Emanuele Valpreda

Ph.D. in Ingegneria Elettrica, Elettronica E Delle Comunicazioni , 36th cycle (2020-2023)

Ph.D. obtained in 2024

Dissertation:

Hardware/Neural Network Codesign for Energy-Efficient Inference on Edge Devices with Optimal Mapping and Compression (Abstract)

Tutors:

Maurizio Martina Guido Masera

Research presentation:

Poster

Profile

Research topic

Optimized acceleration of deep neural networks on edge devices

Research interests

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

Biography

Emanuele Valpreda received the B.S. and M.S. (honors) degrees in electrical and electronics engineering from the Polytechnic University of Turin, in 2017 and 2019 respectively, where he is now pursuing the Ph.D. degree on energy efficient neural network acceleration for edge computing, under the supervision of Prof. Maurizio Martina. He worked from 2019 to 2022 with the Chair of Integrated Systems (LIS) at the Technical University of Munich (TUM), initially as a student and then as a guest researcher. His current research interests include neural network compression, reliability and approximate computing.


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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