# Fábio Henrique Nishihara > researcher in Brazil **Wikidata**: [Q138025596](https://www.wikidata.org/wiki/Q138025596) **Source**: https://4ort.xyz/entity/fabio-henrique-nishihara ## Summary Fábio Henrique Nishihara is a Brazilian researcher in the field of computer science, specializing in parallel computing. Affiliated with the University of São Paulo (USP), he is associated with the Institute of Mathematics, Statistics and Computer Science (IME-USP), where he completed his master's degree in 2008 under the supervision of Alfredo Goldman Vel Lejbman. ## Biography - **Born:** [Data not available in source] - **Nationality:** Brazil - **Education:** Master's degree in Computer Science, Institute of Mathematics, Statistics and Computer Science, University of São Paulo (IME-USP) (2008) - **Known for:** Research in computer science and parallel computing - **Employer(s):** University of São Paulo; Institute of Mathematics, Statistics and Computer Science (IME-USP); Department of Computer Science (IME-USP) - **Field(s):** Computer Science; Parallel Computing - **Aliases:** Fábio H. Nishihara, Fábio Nishihara ## Contributions Fábio Henrique Nishihara has contributed to the academic and research community through his work at the University of São Paulo. His academic trajectory includes the completion of a master's degree in computer science in 2008 at the Institute of Mathematics, Statistics and Computer Science (IME-USP). During this period, he conducted research under the mentorship of Alfredo Goldman Vel Lejbman, a relationship that highlights his connection to established figures in Brazilian computer science. His professional focus lies in **parallel computing**, a field within computer science essential for high-performance processing and algorithm efficiency. He operates out of the Department of Computer Science at IME-USP, a unit recognized for its significant role in teaching, research, and extension since its inception in 1970. Nishihara is also included in the focus list of the "Bibliotecas da USP GLAM project," indicating his relevance to the documentation and open knowledge initiatives associated with the University of São Paulo's library system. His work helps advance the study of algorithms and statistical models, particularly in how systems handle tasks without explicit instructions (relating to the broader context of machine learning and computation studies). ## FAQs ### Q: What is Fábio Henrique Nishihara's area of expertise? A: His primary field of work is computer science, with a specific focus on parallel computing. ### Q: Where does Fábio Henrique Nishihara conduct his research? A: He is affiliated with the Institute of Mathematics, Statistics and Computer Science (IME-USP) and the Department of Computer Science at the University of São Paulo in Brazil. ### Q: Who was Fábio Henrique Nishihara's academic advisor? A: He studied under Alfredo Goldman Vel Lejbman during his master's degree program, which he completed in 2008. ## Why They Matter Fábio Henrique Nishihara represents the ongoing academic rigor present within Brazil's leading higher education institution, the University of São Paulo. His work in **parallel computing** is vital to the advancement of modern computational efficiency, allowing for the execution of complex tasks simultaneously rather than sequentially. This field is foundational to the performance of supercomputers and modern data centers. By engaging in research at IME-USP, a unit with a history dating back to 1970, Nishihara contributes to a legacy of scientific study regarding algorithms and statistical models. His association with the Department of Computer Science places him within a network of researchers pushing the boundaries of how computers process information. Furthermore, his recognition by the Bibliotecas da USP GLAM project underscores the importance of his academic profile in the open knowledge landscape, ensuring that researchers in Brazilian computer science are documented and accessible. ## Notable For * **Specialization in Parallel Computing:** Focuses on a critical sub-field of computer science dedicated to improving processing speeds and algorithm efficiency. * **Affiliation with IME-USP:** Connected to one of Brazil's foremost institutes for mathematics and computer science. * **Academic Lineage:** Studied under Alfredo Goldman Vel Lejbman, establishing a link to prominent Brazilian computer science academia. * **GLAM Project Inclusion:** Recognized by the Bibliotecas da USP GLAM project, highlighting his relevance in cultural and academic metadata. ## Body ### Academic Background Fábio Henrique Nishihara pursued his higher education at the **Institute of Mathematics, Statistics and Computer Science, University of São Paulo (IME-USP)**. He successfully completed his **master's degree in computer science** in **2008**. His academic training is characterized by his mentorship under **Alfredo Goldman Vel Lejbman**, a notable researcher in the field. ### Research and Affiliations Nishihara operates as a researcher within the **Department of Computer Science (IME-USP)**. His professional identity is strongly tied to the **University of São Paulo**, a major hub for research in Brazil. * **Field of Work:** His research concentrates on **computer science**, specifically **parallel computing**. This involves the study of computation and algorithm designs that allow for simultaneous processing. * **Related Concepts:** His work is contextually linked to **machine learning**, defined as the scientific study of algorithms and statistical models used to perform tasks without explicit instructions. ### Institutional Context The institution he is affiliated with, IME-USP, is a teaching, research, and extension unit founded on **January 15, 1970**. It serves as a central pillar for computational study in Brazil. Nishihara’s presence on the **on focus list of wikimedia project** (specifically the Bibliotecas da USP GLAM project) indicates his active participation or documentation within the university's academic and cultural outreach initiatives. ## References 1. [Source](https://teses.usp.br/teses/disponiveis/45/45134/tde-20220712-122508/es.php)