Emanuel Weitschek's teaching activities

SP-BRAIN: scalable and reliable implementations of a supervised relevance-based machine learning algorithm.
SP-BRAIN a supervised machine learning algorithm based on Big Data technologies and applied on the prediticition of DNA splicing sites has been released.

Classification of Large DNA Methylation Datasets for Identifying Cancer Drivers.
BIGBIOCL an algorithm that can apply supervised machine learning methods to datasets with hundreds of thousands of features for the extraction of alternative and equivalent classification models has been published.

Combining EEG signal processing with supervised methods for Alzheimer's patients classification.
A new procedure for classifying EEG signals has been designed and applyed to real demented and Alzheimer's diseased patients.

A novel method and software for automatically classifying Alzheimer's disease patients by magnetic resonance imaging analysis.
A new paper, method, and software for classifying Magentic Resonance Images has been published in Computer Methods and Programs in Biomedicine.

TCGA2BED: extracting, extending, integrating, and querying The Cancer Genome Atlas.
A software tool to search and retrieve TCGA data and convert them in the structured BED format for their seamless use and integration has been released.

Emanuel Weitschek's teaching activities take place at the Department of Engineering of Uninettuno International University. Previously, Emanuel teached at the Department of Engineering of Roma Tre University.

Courses

Emanuel Weitschek is professor for following courses:

Emanuel Weitschek was teaching assistant for following courses at the Department of Engineering of Roma Tre University:

Supervised students

Emanuel Weitschek supervised following students during their final dissertation:

Lorenzo Vaccaro: Biological sequences (CNEs) classification, 2016
Eleonora Cappelli: Genomic query language, 2016
Andrea Cremesini: Gene expression data analysis and integration, 2016
Lorenzo Di Nardo: Cancer data management, 2016
Giovanni Lo Monaco: Biological networks integration, 2016
Daria Monopoli: Clinical data management, 2016
Amgad Raafat Khalaf Shehata: Mobile networks, 2016
Pasquale La Porta: Internet of things, 2016
Pierangelo Punzi: Internet of things, 2016
Massimo Di Lorenzo: Time series analysis, 2016
Alessandro Pasi: A software for document management, 2016
Alessandro Ingrosso: Classification of Breast Cancer patients, 2015
Eleonora Bernasconi: Data mining in the electric power market, 2015
Alessio Cialini: Alzheimer's patients classification through EEG signals, 2015
Mattia Iodice: NGS variant calling with Google Genomics, 2015
Davinder Kumar: NGS reads comparison with alginment free techniques, 2015
Davide Razzino: BioSA: a biological sequences classification software, 2015
Cristiana Astolfi: Worflow management for RNA-Seq data classification, 2014
Valerio Cestarelli: Multiple classification solutions via feature elimination, 2014
Alessandro Giacomini: Gene expression classification and clustering software, 2013
Gabriele Giammusso: Gene expression classification and clustering software, 2012
Giulia Brunori: Species classification with DNA Barcode sequences, 2012
Federico Russo: A GUI for gene expression data classification and clustering, 2012

Emanuel collaborated to the supervision of Giulia Fiscon, PhD in Computer Engineering at Sapienza University.

Available theses

Please take a look at the projects section and contact me, if you like to investigate one of those topics for your final bachelor or master dissertation.

Graduation commission

Emanuel Weitschek is member of the graduation commission for the bachelor and master degrees in Computer Engineering at the Department of Engineering of Uninettuno International University.
Previously, he was member of the graduation commission for the bachelor and master degrees in Computer Engineering at the Department of Engineering of Roma Tre University.
He has been reviewer of several master and bachelor theses.