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Dr Felix Cuadrado

Felix

Senior Lecturer

Email: felix.cuadrado@qmul.ac.uk
Telephone: +44 20 7882 5819
Room Number: Engineering, Eng 153a
Website: http://www.eecs.qmul.ac.uk/~fcuadrado
Office Hours: Tuesday 14:00-16:00

Teaching

Big Data Processing (Undergraduate)

Parallel computing, which implies the simultaneous execution of several processes for solving a single problem, is a mainstream subject with wide ranging implications for computer architecture, algorithms design and programming. The UK has been at the forefront of this technology through its involvement in the development of several innovative architectures. Queen Mary has been actively involved with Parallel Computing for more than a decade. In this module, you will be introduced to parallel computing and will gain first hand experience in relevant techniques. Laboratory work will be based on the MPI (Message Passing Interfaces) standard, running on a network of PCs in the teaching laboratory. The module should be of interest to Computer Scientists and those following joint programmes (eg CS/Maths, CS/Stats). It is also suitable for Chemistry and Engineering students and all those who are concerned with the application of high performance parallel computing for their particular field of study (eg Simulation of chemical Behaviour). The 12-week module involves two hours of timetabled lectures per week. Laboratory sessions are timetabled at two hours per week, normally spanning half the semester only. The module syllabus adopts a hands-on programming stance. In addition, it focuses on algorithms and architectures to familiarise you with messagepassing systems (MPI) as adopted by the industry.

Big Data Processing (Postgraduate)

The 12 week module involves 2 hours of timetabled lectures per week. Laboratory sessions are timetabled at 2 hours per week for 6 to 7 weeks only. The module syllabus adopts a hands-on programming stance. In addition it focuses on algorithms and architectures to familiarise students with message-passing systems ((MPI) as adopted by industry. Parallel computing, which implies the simultaneous execution of several processes for solving a single problem, is a mainstream subject with wide ranging implications for computer architecture, algorithms design and programming. The UK has been at the forefront of this technology through its involvement in the development of several innovative architectures. Queen Mary has been involved with Parallel Computing for more than a decade. In this module, students will be introduced to parallel computing and will gain firsthand experience in relevant techniques.

Cloud Computing (Postgraduate)

Cloud Computing has transformed how services and applications are delivered. Thanks to the rise of virtualisation technology and new programming paradigms, applications can quickly be delivered to a growing audience, without the need to physically own and configure the infrastructure. The Cloud Computing module will cover the main characteristics of Cloud Computing, including the enabling technologies, main software and service paradigms underpinning it, as well as related aspects, namely security, privacy, ethical concerns

Internet Protocols and Applications (Undergraduate)

This module builds upon the Programming Fundamentals and Telecoms and Internet Fundamentals modules, introducing you to the major Internet applications. It focuses on the TCP/IP protocol suite from OSI layers 5 through to 7, though some appreciation is given to transport layer protocols as part of the socket-programming topic.

Research

Research Interests:

 Cloud computing, Big Data Computing, Autonomic Computing

Publications

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