Postdoctoral Researcher
Data scientist with 6+ years experience developing deep learning methods to solve biological problems and streamlining high-throughput sequencing data analysis in high-performance computing environments.
Interests: Bioinformatics, Data science, Metagenomics, Artificial Intelligence
Clustering of viral population through identification of shared genetic modules
python horizontal gene transfer viral metagenomics
Project Site
Metagenomic binning of viral contigs
pytorch clustering metagenomics whole genome sequencing
Project Site
Development of bioinformatics pipelines with Nextflow
nextflow containerization high-performance computing metagenomics
Project Site
Imputation of missing values in single-cell RNA-seq data using Deep Learning
TensorFlow Imputation Single-cell RNA-seq
Project Site08 Dec 2020
Literature Review Improving interpretation of microbiome studies by incorporating phylogenetic information Publications First author Arisdakessian, C.G., Nigro, O.D., Steward, G.F., Poisson, G. and Belcaid, M., 2021. CoCoNet: an efficient deep learning tool for viral metagenome binning. Bioinformatics, 37(18), pp.2803-2810. Arisdakessian,...
PhD Portfolio
01 Dec 2020
From a young age, I enjoyed learning about mathematics and foreign languages, which I explored in my high school coursework. As a mix of mathematics and languages, computer science naturally appealed to me. In pursuit of this interest, I began...
PhD Portfolio
01 Dec 2020
Evidence of MS Degree Obtained joint MSc. Degree from the École Centrale Lyon (France), and Université Claude Bernard Lyon 1 (France) Results of Qualifying Exam. Exam passed on May 16, 2019 Details with ICS Graduate Chair
PhD Portfolio