AI and Embedded Technologies Summary

Through various projects and collaborations, I’ve had real life field experience with various HW and SW technologies, continuously growing! Some are obsolete but part of what made up my experience and Courses Attended NOTE: updated Dec 2024. New Techs/Frameworks/APIs I ma evaluating directly are rapidly coming out

AI & Machine Learning

• LLMs & AI Agents: Llama 3.x, Ollama, llama.cpp, Llamafile, Groq, OpenAI, DeepSeek, Stability.ai, LM Studio, LLM APIs, prompt engineering, custom AI agents
• Frameworks & Python APIs: Scikit-learn, Keras, TensorFlow, PyTorch, NumPy, Pandas, Matplotlib, OpenCV (YOLO, tesseract OCR), BS4, Playwright, Pyautogui, Selenium, PydanticAI, crawl4ai, LangChain
• AI Projects: LLM, prompt engineering automation, AI Agents, RAG
• Detection & Classification: CNN-based models, OpenCV, YOLO ; Voice Recognition Vosk with customised pronounce
• Data Tools: Self-built datasets labeler, Kaggle, Roboflow, LabelAI.io;
• Benchmarking: Evaluating AI models on various tasks, including use of TPUs on Edge embedded devices
• GUI Development: PyQT, tkinter, Streamlit, Panel, Flask, Jupyter Notebooks, Co-labs, Holoviz, Bokeh
• Linters/Tester: ruff, pytest, mypy ; PCLint (C/C++)

Languages & Environments

• Programming Languages: Python 3, C/C++ (ANSI, GNU GCC) Bash scripting
• Embedded & OS Development: Linux Device Drivers/BSP, POSIX Threads, RTOS (FreeRTOS, QNX, Linux Montavista/RTL/RTAI); Edge Impulse
• IDEs & Tool: Jupyter Notebook, Google Colab, PyCharm, QT Creator (PyQT), LM Studio, Stability.ai
• Networking & Cloud: AWS (EC2), PythonAnywhere, Google Cloud (GCS); Server & Database: Apache, MySQL, Wiki web server, php
  • Virtual Machines: VirtualBox, VMWare; Docker
  • Security best practices: ssh, firewalls, wireshark, LAN, WiFi
• Version Control: Git (GitLab, GitHub), DVC (Data Version Control - Dataset versioning), Mercurial (uHG), SVN, CVS
• Other Platforms and Development Tools: Android (Java, Eclipse), iOS (Code Composer + Testflight), Web (HTML/CSS, Streamlit, Panel/Flask), Borland, Microsoft (VB, C#, Win CE)

Hardware and Firmware Embedded Design

• System On Chip (SoC) and MCUs
  • x86 Family: ZFx86, Intel, ST STPC, AMD (MCU 80186CC), Geode GX1, SBC VIA
  • DSP: Texas Instruments
  • SoC ARM: STM32, Samsung S3C24xx/S3C64xx, ST Spear Family, TI OMAP 24xx, Sirf Prima, Sigmatel/Freescale, ST Cartesio, RENESAS
  • Microchip/Atmel: PIC (8-16 bit), SAM xx (32 bit) ; Freescale: MCU HCS08, MCU 68xxx
  • Other: ESP32, Raspberry Pi (3, 4, 4B, AI HAT); Nvidia Jetson Nano, Arduino, Rockchip RK3326 SBC
  • Communication Buses & Protocols:
    • HW: USB (+FTDI), UART/RS232-485, LPT, Keyboard Controller, ISA, EISA, PCI (Target Actel IP 32-bit), PC/104, CompactPCI (Bridge PLX), VME
    • SW: WiFi (Socket SW TCP/UDP), Modem Proprietari, Bluetooth (BT 3.0, BTLE 4.0)
• Other Electronics Experience
  • FPGA/CPLD: Altera Flex, Xilinx, Cypress, Actel
  • ICs & Components: Ethernet controllers (DEC 21143), IEEE1394, mechanical PCB interfacing, DIP, SMD, BGA packages
  • Sensors & Mixed-Signal Devices: Magnetoresistive sensors, ST SABRe, RFID (125kHz Passive RF Systems)
  • Power & Noise Management: Low-power systems (EM - 4 bit), EMC/EMI and noise troubleshooting

Electronic Development Tools

• HW: Altium Designer (ex Protel99SE), LabView, Xilinx Foundation, PSpice, Actel Libero, Altera Max+II, Microsim Schematics, Lauterbach (debugger HW JTAG), Microtek (HW emulators), KiCad (CERN), EagleCAD, freeCAD (ME)
• FW&SW: cross-copilers (gcc; linux makefile); MPLAB IDE, STM32Cube, IAR (compilers/assemblers), CAD-UL (per x186), Eclipse IDE, Visual Studio ; Doxygen, PC-Lint, API C Loquendo TTS

Education (Formal) and AI Courses Attended

AI & Machine Learning Courses (2018-2025)

• Deeplearning.ai (2023-2024) (Courses by Andrew Ng and others)
  • Fine-Tuning Large Language Models (2023)
  • LangChain for LLM Application Development
  • Multi-AI Agent Systems with CrewAI (2024)
  • Building and Evaluating Advanced RAG (2024)
• Stanford University (via EdX and Coursera)
  • Neural Networks and Deep Learning
  • Machine Learning with Deep Convolutional Neural Networks (DCNN)
• YT Channel 3Blue1brown: excellent explanations with animations on math behind NL, LLM and GPT
• medium articles tutorials

AI/ML Events, Seminars, and Conferences

• PyData (Milano & International)
  • Workshops on Python ML libraries: NumPy, Pandas, Scikit-learn, TensorFlow
  • Talks on deploying AI in production (MLOps), data visualization, and large-scale data processing
  • 2024 sessions on Bayesian methods, reinforcement learning, and transformers
• ODSC (Open Data Science Conference) (2017-Present)
  • Hands-on training in NLP, deep learning, and AI ethics
  • Keynotes on AI-driven analytics, generative AI, and industry adoption of LLMs
  • 2023 session on vector databases and Retrieval-Augmented Generation (RAG)
• Google Summit & Codemotion
  • AI and cloud computing trends (Google AI, TensorFlow updates)
  • Workshops on ML model deployment, API integration, and federated learning
• Deep Learning Italia (DLI)
  • Italian community-driven AI/ML advancements
  • Research and case studies in medical AI, automation, and generative models
• Embedded World Conference
  • AI on edge devices: Nvidia Jetson, Raspberry Pi, Rockchip
  • Low-power deep learning inference and real-time ML applications

Politecnico di Torino - Robotics and Automation Specialization (5 years)

• Consultant member of the Italian Engineers Association (“Ordine degli Ingegneri”)

Experience in startup acceleration and networking:

• Shenzhen (China), Salt Lake City (USA) startup incubator programs
• Winner of StartUP WE (Milano, Italy)