- BS, Computer Engineering, King Fahd University of Petroleum and Minerals (KFUMP) 2005-2009
- MS, Computer Science, King Abdullah University of Science and Technology (KAUST) 2009-2011 Thesis title: “TMAC: Timestamp-Ordered MAC for CSMA/CA Wireless Mesh Networks”
- PhD Computer Science, UC Santa Barbara (2012-2015)
Honors & Awards
- Academic Senate Travel Grant UC Santa Barbara 2015 The Doctoral Student Travel Grant awards travel funds to graduate students who have been invited or selected to present a paper, present research, perform or exhibit at a major professional conference or meeting.
- ICDE 2015 Travel Scholarship 2015
- Outstanding publication award UCSB’s computer science department 2015. An annual award for the best publication authored by a student in UC Santa Barbara's computer science department.
- SIGMOD 2015 Travel Award 2015
- “Best papers of ICDE” invitation to a special issue of TKDE 2015
- Best presentation award at the Graduate Students Workshop on Computing UCSB October 2014
- Outstanding TA award UCSB February 2014Academic excellence award KAUST 2010
- Graduate Fellowship KAUST 2009
- Discovery scholarship KAUST 2008
Faisal Nawab graduated with an MS degree in Computer Science from King Abdullah University of Science and Technology (KAUST) in 2011. Nawab currently works as an Assistant Professor of computer science and engineering in the Department of Computer Science and Engineering at the University of California, Santa Cruz, where he works on developing systems for quick and accurate data analysis of new applications in cloud computing and Big Data.
Education and Early Career
Nawab earned a B.S degree in Computer Science from the KFUPM (King Fahd University of Petroleum and Minerals). He then studied Computer Science at KAUST where he obtained an M.S degree. He continued his studies at the UC Santa Barbara University from which obtained a Ph.D. Degree in Computer Science. After graduate studies, Faisal worked as a Research Intern at Microsoft, where he worked in the database group under the supervision of Dr. David Lomet. He then worked as a Research Associate in HP Labs where he focused on designing data stores for non-volatile memory architectures. He studied the implications of emerging flush-on-fail CPU technology on the durability cost of transactions. He also worked on a design of a data store that improves performance by avoiding two main overhead sources: logging and cache-line flushing.
Faisal Nawab's research lies at the intersection of Big Data management and distributed Cloud Computing systems. Specifically, he works on data management systems that accelerate and support data science and global connectivity especially in the context of autonomous, mobile applications and the Internet of Things.
Data processing is the driver of the sustained growth and impact of Internet services and Big Data analytics. The global nature of users and data invites a Global-Scale Data Management paradigm. Faisal's main areas of work and study are related to build global-scale systems with a focus on providing high performance and easy-to-use database abstractions.
Looking forward, two trends in computing will increase the demand on Global-Scale Data Management drastically and will ignite a transformation of data management systems. The first trend is the emergence of Device-driven systems for autonomous applications, Internet of Things (IoT), and mobile agents (self-driving cars and robotics). The second trend is the emergence of Data-driven applications such as data science and machine learning. Faisal's ongoing work explores the opportunities and challenges in supporting the increasing demand of device-driven systems by augmenting data management systems with edge computing technology to increase and diversify resources. Also, exploring domain-specific system designs to support the complexity of emerging data-driven applications is one of his main research areas.