Francisco Carrillo-Perez

PhD in machine learning applied to bioinformatics.

Granada (Spain)

carrilloperezfrancisco at gmail dot com

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About me

My name is Francisco (Paco) Carrillo-Perez, and I hold a Ph.D. in machine learning applied to bioinformatics from the University of Granada. I am working now as a freelance postdoctoral researcher in the Gevaert's lab at Stanford University. I am mainly interested in multi-modal self-supervised learning and generative models for cancer research. In my spare time I like to climb, take long hikes, and read a good book!

Recent News

21/03/2024 New published publication in Nature Biomedical Engineering: Generation of synthetic whole-slide image tiles of tumours from RNA-sequencing data via cascaded diffusion models.
06/03/2024 New published publication in SoftwareX: SnapperML: A python-based framework to improve machine learning operations.
29/01/2024 New published publication in Cell Reports Methods: A 3D lung lesion variational autoencoder.
19/07/2023 New published publication in Cell Reports Methods: Synthetic whole-slide image tile generation with gene expression profile-infused deep generative models.
12/07/2023 New published publication in Nature Communications: Spatial cellular architecture predicts prognosis in glioblastoma.
27/06/2023 New published publication in Cancer Imaging: Performance comparison between multi-center histopathology datasets of a weakly-supervised deep learning model for pancreatic ductal adenocarcinoma detection.
02/06/2023 Invited talk at the Centro Andaluz de Biología del Desarrollo to talk about cross-modal synthetic data generation.
01/04/2023 Colleagues will be presenting our work at ACCR, you can check abstract here: Prediction of cancer transcriptomes from whole-slide images with Vis-Gene.
04/03/2023 New published publication in Nature Medicine: A deep-learning algorithm to classify skin lesions from mpox virus infection.
01/03/2023 Happy to rejoin the Gevaert's lab as a Freelance Postdoctoral Researcher!.
02/12/2022 New published publication in Trends in Molecular Medicine: Imaging genomics: data fusion in uncovering disease heritability.
10/04/2022 New published publication in the Journal of Personalized Medicine: Machine-Learning-Based Late Fusion on Multi-Omics and Multi-Scale Data for Non-Small-Cell Lung Cancer Diagnosis.
29/11/2021 New published publication in the Journal of Esthetic and Restorative Dentistry: Applications of artificial intelligence in dentistry: A comprehensive review.
22/09/2021 New published publication in the BMC Bioinformatics journal: Non-small-cell lung cancer classification via RNA-Seq and histology imaging probability fusion.
19/04/2021 New published publication in the Computers in Biology and Medicine journal: KnowSeq R-Bioc Package: The Automatic Smart Gene Expression Tool For Retrieving Relevant Biological Knowledge.
12/04/2021 Honored to become a Fulbright fellow! I will do a twelve-month research collaboration at Stanford University under the supervision of Professor Olivier Geavert starting October 2021.
22/03/2021 New published publication in the Journal of Dentistry: INFLUENCE OF BACKGROUND COLOR ON COLOR PERCEPTION IN DENTISTRY
19/02/2021 New published publication in the Neural Computing and Applications journal: Deep learning to classify ultra-high-energy cosmic rays by means of PMT signals

Where have you been?