On Lounge since Oct 2026
Diego Ramírez Rosas
Member #882FounderL2Founder, Vora Corporation
Biomedical & Electronic Engineer · AI Engineer · Co-founder @ Vora Corporation · LLMs, agents, ML & deep learning
How karma works. Everyone starts with 5. You get +1 each time another member upvotes one of your posts or comments (your own upvotes don't count), and lose it if they take the upvote back. Post what you're building, answer questions and help other members to earn more.
Achievements
Plugged In ×3Connected sources: GitHub, Hugging Face, LinkedIn, X, website.How: Connected 3 sources (GitHub, LinkedIn, X or a website) in Settings
Plugged In×3Featured
Shipper ×2Projects on your profile.How: Added 5 projects to their profile
Shipper×2
Pinned projects
AI Engineer — LLMs & Agents, Machine Learning, Deep Learning, NLP, Computer Vision. Personal GitHub profile README.
artificial-intelligencecomputer-visiondeep-learninggithub-profilellm
ResNet-style classifier for Fashion-MNIST built with custom residual layers, model subclassing and a custom training loop (tf.GradientTape) in TensorFlow 2. Reaches 82.76% test accuracy training on only 5,000 images.
custom-training-loopdeep-learningfashion-mnistgradient-tapeimage-classification
Character-level language model with a stateful GRU, built with TensorFlow 2 / Keras. Trained on Shakespeare's text to predict the next character and generate new text from a seed string.
deep-learninggrujupyter-notebookkeraslanguage-model
Encoder-decoder LSTM for English-to-German neural machine translation, built with TensorFlow 2 / Keras. Uses a frozen pre-trained word embedding, a custom end-token layer and a custom training loop with greedy decoding.
deep-learningencoder-decoderenglish-germanjupyter-notebookkeras
Neural network classifier for the Iris dataset, built with TensorFlow 2 (Keras), focused on validation, regularisation (dropout, L2, batch normalisation) and training callbacks.
classification-internaldeep-learningjupyter-notebookkerasneural-network
Cats vs dogs image classifier: a CNN trained from scratch vs transfer learning with a pretrained MobileNetV2. 98.7% test accuracy with TensorFlow 2 / Keras.
cats-vs-dogscnndeep-learningimage-classificationjupyter-notebook
Stack
About
Biomedical & Electronic Engineer · AI Engineer · Co-founder @ Vora Corporation · LLMs, agents, ML & deep learning
Experience
Ingeniero Electrónico y Biomédico · Uniandes | Electrónica analógica y digital, telecomunicaciones, diseño de PCB, robótica autónoma, sistemas embebidos y agentes de IA | Dispositivos médicos y procesamiento de señales
Monitor Digitalización De Infraestructura Eléctrica · Universidad de los Andes - Colombia
Monitor de Elementos de Sistemas Eléctricos · Universidad de los Andes - Colombia
Monitor Comunicaciones · Universidad de los Andes - Colombia
