Adrià Ciurana Lanau, Developer in Barcelona, Spain
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Adrià Ciurana Lanau

Verified Expert  in Engineering

Computer Vision Developer

Barcelona, Spain
Toptal Member Since
November 24, 2021

Adrià started programming at 11 with his father. He has explored many areas, but what has fascinated him the most has been IA algorithms. Adrià specialized in classical computer vision, where high level knowledge of machine learning models was necessary. With the emergence of deep learning (DL), he specialized in DL. For eight years, he has worked on disruptive innovation projects in IA and was a trainer in machine learning, deep learning, and statistics to companies and private schools.


Deep Learning, Generative Adversarial Networks (GANs), Machine Learning...
Python, PyTorch, NumPy, Deep Learning, Machine Learning...
MongoDB, MySQL, Azure, Amazon Web Services (AWS), Apache Airflow, Big Data...




Preferred Environment

Linux, PyTorch, Slack, Visual Studio Code (VS Code), Git, Discord

The most amazing...

...project I’ve collaborated on was as the main IA developer, advisor, and trainer in a company that is one of the most promising InsurTechs in the world.

Work Experience

Deep Learning Research Lead

2020 - PRESENT
  • Developed various concept-oriented proofs for the generation of synthetic images for marketing and, as a result, obtained public financing.
  • Created tools for the extraction of information in images from social networks to carry out automatic tagging, captioning, and measurement of the quality of the image, and measurement of impact.
  • Developed a complete pipeline of realistic generations of virtual environments for marketing.
Technologies: Deep Learning, Generative Adversarial Networks (GANs), Machine Learning, Amazon Web Services (AWS), Docker, Optimization, Convex Optimization, Research, Artificial Intelligence (AI)


2019 - PRESENT
  • Created my own consulting firm, which allowed the realization of successful projects.
  • Offered services for project management, advising, and realization of projects in the field of artificial intelligence.
  • Created different free courses at conferences for the scientific dissemination of artificial intelligence.
Technologies: Python, PyTorch, NumPy, Deep Learning, Machine Learning, Amazon Web Services (AWS), Pandas, TensorFlow, Keras, Artificial Intelligence (AI), Computer Vision, Computer Science, Mathematical Modeling, Data Science, Data Engineering

Deep Learning Advisor | Research Lead

2019 - 2021
  • Created a core product for the estimation of vehicle damage, as well as subsequently its quantification in the product’s cost.
  • Trained workers and advisors on decision-making and the strategic vision of the company.
  • Won several awards, including the best algorithm of the year, and was a two-time South Summit winner. The company is currently one of the top 100 most important insurtechs in the world.
Technologies: MongoDB, MySQL, Azure, Amazon Web Services (AWS), Apache Airflow, Big Data, Python, JavaScript, HTML, CSS5, Vue, Keras, TensorFlow, Scikit-learn, PyTorch, SpaCy, Rasa NLU, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Object Detection, Instance Segmentation, Semantic Segmentation, Classification, Data Science, Bayesian Neural Networks, Deep Reinforcement Learning, Convex Optimization, Management, Dynamic Programming, 3D Reconstruction, Graph Neural Networks, Artificial Intelligence (AI)

Research Lead

2020 - 2020
  • Managed a team focused on the development of a non-intrusive advertising insertion application in sports videos.
  • Created neural networks for precise segmentation of games and objects on the playing field. Carried out a shadow estimation to insert the advertisement virtually.
  • Created a complete pipeline to process videos in real-time.
Technologies: Machine Learning, Deep Learning, Optimization, Computer Vision, PyTorch, Scrum, Management, Alpha Matting, Video Analysis, Semantic Segmentation, Object Detection, Multiprocessing, GPU Computing, Docker, Artificial Intelligence (AI)

Deep Learning Research

2019 - 2020
  • Developed highly efficient neural networks for the precise detection and classification of players and the ball on a soccer field.
  • Optimized the neural networks used to apply them in embedded systems using libraries like TensorRT and CUDA.
  • Developed a complete tool for mass data annotation in videos of various sports. These included cloud management to pseudo-annotate, manually annotate, manage data in the cloud, and automatically distribute annotation tasks to different annotators.
Technologies: Deep Learning, Machine Learning, PyTorch, Darknet, Keras, TensorFlow, NVIDIA TensorRT, Python, MongoDB, Docker

Professional Trainer

2019 - 2020
  • Created courses for companies in the field of machine learning.
  • Presented various projects to the shipping and logistics industry to solve multiple logistical problems involving techniques of machine learning, deep learning, sensors, and big data.
  • Created courses for the unemployed in the field of big data and deep learning.
Technologies: Deep Learning, Machine Learning, Statistics, Bayesian Statistics, Artificial Intelligence (AI), Computer Vision

Deep Learning and Machine Learning Developer

2018 - 2019
  • Developed a complete facial recognition pipeline, including web verification middleware, life detection using eye-blinking, face detection and tracking in the browser, a biometric information extraction server, and identity verification.
  • Created an automatic system for extracting information from a personal document. Detected documents via webcam, the automated classification of the document, and the extraction of the relevant information through OCR techniques.
  • Certified delicate processes for banks, such as digital signatures and notarial procedures, among others.
Technologies: PyTorch, Keras, TensorFlow, Machine Learning, Deep Learning, MongoDB, Vue, Amazon Web Services (AWS), Docker, Image Retrieval, Artificial Intelligence (AI)

Full-stack and Machine Learning Developer

2017 - 2018
  • Developed a fully automated operating room management platform, allowing monitoring its current status and efficient management.
  • Tracked and fixed bugs using Asana as an internal task management tool and methodologies using Agile.
  • The platform also includes an estimation system for intervention times and a scheduling system to automate the intervention schedule.
Technologies: Machine Learning, Clustering, Scikit-learn, Keras, PHP, Python, MySQL, Vue, Graphs, Artificial Intelligence (AI), Optimization, Genetic Algorithms


2016 - 2017
Computer Vision Center
  • Developed neural networks to estimate the global light of an image, as well as possible directional lights.
  • Developed custom layers in CUDA to integrate them into the Caffe neural network framework.
  • Developed color clustering techniques to harmonize images.
Technologies: Caffe, TensorFlow, Machine Learning, Deep Learning, Artificial Intelligence (AI)

Photoslurp: Image Generation

Crafted project-oriented generative networks to create quality content in the marketing arena.

I created all the necessary tools for data annotation, the pipeline, and study of the current state-of-the-art synthetic imaging and image analysis tools to extract valuable data and automatically generate tags, captions, and relevant information from social networks.

Bdeo: Car & House Damage Estimation

Advised and trained an intern team, provided strategic vision, technical viability, and led research development.

During a three year period, we combined different areas from machine learning techniques to detect, segment, and estimate the cost of damages produced in vehicles. Later we combined natural language descriptions with images to produce similar estimations from homes. To carry out this project, we developed algorithms totally from scratch. We also made complex annotation tools to accurately annotate precise data. Finally, we implemented interpretation tools to guarantee excellent results. Within the collaboration, we also developed many additional topics: fraud detection systems, recommendation systems, data management, NLP pipelines, and tools based on natural language.

Ogulo: Geometric Estimation in Homes
Developed a household geometry estimation project where new networks of different areas estimated the room's geometry, delimited the rooms, detected the objects' volumetry, removed artifacts, and rearranged the rooms.

I researched cutting-edge processes and specific improvements to the models to offer more robustness. In addition, a study of the state of the art technology was carried out together with the transfer of particular knowledge to the company's technical department.


Created different multimedia content (videos and blog entries) to disseminate and acquire customers related to AI technologies.

I worked on an advice service regarding how to approach stock estimation problems in the technical field.
2018 - 2019

Master's Degree in Big Data

Datahack School - Barcelona, Spain

2015 - 2016

Master's Degree in Computer Vision

Autonomous University of Barcelona - Barcelona, Spain

2011 - 2015

Bachelor's Degree in Computer Science

Autonomous University of Barcelona - Barcelona, Spain


Certified Self-Driving Car Engineer



Certified Data Engineer



Certified Big Data Architect

Datahack schoool


Certified Deep Reinforcement Learning



PyTorch, NumPy, Keras, TensorFlow, Scikit-learn, Pandas, Vue, SpaCy, Rasa NLU


Slack, Git, MATLAB, Apache Airflow


Python, JavaScript, HTML, PHP


Linux, Visual Studio Code (VS Code), Amazon Web Services (AWS), Amazon EC2, Azure, Docker


Data Science, Scrum, Management, Dynamic Programming


Hadoop, Spark, Caffe, Darknet


Redshift, Data Pipelines, MySQL, Databases, MongoDB, Elasticsearch, Amazon S3 (AWS S3)


Machine Learning, Computer Science, Computer Vision, Computer Vision Algorithms, Deep Learning, Generative Adversarial Networks (GANs), Object Detection, Instance Segmentation, Semantic Segmentation, Classification, Video Analysis, Artificial Intelligence (AI), Image Retrieval, Cloning, User Behavior, Optimization, Clustering, CSS5, Alpha Matting, Bayesian Neural Networks, Convex Optimization, Research, Non-differentiable Optimization, Depth Estimation, Time Series, Time Series Analysis, Fourier Analysis, Mathematical Modeling, Data Engineering, Genetic Algorithms, Discord, Cryptography, Applied Mathematics, 3D Reconstruction, Apache Cassandra, Reinforcement Learning, Deep Reinforcement Learning, Autonomous Navigation, PID Controllers, Bayesian Statistics, Big Data Architecture, Big Data, Statistics, NVIDIA TensorRT, Natural Language Processing (NLP), Multiprocessing, GPU Computing, Graph Neural Networks, Graphs, Geometry, Projective Geometry, Ensemble Modeling, Generative Pre-trained Transformers (GPT)

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