Victoria Peterson
PhD - Research in Brain-Computer Interfaces (BCI)
Victoria Peterson
Faculty Researcher @ IMAL-CONICET (Santa Fe, Argentina)
Associate Professor @ FIQ-UNL (Santa Fe, Argentina)
Collaborator @ Brain Modulation Lab (Boston, MGH-Harvard, US).
Group leader of the Applied Computational Neuroengineering Lab (NiCALab) @IMAL-CONICET (Santa Fe, Argentina)
News!
https://twitter.com/mediachicas/status/1352374413170270209
[Sep 2024] Award ANCEFN. "Ciencia de la Ingeniería y la Tecnología".
[April 2024] Speaker @AI in Epilepsy Conference. "AI in measuring treatment responses in neuromodulation"
[March 2024] Interview @Clarín newspaper: "Nos podemos comunicar con una computadora directamente desde nuestra mente. Es un gran desafío". Have a look here
[September 2023] Joining the membership committee of the BCI Society
[Jun - Aug 2023] Participating at the IEEE Brain Wellness Working Group. Giving inputs on the document "Ethical, Legal, Social, and Cultural Implications of Neurotechnologies for Wellness"
[August 2023] Podcast Episode "A Todo Neuro": Uniendo Mente y Máquinas para Transformar Vidas. Check it out here
[June 2023] Talk at Google Zurich. "Enhancing Health through Machine Learning and Brain Computer Interfaces "
[June 2023] Short lecture at the BCI meeting 2023. "Spatial filtering for movement decoding in invasive and non-invasive BCI"
[May 2023] Podcast Episode "Neurocareers: Doing the Impossible": Innovating BCI decoding with Victoria Peterson. Check it out here
[May 2023] New publication. "Deep net detection and onset prediction of electrographic seizure patterns in responsive neurostimulation" @Epilepsy. More info here
[Nov 2022] New publication. "Movement decoding using spatio-spectral features of cortical and subcortical local field potentials" @Experimental Neurology. More info here
[April 2022] Starting new position @IMAL-CONICET-UNL
[Sep 2021] BCI award 2021 nomination. Our BCI research has been nominated for the BCI Award 2021
[Aug 2021] New publication. "Transfer learning based on Optimal Transport for Motor Imagery Brain-Computer Interfaces" @TBME. Check it out here
[Jun 2021] MI-BCI low-cost dataset release. It is in BIDs format! You can download it @OpenNeuro
About me
I am currently a CONICET Faculty Researcher at the Instituto de Matemática Aplicada del Litoral, IMAL-UNL-CONICET, Argentina, where I lead a group on Applied Computational Neuroengineering. We investigate decoding models for invasive and non-invasive neuroscillations with application to Brain-Computer Interfaces. I am also an Associate Professor in the Mathematics department at Facutad de Ingeniería Química, FIQ-UNL, Argentina where I teach optimization and machine learning, data science, and related courses.
From 2021 to 2022, I worked as a Postdoc research fellow at the Brain Modulation Lab, Massachusetts General Hospital, Boston, US, and a Research Affiliate of the Harvard Medical School, under the supervision of PhD MD Mark Richardson. Before that (2019-2021) I was a Postdoc at the Instituto de Matemática Aplicada del Litoral, IMAL-UNL-CONICET, Argentina, under the supervision of Prof. Ruben Spies. I did my PhD in machine learning for brain decoding (2014-2019) at the Instituto de Investigación en señales, sistemas e inteligencia computacional, sinc(i)-UNL-CONICET, Argetina.
I work in the development of computational solutions for brain signal decoding with application to Brain-Computer Interface (BCIs) for neurophysiological decoding. I was introduced to the BCI word research when I was doing my Bachelor's degree thesis. I have since been deeply fascinated by BCIs, with a desire to understand the depth and beauty of the underlying mathematical models, and use the power of advanced signal processing and machine learning tools to make this technology more robust and applicable.
In 2014, driven by the desire to deepen my knowledge in machine learning and BCIs, I started my Ph.D. studies in the field of BCIs, supported by a five-year competitive fellowship awarded to me by the National Council of Scientific and Technical Research of Argentina, (CONICET). In 2017 I made a research visit stay at the Rehabilitation Engineering Laboratory at ETH Zurich thanks to the Doctoral Exchange Grant awarded to me by the Zeno Karl Schindler Foundation (ZKS, Switzerland).
My main research goal is to help toward the development of computer-based technologies that improve the quality of life of people with neurological disorders.
Education
PhD in Engineering, 2018
Bioengineer, 2013
Interest
Machine learning methods for brain signal decoding
Invasive and non-invasive neurophysiology
Positions
2022: Associate Professor @ FIQ-UNL, Argentina.
2022: Faculty Researcher (Assistant) @ IMAL-UNL-CONICET, Argentina.
2021-2022: Research Fellow @ BML-MGH-Harvard, USA.
2019-2021: Postdoc @ IMAL-UNL-CONICET, Argentina.
2016-2020: Teaching assistant @ FI-UNER, Argentina.
2017: Visiting PhD student @ RELAb-ETHZ, Switzerland.
2014-2019: PhD student @ sinc(i)-UNL-CONICET, Argentina.