معرفی
Olac Fuentes is an Associate Professor in the Computer Science Department at the University of Texas at El Paso. His primary research focuses on developing machine learning systems for scientific data analysis, with applications in astronomy, geology, biology, and optics. He specializes in leveraging unlabeled data, active learning, feature selection, and noise-aware algorithms to extract insights from complex datasets.
Education:
- B.S. in Industrial Engineering from Instituto Tecnológico de Chihuahua
- M.S. in Computer Science from University of Texas at El Paso
- Ph.D. in Computer Science from University of Rochester
Research Focus: Dr. Fuentes develops intelligent systems for interdisciplinary scientific challenges. His work spans machine learning theory (optimization, noise handling) and applied domains including: computer vision for environmental monitoring (Arctic change detection, glacier segmentation), neuroinformatics (brain mapping), and multimodal data fusion (prosodic analysis for communication disorders). He frequently employs deep neural networks, active learning, and novel regularization techniques.
Publication Trends: Recent works demonstrate strong cross-disciplinary focus on climate science (satellite image analysis for coastal erosion), biomedical applications (neuroanatomy mapping, histology), and fundamental ML theory. His publications consistently integrate advanced neural architectures (CNNs, LSTMs) with domain-specific challenges in geosciences, neuroscience, and linguistics.
