Alisa Kumbara

Foto,  October 3, 2025
Position
PhD student
Student
PhD in Intelligent Systems Engineering - 40° Ciclo (October 1, 2024 - September 30, 2027)
Curriculum
  • pdf   CV_eng   (pdf, en, 116 KB, 13/11/25)
  • pdf   CV_ita   (pdf, it, 110 KB, 13/11/25)

Alisa is a PhD student in Intelligent Systems Engineering at the Department of Engineering for Innovation Medicine, University of Verona. She earned her Bachelor’s degree in Biomedical Engineering from the Polytechnic University of Marche in 2022, where her thesis focused on developing EEG-based metrics for sound quality analysis. She then completed a Master’s in Medical Bioinformatics at the University of Verona in 2024, assessing the performance of Position Weight Matrix and Support Vector Machine models for predicting transcription factor binding sites. Her research focuses on developing algorithmic tools for large-scale genomic data analysis, with a particular emphasis on exploring genetic variation at both individual and population levels. She specializes in computational approaches for genome editing and regulatory genomics, aiming to bridge data science and molecular biology to advance precision medicine and genome engineering.

Modules

Modules running in the period selected: 0.
Click on the module to see the timetable and course details.


Di seguito sono elencati gli eventi e gli insegnamenti di Terza Missione collegati al docente:

  • Eventi di Terza Missione: eventi di Public Engagement e Formazione Continua.
  • Insegnamenti di Terza Missione: insegnamenti che fanno parte di Corsi di Studio come Corsi di formazione continua, Corsi di perfezionamento e aggiornamento professionale, Corsi di perfezionamento, Master e Scuole di specializzazione.

Research groups

InfOmics
Our research aims to analyse biomedical data efficiently, in particular we develop new methods to mining biological networks, integrate heterogeneous data, analyse omics, reconstruct pangenomes, analyse genomes haplotype-aware and to classify patients. We use theory coming from machine learning, data science, mathematics and graph theory.




Organizzazione

Strutture del dipartimento

Share