Name: Carlos Fernando Gamboa
Pronouns:
Biography:
Carlos Fernando Gamboa is a member of the Scientific Data and Computing Center (SDCC) at Brookhaven National Laboratory, where he has cultivated a career in computing that spans diverse national and international scientific experiments. With a profound commitment to advancing scientific discovery, Carlos has been instrumental in supporting a wide array of distributed data systems within the SDCC. His expertise extends from robust database systems and digital repositories to the intricate world of mass storage systems. These systems often have a global reach, distributed across the world. Carlos Fernando is also associated with the Electrical and Computer Engineering department at Stony Brook University, where he enjoys teaching. Balancing his work life, Carlos Fernando takes time for his family. He enjoys hiking with his family and playing sports like volleyball, soccer, and ultimate frisbee. During COVID, he picked up running as a hobby and loves listening to music.
Institution/Lab: Brookhaven National Laboratory
Website:
SRP Collaboration Topic/Title: Data Storage for Scientific Experiments
Field or research area: Distributed Data Systems
Please select all the topical areas that apply to your project:
Computer Science (i.e., architectures, compilers/languages, networks, workflow/edge, experiment automation, containers, neuromorphic computing, programming models, operating systems, sustainable software); Data Science (i.e., data analytics, data management & storage systems, visualization); High-Performance Computing
Brief Abstract:
One of the missions of the Scientific Data and Computing Center (SDCC) at Brookhaven National Laboratory is to provide access to storage services for a diverse range of High Energy Physics (HEP) scientific experiments, including LHC-ATLAS[1], Belle2[2], and DUNE[3]. An aggregate of 222 million files and data storage totaling 76PB is distributed and managed by independent storage instances for each Virtual Organization (VO). The underlying technology used to support this storage is dCache [4]. Currently, we are in the process of evolving and reviewing event visualization and control schemes, as well as log analysis tools, to improve analytics and monitoring and ensure the high availability of this storage service. Additionally, we are interested in identifying state-of-the-art tools and techniques that allow us to anticipate or predict inefficient storage resource access or real time system component failures. Ultimately, these improvements will have a significant impact on advancing scientific discovery while optimizing storage resources. [1] https://home.cern/science/experiments/atlas [2] https://www.belle2.org [3] https://www.dunescience.org [4] https://www.dcache.org
Desired relevant skills, background, or interests:
Knowledge of: -Scripting languages like Python -Programing languages like Java -Operational Systems like Linux -Databases (Relational or non) -Document databases like Elasticserach -Artificial Intelligence techniques
Other comments:
Do any special requirements apply? U.S. Citizen Only; Permanent Resident OK
Other, specify:
Keywords:
storage; distributed data management; databases; networking; computing engineering; algorithms; Machine Learning; Artificial Intelligence; Data Science; security; optimization; data visualization
Lightning Talk Title: Two Decades of Exploration: A Journey through Data, Technology, and Personal Growth