Papers
5
Total Citations
71
H-Index
3
About
Guillermo Botella is a researcher whose work bridges the gap between high-performance computing and inclusive education, with a primary focus on embedded systems, real-time motion estimation, and STEAM pedagogy. His major contributions lie in the development of low-power, hardware-accelerated motion estimation and optical flow algorithms for autonomous systems, as demonstrated by his most-cited work on a low-cost matching motion estimation sensor implemented on an FPGA and NIOS II microprocessor (34 citations). He has also advanced robust motion estimation on multi-core DSPs for robot navigation, showcasing his expertise in efficient, real-time embedded vision. Beyond hardware, Botella is a leading advocate for diversity in STEAM, co-authoring influential papers on educational robotics for all genders and backgrounds (22 citations) and developing the MOOC "STEAM4ALL" to promote inclusive robotics education. His work not only pushes the boundaries of embedded vision processing but also ensures that the next generation of engineers is diverse and equipped with computational thinking tools.
Research Focus
Key Achievements
Top Papers
- 1
- 2Educational Robotics for All: Gender, Diversity, and Inclusion in STEAM22 citations · 2020
- 3Robust motion estimation on a low-power multi-core DSP11 citations · 2013
- 4Gender and STEAM as part of the MOOC STEAM4ALL2 citations · 2021
- 5Real-Time Motion Processing Estimation Methods in Embedded Systems2 citations · 2012