Luca Savant Aira

Dottorando in Ingegneria Elettrica, Elettronica E Delle Comunicazioni , 38o ciclo (2022-2025)
Dipartimento di Elettronica e Telecomunicazioni (DET)

Profilo

Dottorato di ricerca

Argomento di ricerca

Multi-image restoration exploiting neural implicit world models

Tutori

Interessi di ricerca

Big Data, Machine Learning, Neural Networks and Data Science
Multimedia Signal Processing

Biografia

I am currently a Ph.D. candidate at the IPL group at Politecnico di Torino, specializing in multi-image restoration by exploiting neural implicit world models. This research allows me to delve into cutting-edge techniques and contribute to the advancement of knowledge in this field.
Prior to my Ph.D., I earned a Master's Degree in Mathematical Engineering from Politecnico di Torino in 2021/2022, with a focus on Statistics and Optimization of Networks. My master's thesis, "Job Scheduling on uniform machines: approximation ratios by computer-assisted proofs," showcased my ability to employ innovative approaches, including computer-assisted proof methods, to achieve accurate and reliable results.
I hold a Bachelor's Degree in Mathematics for Engineering, earned in the period 2017/2020, also from Politecnico di Torino, where I graduated with a thesis titled "Machine Learning Performance Analysis for Discrete Fracture Networks," earning a grade of 110L/110.
My academic journey has instilled in me a profound passion for logic and scientific rigor. I am particularly interested in Machine Learning and Deep Learning, with a focus on neural architectures. Additionally, my expertise extends to Geometry, including Linear Algebra, Topology, and Differential Geometry, as well as Optimization through Mathematical Programming. This multidisciplinary background positions me as a versatile professional ready to contribute to advancements at the intersection of mathematics and technology.

Didattica

Insegnamenti

Corso di laurea magistrale