
  • Developed algorithms to aggregate climate projection data specifically for hydrological basins, enhancing data accuracy and usability.
  • Created comprehensive climate risk analysis report guidelines, ensuring stakeholders have clear and actionable insights for decision-making.
 
 
 
 
 
Data Scientist I
ClimateAi
January 2023 – February 2024 Remote
  • Created tailored datasets for various clients to assess climate-related risks, focusing on areas such as pests, diseases, sunshine hours, and heat stress.
  • Successfully migrated and adapted the existing codebase from Google Cloud to Amazon Web Services, ensuring seamless transition and improved performance.
  • Developed advanced algorithms for post-processing high-resolution global climate projection variables, optimizing computing resource usage and efficiency.
 
 
 
 
 
Software Engineer
Deal Engine
August 2022 – January 2023 Remote
  • Developed advanced Natural Language Processing (NLP) algorithms to infer tax-related rules for various countries and airlines.
  • Managed and controlled source code versions effectively using Git, ensuring code integrity and collaboration.
  • Built, accessed, and maintained robust databases using SQL, ensuring data accuracy and availability.

Recent Publications

Yun, Hyuk Jin, Lee, Han-Jui, You, Sungmin, Lee, Joo Young, Aguirre-Chavez, Jerjes, Vasung, Lana, Lee, Hyun Ju, Tarui, Tomo, Feldman, Henry A., Grant, P. Ellen, Im, Kiho (2025). Deep Learning–based Brain Age Prediction Using MRI to Identify Fetuses with Cerebral Ventriculomegaly. Deep Learning–based Brain Age Prediction Using MRI to Identify Fetuses with Cerebral Ventriculomegaly.

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Photo Gallery

I’ve always liked taking pictures of sunsets, flowers and the sea. Recently I decided to try to up my game, and here you can see a little of the pictures I’ve taken so far. Not an expert at all, but I do love taking pictures of pretty things.

See the full gallery

Preview Image

Contact

Hi there! I’m always excited to chat about research, collaborations, or talk about grad school in general. Whatever’s on your mind, feel free to drop me a line— I’m here to help and share ideas.