Javier Lopez Randulfe
Place of employment
Informatics 6 - Chair of Robotics, Artificial Intelligence and Real-time Systems (Prof. Knoll)
Parkring 13. Room HB 2.02.19
85748 Garching b. München
- Phone: +49 (89) 289 - 17633
Javier is a research assistant at the chair of Robotics, Artificial Intelligence and Real-time Systems (I6). He joined the group in October 2019.
He received a master in Electrical Engineering in 2014 from the University of Vigo, and a master in Robot Systems from the University of Southern Denmark (SDU) in 2019. He has previously worked as a researcher within the fields of medical image processing and mobile robots. He also has experience in industry, namely in the automotive sector.
He is currently involved in the KI-ASIC project developing neuromorphic solutions for the processing of radar signals in the autnomous driving field. His main work right now consists in the design and implementation of Spiking Neural Network algorithms and topologies.
My main fields of interest are the following:
- Neuromorphic engineering, with a focus on Spiking Neural Networks
- Mobile robots and drone technology
- Computer science and AI
At the moment, there are no specific thesis proposals offered. However, feel free to contact me if you are interested in doing a thesis within the aforementioned fields of interest. I would be specially interested in supervising a thesis related to my main work on radar signal processing using SNNs, which is mentioned in the previous section.
López-Randulfe, J., Duswald, T., Bing, Z., and Knoll A. "Spiking Neural Network for Fourier Transform and Object Detection for Automotive Radar." Frontiers in Neurorobotics 15 (2021)
López-Randulfe, J., Rodríguez-Andina, J.J., and Fariña, J.. "UviSpace—A multidisciplinary PBL system based on mobile robots." IECON 2017-43rd Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2017.
López-Randulfe, J., Veiga, C., Rodríguez-Andina, J.J., and Farina; J. "A quantitative method for selecting denoising filters, based on a new edge-sensitive metric." 2017 IEEE International Conference on Industrial Technology (ICIT). IEEE, 2017.