I am interested in healthcare, artificial intelligence, education and Latin America.
I am working at the intersection of digital health and artificial intelligence.
My main research interest is to find effective solutions to behavioral disease with technology. A disease that affects millions of people worldwide.
I am a postdoctoral researcher in the Edelman Lab at the Institute for Medical Engineering and Sciences at MIT.
I was a postdoctoral fellow at the Miller lab, at the Picower Institute for Learning and Memory and the Brain + Cognitive Sciences department at MIT. Where I worked in developing machine learning models from large-scale neural recordings to obtain meaning in the underlying mechanisms of cognition and memory. This to pave the way for much-needed solutions in brain disease.
You can find my most-updated CV here (February 2021).
I presented research at the Society of Neuroscience conference 2019 by giving a talk at the mini-symposium entitled Artificial Intelligence and Neuroscience: From Neural Dynamics to Artificial Agents
I recently published a short-paper with my college, Andre Bastos, on "Pattern recognition of deep and superficial layers of the macaque brain using large-scale local field potentials" Presented at the Conference on Cognitive Computational Neuroscience 2019
I am the lead organizer of the first Artificial Intelligence Latin American summit 2020 held at MIT’s Media Lab on January 21-23 2020. The goal of the summit is to incentivize leaders of the region in government, industry, and academia to invest and develop Artificial Intelligence for social benefit. You can find the videos of the meeting here: https://www.youtube.com/c/ailatinamericansummit. I also wrote an opinion article on the motivations behind organizing the summit. MIT News also wrote a story.
I have also enjoyed spending some of my time at the Alan Turing Institute in the UK, as part of the data study groups. Those bring together some of the UK's top talent from data science, artificial intelligence, and wider fields, to analyze real-world data science challenges. I worked on tackling fairness in machine learning. Here is the report and a subsequent tool spun out from the project.
My research currently holds the world record (if no longer, let me know!) in biometric footstep recognition. By obtaining an equal error rate of 0.7% in the largest footstep recognition database with a spatio-temporal deep network using resnets.
I did my Ph.D. at the University of Manchester in the UK. I focused my doctoral thesis on machine learning for gait analysis in the context of security and healthcare.
For my master's degree thesis I worked on indoor positioning, simultaneous localization and mapping in Robotics (SLAM) and cancer research.
My full and updated list of research publications is in google scholar. If you are interested in any of my research work don't hesitate to contact me at [c]@mit.edu for questions or resources.
To find out what I am up to and the things I am interested in, check out my twitter. I love music too: besides loving the new wave of Latin American artists, I also love experimental and creative music that blends the old (Jazz, classical) with the new (electronic, ambient) in interesting and pleasant ways. Some of my favorites artists are Nils Frahm, Apparat, Skinshape, Jon Hopkins, Helios, and Alaskan Tapes. I also like to tell stories with music.
I am a running and swimming enthusiast. I have run the Amsterdam, Hanover and New York marathons and several half-marathons around Europe. I plan to run the Tokyo, Berlin, London, Chicago, and hopefully Boston marathons in the near future. You can follow me on Strava. I also did the London triathlon of 2016 (Olympic distance) which is probably my first and only triathlon due to not having enough time for training!
[c] = costilla