PitchD 2020 edition: the second PitchD

29 January 2020 – 5.30 PM
Politecnico di Torino – Maxwell Room

Here’s the second PitchD – the PhD’s pitch of the new 2020 edition. Our PhD IEEE Student Members explain to students, colleagues and professors their research. For the second event, two PhD students with an electronics background will show insight into their work. Join us to listen to their PitchD.

CMOS Electronics readout for radiation detector at cryogenic temperature

Mr. Alejandro Martinez
Dept. of Electronics and Telecommunications (DET), Politecnico di Torino
Istituto Nazionale di Fisica Nucleare, Torino

Cryogenic CMOS electronic could provide an important impact in the current conventional electronic applications, since this can offer important device performance improvements, in term of RMS noise, power consumption and speed. In the nuclear physics area, the underground astroparticle physics experiments require the usage of the cold electronics due its structure (LAr and LXe Time Projection Chamber). In this presentation, the behavior of 110 nm CMOS transistor parameters (gm, Vth, µo, rSD, q) between 300 K and 77 K and the integrated front-end electronic design for readout a sensor area of 24 cm2 are presented. The experimental result of the cryogenic electronic front-end for DarkSide20K, using a SiPM as sensor and Liquid Nitrogen, are described. This research is on behalf of DarkSide collaboration.

Tag-Less Indoor Localization with AI and Capacitive Sensors

Mr. Osama Bin Tariq
Dept. of Electronics and Telecommunications (DET), Politecnico di Torino

Low cost, ubiquitous, tag-less, and privacy-aware indoor monitoring is essential to many applications, such as home automation and assisted living of elderly persons. Capacitive sensors can be inconspicuous, cost and power-effective solution, but afflicted by noise especially at ranges much longer than their plate diameter. Here, we explore how well different Artificial Intelligence (AI) techniques can extract location and movement information from noisy experimental data (with both high-pitch and slow drift noise) obtained from capacitive sensors operating in load mode at long ranges. For a 3 m x 3 m space equipped with four 16 cm x 16 cm capacitive sensors, we investigate first how well Machine Learning (ML) can localize a person in 16 predefined positions, then how well continuous human walking trajectories can be reconstructed by various types of Neural Network architectures. We discuss how the experimental data was obtained, preprocessed, and the outcome of the various ML and AI techniques. The key result is the ability to locate and track a person in the above setting with an average accuracy of 93% for location classification and a mean error of 28 cm for trajectory reconstruction using sensors with an estimated SNR of about 3-4 dB.

Low Density Parity Check Codes for Post-quantum Cryptography

Ms. Kristjane Koleci
Dept. of Electronics and Telecommunications (DET), Politecnico di Torino

The current technological progress in the field of quantum computing poses serious problems for the security of widely adopted asymmetric cryptosystems as RSA and ECC. The asymmetric encryption requires to rely on different algorithms, such as Code-based cryptography. The topic of my research is the McEliece cryptosystem based on Error Correcting Codes, in particular a version that adopts QC-LDPC codes. The codes are structured and sparse, thus they have key of small size even if the dimensions of the inner variables are huge. I am mainly working on the hardware implementation of the decryption system in order to make the computation of the quantities faster and include the possibility to have a scalable architecture that is able to match the needs of a particular application or the limitations of a device.


IMPORTANT NEWS: during the last month, we improved the collaboration with the directors of PhD programs. We are very glad to announce that, from now on, the seminars will be recognized as external activities for the PhD candidates in the Electrical, Electronics and Communications Engineering (EECE). Three hard skill hours can be obtained by speakers, one hard skill hour can be obtained for who attend the seminar in the audience (max. 5 hours). This justifies the choice of adding a speaker to the seminar. Traditionally, the PitchD involves two speakers, from now on the speakers will be three to better fits PhD programs rules. During the event, it will be possible to register for obtaining a certification valid for the EECE PhD program. We are working also with the coordinators of other PhD programs, other news will be available soon.

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