Beatrice Bussolino Pangerz

Ph.D. in Ingegneria Elettrica, Elettronica E Delle Comunicazioni , 35th cycle (2019-2022)

Ph.D. obtained in 2023

Dissertation:

Techniques and Optimization Strategies for Efficient Hardware Acceleration of Neural Networks: Tap-Wisely-Quantized Winograd Algorithm and Capsule Networks (Abstract)

Tutors:

Maurizio Martina

Research presentation:

Video presentation

Profile

Research topic

Hardware accelerators for Deep Neural Networks training and inference

Research interests

Big Data, Machine Learning, Neural Networks and Data Science
VLSI theory, design and applications

Biography

Beatrice Bussolino received the B.Sc. and M.Sc. degrees in Electronic Engineering, in 2017 and 2019 respectively, at Politecnico di Torino, where she is now pursuing the Ph.D. degree in Electrical, Electronics and Communications Engineering under the supervision of Prof. Maurizio Martina. Her current research activity is in the field of Machine Learning and Deep Neural Networks (DNNs) in particular. Working in close collaboration with the Technical University of Vienna (TUWien) and Prof. Muhammad Shafique, the aim is the design of dedicated on-chip architectures for inference and training of DNNs, with a comprehensive approach from the model and its possible optimizations to the physical implementation.

Teaching

Teachings

Master of Science

MostraNascondi A.A. passati

Bachelor of Science

MostraNascondi A.A. passati

Publications

Works published during the Ph.D. View all publications in Porto@Iris

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