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Miguel is currently a Senior Research Engineer at University College London, UK, where he leads pioneering advancements in data-centric AI tools for Medical Imaging, MedTech, SurgTech, Biomechanics, and Clinical Translation. His work focuses on driving innovation and delivering impact in several critical areas: Real-time AI for surgery, eye movement disorders, and echocardiography, Sensor fusion data integrating wearable trackers with medical imaging, Generative models for fetal imaging, and Child-robot interaction in low-resource countries. By harnessing these cutting-edge technologies, he is dedicated to transforming healthcare through AI and making a lasting impact on patient care and medical research.

Miguel Xochicale, PhD's Projects

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University of Birmingham Three Minute Thesis 2018 (3MT)

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unmanned aerial vehicles (UAVs)

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[NIPS 2017] Toward Multimodal Image-to-Image Translation

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Otto Blockly; a fully integrated graphical programming for Arduino robots, ready to install in your computer, works offline

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BlocklyDuino is a web-based visual programming editor for arduino.

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Brian is a simulator for spiking neural networks [https://github.com/brian-team]

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Replication of "practical method for determining the minimum embedding dimension of a scalar time series", Cao Liangyue, Physica D: Nonlinear Phenomena, v. 110, n. 1, pp 43-50, 1997.

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Cool vision, learning, and graphics papers on Cats!

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Code of Ethics for Young Scientist

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Consortium of European Research on Emotion 2018: April 4-5, 2018, Glasgow, Scotland (UK)

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Challenges in Machine Learning using Mexican Open Datasets

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:computer: :school_satchel: code

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My CV :scroll: :unlock: :octocat:

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DanceNet -💃💃Dance generator using Autoencoder, LSTM and Mixture Density Network. (Keras)

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