Keynote Speakers

Trilce Estrada

Trilce Estrada

Trilce Estrada is an associate professor in the department of Computer Science at the University of New Mexico. She earned her PhD in 2012 from University of Delaware. Her research interests include self-managed distributed systems, Big Data analysis, crowd sourcing, and machine learning. Her overarching research goal is to solve computationally intensive and data intensive problems in science, health, and education, especially in scenarios where resources and trained professionals are scarce. She is also actively involved in improving participation of women in computing-related fields.

Her work for Accurate Scoring of Drug Conformations at the Extreme Scale won first place at the 2015 IEEE International Scalable Computing Challenge, a competition in which participants demonstrate working solutions to real-world problems that rely on large scale computing. In 2019 she was named the ACM SIGHPC Emerging Woman Leader in Technical

Computing. This award is presented to a woman in HPC every two years in recognition of impact as indicated by early career achievements and commitment to growing the HPC community through service and mentorship. She has been chair of multiple mentoring efforts, reaching over 400 students, including the PhD Forum and Student Program at IPDPS (2014-2018) and the Mentor Protege Program at SC (2019). Estrada obtained a PhD in Computer Science from the University of Delaware, a M.S in Computer Science from INAOE, Mexico and a B.S in Informatics from the Universidad de Guadalajara, Mexico.

 

 

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Liliana Barbosa Santillan

Liliana Barbosa Santillan

Liliana was awarded with several scholarships from the National Institute of Astrophysics, Optics and Electronics, the National Council of Science and Technology, Carolina Foundation, and Technical University of Madrid.

Liliana has presented conferences in different states in México, and Europe. She has collaborated applied research projects with a wide variety of organizations like National Institute of Astrophysics, Optics and Electronics; Ontology Engineering Group; The Computational logic, Languages, Implementation, and Parallelism Laboratory; Embedded and Real-Time Systems Collaborative Laboratory; FAO: Food and Agriculture Organization of the United Nations for a world without hunger; Mexican Army; the Ministry of the Economy and the State Council for Science and Technology of Jalisco; The TechBA Silicon Valley program, among others.

She has been member of the National Research System in Mexico (SNI I). Her research interests include semantic (web) applications, ontology systems, security, parallel programming with GPU, and quality software. Finally, She is the chairperson of www.dataminingengineeringgroup.net

 

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Ewa Deelman

Ewa Deelman

Her main area of research is distributed computing. She researches how to best support complex scientific applications on a variety of computational environments, including campus clusters, grids, and clouds. She has designed new algorithms for job scheduling, resource provisioning, and data storage optimization in the context of scientific workflows.

Since 2000, She has been conducting research in scientific workflows and has been leading the design and development of the Pegasus software that maps complex application workflows onto distributed resources. Pegasus is used by a broad community of researchers in astronomy, bioinformatics, earthquake science, gravitational-wave physics, limnology, and others.

She is also the Principal Investigator for the CI Compass, the NSF Cyberinfrastructure Center of Excellence, which provides leadership, expertise, and active support to cyberinfrastructure practitioners at NSF Major Facilities and throughout the research ecosystem in order to enable ongoing evolution of our technologies, our practices, and our field, ensuring the integrity and effectiveness of the cyberinfrastructure upon which research and discovery depend.

In addition, she is interested in issues of distributed data management, high-level application monitoring, and resource provisioning in grids and clouds.

 

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