🚀 Hi, I’m Jorge Veiras Yanes! A visionary Machine Learning Engineer, founder, and product lead with a passion for turning complex data into game-changing AI solutions. I thrive on innovation, constantly pushing boundaries to create impactful products that redefine industries. From developing AI tools that help businesses captivate their audience to influencing environmental policies with data-driven insights, I’m all about making technology work smarter, faster, and better.🔬 My journey began with a B.Sc. in Physics 🌌 from the University of La Laguna, where I fell in love with computational modeling and machine learning. I recently completed my M.Sc. in Environmental Data Science and Machine Learning at Imperial College London 🎓, mastering the art of big data analytics, AI-driven insights, and seamless deployment strategies.💡 As the founder and product lead of VibePulse, I lead the development of innovative AI-driven solutions that empower restaurants and brands to optimize their visual presence and connect authentically with their audience. VibePulse leverages cutting-edge machine learning to analyze and recommend the best visual content, ensuring that businesses present the right vibe to attract and engage customers effectively.🏆 When I'm not engineering the next big AI breakthrough, you’ll find me traveling the world ✈️, perfecting karate katas 🥋, or pushing my limits at the gym 🏋️♂️. I’m passionate about exploring new cultures and finding inspiration in every corner of the globe, bringing fresh perspectives to my work.📬 I’m open to exciting opportunities in machine learning, AI, and data science where I can continue to drive innovation and deliver exceptional results. Let’s connect if you’re ready to collaborate, explore new ideas, or just geek out about AI and data! Together, we can make incredible things happen.
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Machine Learning EngineerArtioLondon, Gb
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Data ScientistArtio Oct 2024 - PresentLondon Area, United Kingdom
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Machine Learning EngineerVibepulse Apr 2024 - PresentLondon Area, United Kingdom🚀 Leading the development and deployment of the first-ever SaaS platform dedicated to enhancing restaurant experiences through the analysis, classification, and optimisation of their vibes.📊 Compiled a dataset of over 38,000 images through web scraping and AI-generated content to support model training.🧠 Trained and deployed Vision Transformers (ViTs), achieving up to 30% greater F1 scores in some ambience categories compared to leading commercial models like ChatGPT-4o mini and Gemini 1.5 Flash.💻 Designed and implemented both the front-end and back-end of the platform, ensuring seamless integration of features such as AI-driven ambient music generation 🎶 and optimal image selection.🤝 Collaborated with industry experts at Google to refine AI model performance and platform deployment, leveraging Google Cloud Platform (GCP) for scalable, distributed computing solutions.💷 Generated £720 in revenue in August 2024, enhancing the ambience in over 36 restaurants through data-driven insights and AI tools. -
Geospatial Data Science Csic Intern - Seagrass Ecosystem Mapping And Blue Carbon Stock AssessmentInstituto Español De Oceanografía Mar 2023 - May 2023Santa Cruz De Tenerife, Canary Islands, Spain🌊 Seagrass Ecosystem Mapping and Blue Carbon Stock Assessment🛰️ Harnessed Sentinel-2 satellite imagery to map Cymodocea nodosa’s spatiotemporal distribution and estimated blue carbon stocks.🛠️ Performed rigorous image pre-processing: atmospheric correction, radiometric correction, BRDF correction, land masking, sun glint correction, deep water masking efforts, and water column correction using depth invariant indexes.🤖 Leveraged machine learning algorithms for image coverage classification. Random Forest classifiers exhibited the highest F1 scores, ranging between 0.92 and 0.99.📈 Improved metric results from prior studies in the same study area, which yielded accuracies of 0.73 using the WV-2 satellite and the same water column correction method.🌱 Established that in 2021, in our study area, the Cymodocea nodosa sequestered, on average, 73,500 Mg of CO2, offsetting the annual CO2 emissions generated by the Canary Islands’ combustion plants. -
Data Science InternshipUniverzita 'Pavla Jozefa Šafárika' V Košiciach Jul 2022 - Sep 2022Kosice, Slovakia🫀 Application of Deep Learning Methods in ECG Recordings for Arrhythmia Detection🧑💻 Developed machine learning and deep learning algorithms for classifying arrhythmias in ECG recordings extracted from the PhysioNet database.📊 Identified that the best classifiers are Convolutional Neural Networks with an AUC of 0.9.🛠️ Acquired expertise in: machine learning and deep learning algorithms, loss functions and regularisation, optimisation methods (Gradient Descent, SGD, Adam, Nadam), cross-validation, backpropagation, activation functions (Sigmoid, ReLU, TanH, Maxout), batch normalisation, data cleaning methods, PCA, and metrics for statistical analysis.
Jorge Veiras Education Details
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Environmental Data Science And Machine Learning -
Physics
Frequently Asked Questions about Jorge Veiras
What company does Jorge Veiras work for?
Jorge Veiras works for Artio
What is Jorge Veiras's role at the current company?
Jorge Veiras's current role is Machine Learning Engineer.
What schools did Jorge Veiras attend?
Jorge Veiras attended Imperial College London, Universidad De La Laguna.
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