Dr. Miguel Angel Aguilar

- Optimization of AI models for efficient inference Embedded Systems - Focus on Perception Systems for highly automated driving and user experience

- Gave lectures on ``SoC Design'', ``Low-Power Design'' and ``Embedded Architectures''. - Supervised Master Theses

- Researched compiler technologies for homogeneous and heterogeneous multicore embedded systems. - Presented research results in 15 publications in renowned conferences, journals and books. - Contributed to research projects with academic and industrial partners. - Transfered technologies derived from research results into the industry. - Supervised multiple students in the context of internships and theses. - Assisted in teaching activities, including lecture exercises and laboratories

- Researched and developed software parallelization technologies based on LLVM and Clang - Contributed to product release cycles in terms of testing and bug fixing

- Working areas: Embedded Systems, Linux, Open Source Technologies. - Gave lectures on ``Introduction to Embedded Systems''

- Designed and developed Linux-based embedded systems of various application domains that were successfully deployed in the market - Designed and implemented Linux drivers and contributed to the Linux source tree - Developed and integrated application and low-level software - Developed SDKs for embedded SoCs - Hardware bring up - DSP software design and implementation on Texas Instruments DSPs of the family C6x in particular C64x+ and C67x - On-site and off-site customer support

Focus on Heterogeneous Multi-Core Embedded Systems. Dissertation: "Software Parallelization and Distribution for Heterogeneous Multi-Core Embedded Systems".

Master Thesis: "Retargeting MAPS to TI Multi-Core DSP Platforms for Real-Time Applications"

Thesis: Development of a Pre-processing Stage for Noise Reduction, Contrast and Sharpness Enhancement in Digitized Images of Electrophoresis Gels