David Atienza Alonso

photo placeholder image

Scientific Director

david.atienza@epfl.ch +41 21 693 11 31 http://esl.epfl.ch/

Citizenship: Spanish and Swiss

EPFL VPA ECOCLOUD-GE
ELG 131 (Bâtiment ELG)
Station 11
CH-1015 Lausanne

Web site:  Web site:  https://ecocloud.ch

EPFL STI SEL-GE
ELG 130 (Bâtiment ELG)
Station 11
CH-1015 Lausanne

vCard
Administrative data

Fields of expertise

Internet of Things (IoT) and edge computing design, embedded systems design, 2D/3D thermal modeling and management for multi-processor system-on-chip (MPSoc), electronic design automation (EDA), wireless body sensor networks (WBSN), memory optimizations, low-power hardware and software co-design, embedded machine learning.

Publications

Selected publications

Other publications

Teaching & PhD

Teaching

Electrical and Electronics Engineering

PhD Programs

Doctoral Program in Electrical Engineering

Doctoral Program in Microsystems and Microelectronics

Courses

Microprogrammed Embedded Systems

The student will get to know the architecture of microprogrammed embedded systems, including the microprocessor architecture, memory hierarchy and different input/output peripherals, using as case study the Nintendo DS portable platform.

Lab on hardware-software digital systems codesign

During the course, we cover the design of multi-core embedded systems running Linux on an FPGA. Students learn how to develop hardware-software co-design solutions for complex tasks using high-level synthesis languages. We cover debugging co-designed embedded systems with integrated logic analyzers.

Lab on app development for tablets and smartphones

This course focuses on mobile application programming for the Android ecosystem. Students learn to develop distributed Apps on mobile platforms, interfacing with multiple heterogeneous devices and the cloud. Students receive tablets and smartwatches, and can use their own Android devices if desired.

Design and Optimization of Internet-of-Things Systems

This course provides an overview of the relevant technologies and approaches for the design and optimization of Internet-of-Things (IoT) systems. It covers architectures of edge computing platforms, wireless communication options, cloud computing backend and different machine learning applications.