Alessio Borgi

Alessio Borgi

PhD in Graph Neural Networks and Generative AI 👨🏻‍💻🤖

CV

Education

  • Ph.D. in Engineering in Computer Science — Artificial Intelligence, Sapienza University 🇮🇹 & University of Cambridge 🇬🇧 — 2025–present
    Supervisors: Prof. Pietro Liò (supervisor), Prof. Fabrizio Silvestri (co-supervisor)
    Focus: Graph Neural Networks & Generative AI

  • M.Sc. in Artificial Intelligence & Robotics, Sapienza University 🇮🇹 — 2023–2025
    Final mark: 110/110
    Thesis: Polynomial Sheaf Diffusion and Equivariant Sheaf Neural Networks
    Courses: Artificial Intelligence, Machine Learning, Neural Networks, Robot Programming, Robotics I & II, NeuroEngineering, Computer Vision, Medical Robotics, Reinforcement Learning, Autonomous & Mobile Robotics, Deep Learning, Advanced ML, Generative AI Safety, HRI, Robot Benchmarking & Competitions, Multilingual NLP.
    Memberships: ALCOR Lab and ISPAMM Lab.

  • B.Sc. in Applied Computer Science and Artificial Intelligence, Sapienza University 🇮🇹 — 2020–2023
    Final mark: 110/110 with Honours
    Thesis: Building Real-Time Multivariate Anomaly Detection Systems in Industry’s 5G Networks: A Comprehensive Workflow — GitHub GitHub.
    Courses: Deep Learning, AI Lab & Computer Vision, Machine Learning, Artificial Intelligence, Web & Software Architecture, Cybersecurity, Programming I/II (+ Lab), Databases, HCI, Networking, Operating Systems, Algorithms, Statistics, Startup & Management, Business & CS, Computer Architecture, Calculus I/II/III, Linear Algebra, Physics, Probability, Foundations of CS.
    Membership: OmniAI Lab.

  • Secondary School — Information Technology, I.I.S. Guglielmo Marconi, Civitavecchia 🇮🇹 — 2015–2020
    Final mark: 100/100
    Thesis/Project: Electric Company: Ticketing System — GitHub GitHub.

Visiting Research

  • Space Robotics — Tohoku University, Space Robotics Lab, Sendai, Japan 🇯🇵 — June–July 2025
    Supervisor: Prof. Kazuya Yoshida
    Project: MoonBot Navigation — Autonomous robot for lunar navigation & object interaction. Dijkstra-based path planning, object detection (vision), custom robot design, gripper control.
    Repository: GitHub MoonBot Navigation (GitHub)
    Outcome: Selected as top-1 student for the exchange; developed the MoonBot Navigation project (linked above) which won the TESP 2025 Competition, and I received the Research Certificate of Excellence. Project Page: Visiting Research Tohoku University Page.

  • AI & Robotics in Healthcare — Johannes Kepler Universität (JKU), Linz, Austria 🇦🇹 — Aug–Sept 2024
    Supervisor: Prof. Alexander Steinmaurer
    Project: CareConnect — AI-driven system to query environmental/hospital data via chat, generate real-time graphs, and trigger notifications & robotic actions using LangChain.
    Repository: GitHub CareConnect (GitHub)
    Achievement: Best Poster & Project Award (program showcase).

Work Experience

  • AI & ML Software Research Engineer (Intern) — Hewlett Packard Enterprise (HPE) — Mar 2023 – Aug 2023
    Research on Multivariate Anomaly Detection over 5G time-series.
    – Designed a customer-centered & customer-agnostic workflow: from network data integration to feature selection for anomaly identification.
    – Validated with a major network customer, reducing models to train/maintain and lowering design/inference resource/time requirements while preserving overall metrics.
    – Honourable Mention in an internal HPE Hackathon.
    – Team Best HPE 2023 Paper Award.

Awards

  • G-Research Early Career Award: Scholarship for promising young researchers (November, 2025).
  • Research Certificate of Excellence - Selected as top-1 student for the visiting period, won TESP 2025 Competition and awarded with a Certificate of Research Excellence. (Tohoku University 2025, Japan).
  • Generative AI Safety Challenge — Privacy Violation Detection (Individual Award) & Attack on Data (Team Award), (Sapienza University of Rome, Italy, 2025).
  • Best Poster Award — Mediterranean Machine Learning (M2L) Summer School, (Milan, Italy, 2024).
  • Best Paper Award (team) — Hewlett Packard Enterprise PathFinder Team Recognition, (2023).
  • Honourable Mention — Hewlett Packard Enterprise Internal Hackaton, (2023).

Skills

Programming Languages: Python · Java · C++ · Matlab · Java-FX · Swing · FXML · RISC-V · GO · JavaScript · VueJS · OpenAPI · CSS · HTML · SQL · PHP · Flutter

Core ML/Graph: PyTorch · Tensorflow · Diffusers · Transformers · W&B · NumPy · PySpark · Pandas · OpenCV

Robotics & Systems: ROS · Rviz · WeBots · GMapping

Tooling: CUDA · Git · Linux · Docker · LaTeX · Hydra/YAML · Streamlit · Figma · Arduino · Raspberry Pi · Docker · WordPress · Axios

Certifications

  • Cambridge Assessment International Education — First Certificate (B2) (ID: B3329535)
  • Instituto Cervantes — DELE A1 (ID: S6516DL9BAHUJHY248TJ4V4KJ2)
  • DeepLearning.AI & AWS — Generative AI with Large Language Models (Coursera) (ID: VHCBD26QZP7W)
  • AWS — AI & ML Scholarship Program (verified)
  • COMAU — “Use and Programming” Robotic License (ID: kDHqAdhwAT)
  • IBM — Cloud Core Certification (verified)
  • IBM — Blockchain Essentials Certification (verified)

Languages

  • Italian — C2 (Mother tongue)
  • English — C1
  • Spanish — A1

Publications

Contact