Laura Dubreuil Vall

Research in Neuroscience and Machine Learning

Laura Dubreuil Vall

Laura Dubreuil Vall

Engineer and Neuroscientist

Genentech (Roche)

Biography

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 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 the 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 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.

Interests
  • Neurotechnology
  • Electroencephalography (EEG)
  • Brain stimulation
  • Machine learning
  • Product Development
  • Healthcare Strategy
Education
  • 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

Experience

 
 
 
 
 
Genentech (Roche)
Clinical Scientist, Neurotech Innovation Lead
Jul 2020 – Present San Francisco, CA (US)
As a Neurotech Innovation Lead at the Neuroscience Product Development division of Genentech/Roche, my goal is to identify and develop new technologies at the intersection of engineering, data/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 drug responses.
 
 
 
 
 
Neuroelectrics
Technical Manager
Sep 2014 – Jul 2020 Boston, MA (US)
  • Lead the expansion of the company to the US, creating a new team and managing relationships with partners and KOLs in the scientific community.
  • Supported product strategy of a medical wearable device for EEG recording and non-invasive brain stimulation (tDCS/tACS/tRNS).
  • Managed 300+ accounts with large universities and hospitals, meeting over 120% of revenue goals every year in US and Canada.
  • Management of clinical studies and data collection in collaboration with hospitals and universities across the US, including FDA clinical studies and 510k submissions.
 
 
 
 
 
Harvard Medical School, Neuropsychiatry and Neuromodulation Lab
Research Fellow
Sep 2015 – Oct 2020 Boston, MA (US)
  • Performed clinical research on the use of EEG as a biomarker for the neuromodulation of executive functions in healthy controls and ADHD patients.
  • Designed a deep Learning system based on convolutional neural networks to diagnose ADHD patients and explore new biomarkers based on their EEG signals.
 
 
 
 
 
Starlab
Research Engineer, Project Manager
Jul 2012 – Aug 2014 Barcelona
  • Signal processing and data analysis for the design and development of systems based on electroencephalography (EEG) for brain computer interfaces (BCI), Neurofeedback and health/medical applications.
  • Research in transcranial Current Stimulation (tDCS, tACS and tRNS) for different applications, such as learning and cognitive enhancement or the treatment of chronic pain, post stroke rehabilitation, addictive disorders and depression, among others.
 
 
 
 
 
Ernst & Young
Consultant in Life Sciences
Oct 2011 – Apr 2012 Barcelona
Strategic and management consulting in life sciences industries, including Biotechnology, Healthcare, Pharmaceutical and Medical Devices.
 
 
 
 
 
Massachusetts Institute of Technology (MIT)
Research Scholar
Feb 2011 – Aug 2011 Boston, MA (US)
  • Improved the design of an underwater acoustic video transmission system by adding video compression techniques and signal processing techniques to compensate for the Doppler effect. Supervisor: Dr. Milica Stojanovic and Dr. Chryssostomos Chryssostomidis.
  • Evaluated the effects of the Social Impact Assessment prepared for interstate management of herring in the Northeast US. Supervisor: Dr. Madeleine Hall-Arber.
 
 
 
 
 
Institute of Photonic Sciences (ICFO)
Intern
Jul 2009 – Sep 2009 Barcelona
Worked in the “Quantum engineering of light” team by exploring fundamental aspects of quantum theory and enabling the implementation of applications that might require specific types of quantum or classical light, especially in communications and high-resolution probing and imaging. Supervisor: Dr. Juan Pérez.

Projects

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Tabula Rasa

Tabula Rasa

Trusted Biometrics under Spoofing Attacks

Beaming

Beaming

Beaming through augmented media for natural networked gatherings

AsTeRICS

AsTeRICS

Assistive Technology Rapid Integration & Construction Set

Non-invasive brain stimulation

Non-invasive brain stimulation

Transcranial Direct Current Stimulation (tDCS) for the treatment of neuropsychiatric conditions

Galvani

Galvani

Controlling epileptic brain networks with computationally optimized weak electric fields

Machine Learning for EEG-based biomarkers

Machine Learning for EEG-based biomarkers

Deep Learning with EEG Spectrograms enable ADHD diagnosis and Parkinson’s prognosis

Recent Publications

Quickly discover relevant content by filtering publications.
(2021). Transcranial Direct Current Stimulation to the Left Dorsolateral Prefrontal Cortex Improves Cognitive Control in Patients With Attention-Deficit/Hyperactivity Disorder: A Randomized Behavioral and Neurophysiological Study. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging.

Cite Project DOI

(2021). Personalized, Multisession, Multichannel Transcranial Direct Current Stimulation in Medication-Refractory Focal Epilepsy: An Open-Label Study. Journal of Clinical Neurophysiology.

Cite Project DOI

(2020). Transcranial Direct Current Stimulation Modulates Dysexecutive Deficits and its Neurophysiological Signatures in Attention-Deficit Hyperactivity Disorder. J31st Annual Meeting of the American Neuropsychiatric Association. J Neuropsychiatry Clin Neurosci.

Cite DOI

(2019). The multiscale dynamics of resting-state brain activity is associated with the performance of dual task standing postural control in older adults. International Society of Posture and Gait Research Congress.

Cite Poster

Contact

  • 1 DNA Way, South San Francisco, CA 94080