Intro

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Work

Currently working at T&S Germany
Email:raulkevinviana@gmail.com

CV

Raúl Kevin do Espírito Santo Viana

raulkevinviana@gmail.com ❦ +49 174 59 217 96 ❦ Stuttgart, Germany ❦

Work Experience

Lead AI Expert, BigLittleHead

Lisbon, Portugal  |  Jan. 2023 – Present

  • Co-founded a project to develop Portuguese-optimized LLMs for grammar correction and creative writing, training models on 500k+ Portuguese text samples using PyTorch and Hugging Face Transformers.
  • Fine-tuned GPT-3 and T5 architectures for Portuguese text generation.
  • Led cross-functional collaboration with engineers to integrate model outputs into a Flask-based web app, scrape and process web data.

Embedded Software Engineer Consultant, Bosch (Technology & Strategy)

Stuttgart, Germany  |  Sept. 2023 – Present

  • Developed the new version of Diagnostic and System Management (DSM) interacting with VM Brakes (Bosch) and CUBAS (ETAS), to be deployed on 100,000+ diagnostic devices.
  • Implemented and validated diagnostic components (DEM, DCM, OBD).
  • Designed and executed C-based test cases for robust AUTOSAR diagnostic features.
  • Created and adapted oAW scripts and AUTOSAR configurations to generate C code.
  • Developed automation scripts for documentation, code generation, and testing procedures.
  • Wrote requirements in DOORS and designed software in Enterprise Architect.

Software Engineer, Continental

Porto, Portugal  |  Aug. 2022 – Aug. 2023

  • Fine-tuned the T5-Code model to generate test cases for CarMaker, reducing creation time from 1 hour to 6 seconds.
  • Mentored and onboarded new colleagues in the Virtual Testing and Simulation team.
  • Developed simulation environments using CARLA and Python for realistic testing scenarios.
  • Conducted HiL and SiL testing for Volkswagen and Mercedes.
  • Designed and adapted test cases in collaboration with clients.

AI Researcher, Instituto de Telecomunicações

Aveiro, Portugal  |  Jul. 2021 – Dec. 2022

  • Developed and studied ML approaches to reduce the complexity of the Versatile Video Coding (VVC) standard.
  • Achieved a 41.49% complexity reduction in the VVC encoder with only 0.65% quality loss and 6.80% bitrate increase.
  • Processed large datasets (100+ GB).
  • Studied MSE-CNN architectures and documented behavior and potential.
  • Delivered encoded datasets and training code for MSE-CNN.

Education

Integrated Master’s Degree in Electronics and Telecommunication Engineering

Universidade de Aveiro, Aveiro, Portugal  |  Jul. 2017 – Jul. 2022

Specialization in Automation.

Bachelor Degree in Electrical Engineering

National Taiwan University of Science and Technology, Taipei, Taiwan  |  Aug. 2016 – Jun. 2017

MOFA Scholarship student.

Languages, Skills & Interests

  • Languages: Chinese (A2), English (C1), Portuguese (Native), Spanish (B1), German (A2)
  • Technologies: Cloud Services, C, Java, JavaScript, C++, Python, Generative AI, CNNs, ML algorithms, PyTorch, TensorFlow, Jupyter Notebook, Codecs, LLM Fine-Tuning, ChatGPT/Gemini APIs, pandas, pygame, AUTOSAR, DSM, OBD, Real-Time Systems, Embedded Software Development, Microcontrollers, V-Cycle, TDD, DEM, UDS, DOORS, Enterprise Architect, J1939 Dcm, ODX, Doxygen, FreeRTOS, MATLAB, Simulink

GitHub: MSE-CNN Implementations

About

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