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Hi there, I'm Miguel 👋

About Me

I'm a PhD student whose research focuses on deep learning and natural language processing (NLP) in conversational systems, specifically working with large language models (LLMs). I've also collaborated on various research projects as a data scientist and computer vision engineer. In addition to my research work, I have experience as a software engineer, developing both software and web applications.

Current Projects

  • 🔭 I’m currently working on improving conversational systems using deep learning and NLP techniques with LLMs.
  • 🌱 I’m constantly learning and staying up-to-date with the latest advances in AI, NLP, and computer vision.

Collaboration & Connect

  • 👯 I’m always open to collaborating on research projects and sharing my expertise in data science, deep learning, and software engineering.
  • 🤔 If you need help or advice, feel free to reach out.
  • 💬 Ask me about my research, experience, or anything related to AI and computer science.

How to Reach Me

Miguel Ángel Medina Ramírez's Projects

cifar10-pytorch icon cifar10-pytorch

A simple comparison between different neuronal architecture to solve the dataset CIFAR10

face-recognition icon face-recognition

A simple implementation for face recognition using convolutional networks

facebool icon facebool

Have you ever played a platform game using your face... WHILE SHOUTING?!🏀

improving-dialogue-management icon improving-dialogue-management

A detailed analysis of task-oriented dialogue systems, emphasizing the importance of high-quality datasets in dialogue management. We crafted a synthetic dialogue generator to highlight the impact of dataset errors on model outcomes.

lit-gpt icon lit-gpt

Hackable implementation of state-of-the-art open-source LLMs based on nanoGPT. Supports flash attention, 4-bit and 8-bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.

matharray-formalverification icon matharray-formalverification

Simple Ada/Spark package which works with some mathematical functions and arrays. The objective of this library is to make a formal verification using SPARK of some algorithms.

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