Mariana Dias

About

I’m a Machine Learning Engineer with a broad background in Machine Learning and Deep Learning, and specilized in Computer Vision and 3D geometry. Beyond training models, I have experience building clean, maintainable systems with solid architecture and CI/CD practices. Having worked closely with graphics engineers, cloud and infrastructure teams, and 3D artists, I have developed a strong understanding of how to communicate effectively across different domains to build real-world systems. My work has led to two SIGGRAPH publications and contributions to multiple granted US patents.

  • Age: 30
  • City: Porto, Portugal

Technical Skills

Programming languages

  • Python
  • C++ (OpenCV, FBX SDK)
  • C#
  • Matlab

Engineering & Tooling

  • Git, Docker, Linux
  • Amazon Bedrock
  • LaTeX

Libraries

  • PyTorch
  • OpenCV, Scikit-Image, Pillow, MediaPipe
  • Open3D, Trimesh, PyMeshLab
  • NumPy, SciPy, Pandas, Scikit-Learn
  • LangChain/ LangGraph, Docling

Machine Learning

  • Deep Learning for vision: CNNs, GANs, Diffusion Models, Autoencoders, ViT, CLIP
  • Computer Vision tasks: segmentation, keypoint detection, regression, classification, and style transfer
  • Synthetic data generation
  • Geometry/ Graphics algorithms: collision detection, decimation, voxelization, texture packing
  • AI Agents & RAG

3D & Graphics

  • Blender - global tool usage & scripting
  • Unity - scripting in C#
  • MetaHuman Creator

Languages

  • Portuguese (native)
  • English (fluent)

Resume

Education

Integrated Master's in Bioengineering

2014 - 2019

Faculty of Engineering of the University of Porto (FEUP)

  • Specialization in Biomedical Engineering.
  • Master thesis: Thoracic MRI emulation through texture synthesis and ground truth manipulation. Thesis developed at the Institute for Systems and Computer Engineering, Technology and Science (INESC TEC) and published here.
  • For my Master's thesis, I focused on using Generative Adversarial Networks to generate synthetic thoracic MRI data from labeled images. The objective was to create novel, synthetic MRIs that could be used to train other Machine Learning algorithms in the medical field (e.g. segmentation of bones and tissues, tumor detection, etc).

Professional Experience

Senior Software Engineer

August 2019 - Present

Didimo, Porto, Portugal

Didimo is a company that offers two primary services:
  • creation of high-quality and realistic 3D avatars from a single facial photo;
  • automated creation of non-playable characters (NPCs) for the gaming industry, with variety and at scale

I currently work on the core engine that generates the avatars, specifically on facial reconstruction and conditional face generation. Most of my work focuses on the Computer Vision challenges required for the generation of realistic and clean facial assets (geometry and textures) and on integrating those developments mindfully into the product. Working alongside 3D artists and Unity/ Unreal developers, I have also had the opportunity to tackle Computer Graphics challenges, having worked on a mix of topics from texture packing to rendering, among many others. I advocate for clean, efficient, tested, and overall good-quality code, so I also dedicate some of my time to software design challenges.

At Didimo, I had the opportunity to contribute to the development of a product from its early days. I learned that resilience, patience, teamwork, and knowledge sharing are at the core of producing good-quality software. I experienced what it is like to be at the beginning of a team and to welcome and integrate new people into it, which reinforced my appreciation for mutual support and collective growth.

Internship

September 2017 - June 2018

Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), Porto, Portugal

Intern of the Breast Research Group (BRG), at the Telecommunication and Multimedia Center (CTM), at INESC TEC. Developed Computer Vision algorithms to perform multiple tasks with medical images, including segmentation and image generation, using thoracic MRI data.

Publications

Creating Infinite Characters From a Single Template: How Automation May Give Super Powers to 3D Artists

SIGGRAPH 2024

Mariana Dias, Pedro Coelho, Rui Figueiredo, Rita Carvalho, Verónica Orvalho, and Alexis Roche.

In ACM SIGGRAPH 2024 Talks (SIGGRAPH '24). Association for Computing Machinery, New York, NY, USA, Article 47, 1–2.

DOI

High-fidelity facial reconstruction from a single photo using photo-realistic rendering

SIGGRAPH 2022

Mariana Dias, Alexis Roche, Margarida Fernandes, and Verónica Orvalho.

In ACM SIGGRAPH 2022 Talks (SIGGRAPH '22). Association for Computing Machinery, New York, NY, USA, Article 17, 1–2.

DOI

Adversarial Data Augmentation on Breast MRI Segmentation

2021

Teixeira, J.F.; Dias, M.; Batista, E.; Costa, J.; Teixeira, L.F.; Oliveira, H.P.

Appl. Sci. 2021, 11, 4554.

DOI

Automatic Sternum Segmentation in Thoracic MRI

2019

M. Dias, B. Rocha, J. F. Teixeira and H. P. Oliveira

41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 2019, pp. 1018-1021

DOI

Patents

Systems, Methods and Media for Deep Shape Prediction

Pending

US20230237840A1

Advanced automatic rig creation processes

Active

US12067662B2

Advanced systems and methods for automatically generating an animatable object from various types of user input

Active

US11645800B2

Additional developments to the automatic rig creation process

Active

US11508107B2

Portfolio

In my free time, I enjoy creating 3D art and developing small software projects — some of which you can find below. This website is one of those projects too.
  • All
  • Software development
  • 3D Artwork