+ Ricardo de Azambuja

I’m an Electrical Engineer with an MSc in Electrical Engineering / Automation, a PhD in A.I. / Robotics and experience that goes from electronics, web development, digital printing… to heavy machinery, 3D printing, artificial intelligence, computer vision and agricultural robotics. However, I’m not only used to technical fields because I even worked as a door-to-door salesman when I was publishing a monthly magazine!

Yep, I’ve done quite a lot of different things so far, I have lots of experience as an entrepreneur (managing people, taking care of accounting and legal bureaucracy, etc.) and now I’m eager for working with A.I. based robotics here in Montréal.

+ Current Projects

• Internet-of-Things Platform for Humanitarian Aid project where I’m currently working on automated landing for drone swarms.

+ Scholarships and Awards

• PhD Scholarship (2013-2017) - CAPES (four years).
• MSc Scholarship (2011-2012) - CAPES (two years).
• Undergraduate Research Scholarship (2000) - FAURGS (one year).
• Undergraduate Research Scholarship (1997-1998) - CNPq (two years).
• Selected to attend MILA (CIFAR) Deep / Reinforcement Learning Summer School (2017).
• Selected to attend Nengo-3rd annual summer school on large-scale brain modelling (2016).
• Selected to attend The 2014 CapoCaccia Cognitive Neuromorphic Engineering Workshop.

+ Select Publications

1. R. de Azambuja, V.J. Brusamarello, S. Haffner, and R. Wolff Porto. “Analysis and Optimization of an Inductive Power Transfer With a Randomized Method.” IEEE Transactions on Instrumentation and Measurement 63, no. 5 (May 2014): 1145–52. doi:10.1109/TIM.2013.2296397, Bibtex citation.
2. V. J. Brusamarello, Y. B. Blauth, R. de Azambuja, I. Muller, and F. R. de Sousa. “Power Transfer With an Inductive Link and Wireless Tuning.” IEEE Transactions on Instrumentation and Measurement 62, no. 5 (May 2013): 924–31. doi:10.1109/TIM.2013.2245041, Bibtex citation.
3. R. de Azambuja, F. B. Klein, M. F. Stoelen, S. V. Adams, and A. Cangelosi. “Graceful Degradation Under Noise on Brain Inspired Robot Controllers.” In Neural Information Processing, edited by Akira Hirose, Seiichi Ozawa, Kenji Doya, Kazushi Ikeda, Minho Lee, and Derong Liu, 195–204. Lecture Notes in Computer Science 9947. Springer International Publishing, 2016. doi:10.1007/978-3-319-46687-3_21, Bibtex citation, Github repository.
4. R. de Azambuja, A. Cangelosi, and S.V. Adams. “Diverse, Noisy and Parallel: A New Spiking Neural Network Approach for Humanoid Robot Control.” In 2016 International Joint Conference on Neural Networks (IJCNN), 1134–42. Vancouver, 2016. doi:10.1109/IJCNN.2016.7727325, Bibtex citation, Github repository.
5. R. W. Porto, V. J. Brusamarello, I. Muller, F. R. Sousa, and R. Azambuja. “Design and Optimization of a Power Inductive Link.” In Instrumentation and Measurement Technology Conference (I2MTC), 2014 IEEE International, 648–53. IEEE, 2014. doi:10.1109/I2MTC.2014.6860823, Bibtex citation.
6. R. Azambuja, V. J. Brusamarello, S. Haffner, and R. W. Porto. “Full Four Capacitor Circuit Compensation for Inductive Power Transfer.” In Instrumentation and Measurement Technology Conference (I2MTC), 2013 IEEE International, 183–187. IEEE, 2013. doi:10.1109/I2MTC.2013.6555406, Bibtex citation.
7. R. W. Porto, V. J. Brusamarello, R. Azambuja, and O. Frison. “Design and Analysis of a GMR Eddy Current Probe for NDT.” In Sensing Technology (ICST), 2013 Seventh International Conference on, 424–429. IEEE, 2013. doi:10.1109/ICSensT.2013.6727688, Bibtex citation.
8. V. J. Brusamarello, Y. B. Blauth, R. Azambuja, and I. Muller. “A Study on Inductive Power Transfer with Wireless Tuning.” In Instrumentation and Measurement Technology Conference (I2MTC), 2012 IEEE International, 1098–1103. IEEE, 2012. doi:10.1109/I2MTC.2012.6229372, Bibtex citation.
9. D. A. Sala, V. J. Brusamarello, R. de Azambuja and A. Cangelosi “Positioning Control on a Collaborative Robot by Sensor Fusion with Liquid State Machines.” In Instrumentation and Measurement Technology Conference (I2MTC), 2017 IEEE International. Milano, 2017. doi:10.1109/I2MTC.2017.7969728, Github repository.
10. R. de Azambuja, F.B. Klein, S.V. Adams, M.F. Stoelen and A. Cangelosi. “Short-Term Plasticity in a Liquid State Machine Biomimetic Robot Arm Controller.” In 2017 International Joint Conference on Neural Networks (IJCNN). Anchorage, 2017 doi:10.1109/IJCNN.2017.7966283, Github repository.
11. R. de Azambuja, D.H. García, M.F. Stoelen and A. Cangelosi. “Neurorobotic Simulations on the Degradation of Multiple Column Liquid State Machines.” In 2017 International Joint Conference on Neural Networks (IJCNN). Anchorage, 2017. doi:10.1109/IJCNN.2017.7965834, Github repository.
12. Stoelen, Martin F., Ricardo de Azambuja, and Angelo Cangelosi. “A Physical Architecture for Studying Embodiment and Compliance: The GummiArm.” Cognitive Robot Architectures (2017): 68. Final version Eucognition.org
13. Abdulla Mohamed, Phil F. Culverhouse, Ricardo De Azambuja, Angelo Cangelosi, Chenguang Yang. “Automating Active Stereo Vision Calibration Process with Cobots.” In IFAC-PapersOnLine Volume 50, Issue 2, December 2017. doi:10.1016/j.ifacol.2017.12.030, Final version - IFAC-PapersOnLine.

+ Contact Information and Links

• Contact Ricardo by email: ricardo {dot} azambuja {at} gmail {dot} com

• Or find him on Google Scholar, GitHub, and LinkedIn

• Personal Website