Philippe Bich

PhD Student - Tiny Machine Learning, Machine Learning at the Edge, Robotics

Email: philippe.bich@polito.it
PhD Scolarship: Tiny Machine Learning For Satellite Applications
Website: link

Philippe is a PhD student in Electrical, Electronics and Communications Engineering at Politecnico di Torino (Italy) under the supervision of Professor Gianluca Setti. He obtained a Bachelor’s Degree in Computer Engineering at Politecnico di Torino in 2018 and in 2020 a Master’s Degree in Mechatronic Engineering with a thesis written under the supervision of Professor John Baillieul during his stay at Boston University (USA).
His research focuses now on Tiny Machine Learning which is one of the fastest‐growing areas of Deep Learning. TinyML is rapidly becoming more accessible and differs from mainstream machine learning because it requires not only software expertise, but also embedded‐hardware expertise.


Recent Publications since 2017 (6)

  1. Zuowen Wang, Chang Gao, Zongwei Wu, Marcos V. Conde, Radu Timofte, Shih-chii Liu, Qinyu Chen, Zheng-jun Zha, Wei Zhai, Han Han, Bohao Liao, Yuliang Wu, Zengyu Wan, Zhong Wang, Yang Cao, Ganchao Tan, Jinze Chen, Yan Ru Pei, Sasskia Brüers, Sébastien Crouzet, Douglas Mclelland, Oliver Coenen, Baoheng Zhang, Yizhao Gao, Jingyuan Li, Hayden Kwok-hay So, Philippe Bich, Chiara Boretti, Luciano Prono, Mircea Lică, David Dinucu-jianu, Cătălin Grîu, Xiaopeng Lin, Hongwei Ren, Bojun Cheng, Xinan Zhang, Valentin Vial, Anthony Yezzi, James Tsai (2024) Event-Based Eye Tracking. AIS 2024 Challenge Survey, In: Proceedings of 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pages 5810-5825, Type: Conference
  2. P. Bich, C. Boretti, L. Prono, F. Pareschi, R. Rovatti, G. Setti (2024) Optimizing Vision Transformers: Leveraging Max and Min Operations for Efficient Pruning, In: Proceedings of the 2024 IEEE 6th International Conference on AI Circuits and Systems (AICAS), pages 337-341, ISBN: 979-8-3503-8363-8, Type: Conference
  3. Philippe Bich, Luciano Prono, Mauro Mangia, Fabio Pareschi, Riccardo Rovatti, Gianluca Setti (2023) Multiply-And-Max/min Neurons at the Edge: Pruned Autoencoder Implementation, In: Proceedings of the 2023 IEEE 66th International Midwest Symposium on Circuits and Systems (MWSCAS), pages 629-633, ISBN: 979-8-3503-0210-3, Type: Conference
  4. Chiara Boretti, Philippe Bich, Fabio Pareschi, Luciano Prono, Riccardo Rovatti, Gianluca Setti (2023) PEDRo: an Event-based Dataset for Person Detection in Robotics, In: Proceedings of 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pages 4065-4070, ISBN: 979-8-3503-0249-3, Type: Conference
  5. Philippe Bich, Luciano Prono, Mauro Mangia, Fabio Pareschi, Riccardo Rovatti, Gianluca Setti (2022) Aggressively prunable MAM²-based Deep Neural Oracle for ECG acquisition by Compressed Sensing, In: Proceedings of the 2022 IEEE Biomedical Circuits and System Conference (BioCAS2022), pages 163-167, ISBN: 978-1-6654-6917-3, Type: Conference
  6. Chiara Boretti, Philippe Bich, Yanyu Zhang, John Baillieul (2022) Visual Navigation Using Sparse Optical Flow and Time-to-Transit, In: 2022 International Conference on Robotics and Automation (ICRA), pages 9397-9403, ISBN: 978-1-7281-9681-7, Type: Conference