Alfredo Vellido


I am currently an associate professor (formerly a Ramón y Cajal researcher) at CS / UPC, and part of the SOCO SGR Research Group
and the IDEAI Research Center. Member of the
CIBER-BBN, and the IEEE-CIS Data Mining and Big Data Analytics Technical Committee ,
in which I am Chair of the Task Force on Medical Data Analysis and a member of the Explainable Machine Learning (EXML) Task Force.
Member of the Editorial Boards of PLoS ONE and Neural Processing Letters.

CS academic coordinator at Escola Superior d’Enginyeries Industrial, Aeroespacial i Audiovisual de Terrassa (ESEIAAT)

Recently organized the WSOM+2019 Conference in Barcelona, Spain (June 26-28, 2019).

Recent invited talks: 
1st Industrial Conference on AI and Health (ICAIH 2019
), Milano, Italy, 2019:
 "Cautionary Tales about the Application of AI in Health"
Workshop on the Impact of Artificial Intelligence in Healthcare (UPF, Barcelona, Spain), 2019:
 "Interpretability, explainability, and rigurous validation of AI tools for clinical decison making"

2nd
Science for Dialysis Meeting: Artificial Intelligence at Bellvitge University Hospital (Barcelona, Spain), 2018:
"Social beasts: societal challenges of AI and ML in medicine"
(youtube video) 


Currently organizing conference special sessions/workshops
you might want to know about
:
ESANN 2021 (virtual event) "Interpretable Models in Machine Learning and Explainable Artificial Intelligence"

Some past special sessions/workshops
IJCNN 2021 (virtual event) "Transparent and Explainable Artificial Intelligence (XAI) for Health"
WCCI/IJCNN 2020 (Glasgow, Scotland, UK) "Explainable Computational/Artificial Intelligence Methods
"
IJCNN 2019 (Budapest, Hungary) "Explainable Machine Learning
"
IDEAL 2019 (Manchester, UK)
"Machine Learning in Healthcare"
ESANN 2019 (Bruges, Belgium) "Societal Issues in Machine Learning: When Learning from Data is Not Enough"

ESANN 2018 (Bruges, Belgium) "Deep Learning in Bioinformatics and Medicine",
IWBBIO 2018 (Granada, Spain)
"Interpretable Models in Biomedicine and Bioinformatics"
,

IJCNN 2017 (Anchorage, Alaska, USA) "Machine Learning for Enhancing Biomedical Data Analysis", and

NIPS 2017 (Long Beach, CA, USA) "Transparent and interpretable Machine Learning in Safety Critical Environments"

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