Ugo Emanuele Figus

EPFLETUEL-SEL-MA3

Curriculum vitae

Politecnico di Torino – Grenoble INP Phelma – EPFL
Turin, Grenoble, Lausanne
Master’s Degree in Nanotechnologies for ICTs
Sept 2024 – Present

  •    Joint master degree with high selectivity (20 students in Italy) between three esteemed universities, combining semiconductor physics, fabrication, and electronic engineering.

  •    Topics: Physics and electronics fundamentals of nanotechnology, electronic devices, microscopy, nanofabrication, nanoelectronics, VLSI design, hands-on laboratory work in clean rooms, implementation of digital microelectronic systems on FPGAs using VHDL, circuit layout and physical design with Cadence, system-on-chip development with AMD Vivado.

Università degli Studi di Salerno
Fisciano (SA), Italy
Bachelor’s Degree in Computer EngineeringGPA: 27.3/30
Sept 2020 – Sept 2023

  •    Topics: Electronics, automation, telecommunications, software implementation, data analysis with R Studio, database management with SQL, programming in Java and JavaFX, fundamentals of engineering subjects.

Projects

Restart-Arcadia THz Technology
Università degli Studi di Salerno – Fisciano (SA), Italy
Jun 2025 – Aug 2025

  •    Integrated COMSOL Multiphysics and Keysight ADS inside MATLAB for full communication chain simulation, combining multiphysics device modeling (antennas, waveguides, passive components) with RF, microwave, and system-level design for end-to-end performance evaluation.

  •    Strengthened communication, collaboration, and time-management skills through multicultural and multidisciplinary teamwork.

Advanced MOSFET Technology for Cryogenic Electronics
CEA-Leti / Phelma / CromaLab
Feb 2025 – May 2025

  •    Modeled and analyzed FDSOI MOSFET behavior at cryogenic temperatures using Synopsys Sentaurus TCAD, focusing on performance optimization and reliability for low-temperature electronic applications.

  •    Collaborated with a cross-functional team to optimize workflow and operational processes, achieving analysis down to 4 K.

Protein Classification with Graph Neural Networks
Universitat Rovira i Virgili – Tarragona, Spain
Feb 2023 – Jun 2023

  •    Developed a predictive GCN model for protein classification implemented in Python using Pandas, TensorFlow, and Keras, with model training and testing.

  •    Enhanced problem-solving and autonomous analytical skills by independently researching advanced topics in computational biology.

Skills

  •    Programming Languages: C/C++, Python, SQL, R, LATEX, Java, JavaFX

  •    Hardware & Tools: VHDL, SystemVerilog, Cadence, AMD Vivado, FPGA design

  •    Software & Data: COMSOL, Keysight ADS, Synopsys Sentaurus TCAD, MATLAB, R Studio

  •    Productivity & Collaboration: Git, Office Suite (Excel, PowerPoint, Word)

  •    Data Analysis: Python (Pandas, NumPy, Matplotlib)

Language Skills

  •    Italian: Native

  •    English: C1 Advanced (Cambridge)