Research

I use electroencephalography (EEG) recordings to implicitly control generative models’ (generative adversarial neural networks or GANs) output visual features as a model task.

🧠 What are the similarities between human cognition and machine learning models?

I investigated the similarity between images measured as GAN-learned distances and compared them to human perceptual distances (Psychophysiology, submitted).

📈 How can we use physiological recordings or medical data in user-centered machine learning methods?

I use EEG as feedback to steer the GAN and match the user’s intentions (e.g., I think of a blond and smiling person, the GAN generates a blond and smiling person UIST'20). I extend the applications to brain-based semantic image editing (CVPR'22) and implicit multi-user image generation (in progress).

🤖 Can such data inform us to enhance or design novel machine learning algorithms?

In progress.

📚 Can we model human memory and help humans learn?

I have combined a cognitive model of memory (infer how the user learns and forgets) and model-based planning (when to review or show a new item) for intelligent tutoring systems IUI'21. I have also contributed to open science by replicating a connectionist memory model, leading to correcting the original manuscript (ReScience C).

Other

• Mentoring, networking, advocacy, and event planning.
• Tech: GNU+Linux (Gentoo/Arch/Debian), FLOSS, Vim, UNIX philosophy, refurbishing computers.
• Sports, personal growth, and music: certified coach and personal trainer. I play triad chords on a (music) keyboard.