معرفی
Trilce Estrada is an Associate Professor in the Department of Computer Science at the University of New Mexico (UNM), School of Engineering. She leads the Data Science Laboratory and is actively involved in research, teaching, and service. Her work focuses on solving data- and compute-intensive problems in science, health, and education, particularly in resource-constrained environments.
Her research interests include:
- Machine Learning and scalable learning techniques
- Big Data analytics and distributed systems
- High Performance Computing and cyberinfrastructure
- In-situ data analytics for scientific workflows
- Pervasive healthcare using mobile and distributed systems
Although no publication list is provided, her current research projects indicate a strong focus on distributed learning, in-situ analysis for molecular dynamics, cyberinfrastructure optimization, and robust science in high-throughput computing. These projects reflect interdisciplinary collaboration and a commitment to scalable, reproducible, and impactful computing solutions.
Dr. Estrada has served in numerous leadership roles in major computing conferences, including as Program Co-Chair for IEEE Cluster 2022, Chair of the Mentor-Protégé Program at SC19, and Chair of the IPDPS PhD Forum and Student Program for multiple years. She has also been active in NSF panels and curriculum development, particularly in integrating Big Data into educational frameworks.
She is committed to mentoring and improving diversity in computing, serving as faculty advisor for Women in Computing and CSGSA, and participating in outreach to attract underrepresented groups to computer science. She currently oversees a research group but is not accepting new students due to capacity. Independent study opportunities are available under strict eligibility criteria.
Her lab, the Data Science Laboratory, supports interdisciplinary research in data-intensive domains. She is also involved in educational initiatives and curriculum development at UNM and nationally.
