Research in Neuroscience and Machine Learning
I am an engineer working at the intersection of technology and neuroscience, with a deep passion for investigating the intricacies of the human brain to contribute to a greater understanding and improvement of our mental health as a society.
I graduated in Telecommunications Engineering at Polytechnic University of Catalonia (UPC). After working in academia (ICFO) and completing my master thesis at MIT, I joined Starlab as a Research Engineer, working in applied neuroscience R&D with a focus on EEG signal processing and data analysis for Brain Computer Interfaces (BCI) and non-invasive brain stimulation techniques (tDCS, tACS and tRNS). After two years, I joined Neuroelectrics team (Starlab’s spinoff company) and I moved to Boston as a Technical Manager to open the first international offices of the company. During the following years I combined my job at Neuroelectrics with my PhD in Neuroscience at University of Barcelona, in collaboration with Harvard Medical School, where I explored the use of deep learning techniques applied to EEG data to study brain dynamics and physiological biomarkers, as well as the use of transcranial current stimulation as a neuromodulation technique to improve executive function in healthy and clinical populations.
I am currently the Neurotech Innovation Lead at the Neuroscience Product Development division of Genentech/Roche in San Francisco (CA), where my goal is to identify and develop new technologies at the intersection of engineering, AI and medicine, bringing neurotech into biotechnology and leading the transformation of traditional diagnostics and therapies for psychiatric and neurological disorders. I am currently working on different projects using machine learning to develop EEG-based biomarkers to predict disease progression, improve patient stratification and predict treatment response.
Download my resumé.
PhD in Neuroscience, 2020
University of Barcelona
MSc in Telecommunications Engineering, 2011
Polytechnic University of Catalonia
BSc in Telecommunications Engineering, 2008
Polytechnic University of Catalonia
Transcranial Direct Current Stimulation (tDCS) for the treatment of neuropsychiatric conditions
Neuromodulation interventions and EEG biomarkers for executive function in healthy and clinical populations
Executive function is …
What is it like as a woman to prepare for and enter a science and engineering workforce where men hold almost 70% of available jobs? …
State-of-the-art of numerical head modeling in tES: methods and applications
Numerical head models in transcranial electrical …
In 2019 I received the “Dona TIC” award by the Catalan government to women in STEM fields. The goal of this award is to recognize and …
This chapter is part of the book “Sex and Gender Bias in Technology and Artificial Intelligence: Biomedicine and Healthcare Applications”, which will be published this upcoming March 2022.
The book details the integration of sex and gender as critical factors in innovative technologies (artificial intelligence, digital medicine, natural language processing, robotics) for biomedicine and healthcare applications. By systematically reviewing existing scientific literature, a multidisciplinary group of international experts analyze diverse aspects of the complex relationship between sex and gender, health and technology, providing a perspective overview of the pressing need of an ethically-informed science. The reader is guided through the latest implementations and insights in technological areas of accelerated growth, putting forward the neglected and overlooked aspects of sex and gender in biomedical research and healthcare solutions that leverage artificial intelligence, biosensors, and personalized medicine approaches to predict and prevent disease outcomes. The reader comes away with a critical understanding of this fundamental issue for the sake of better future technologies and more effective clinical approaches.