Team
The CDS Lab lab is based in Trieste, but some members are physically located across other institutes and, in that case, co-supervised with other PIs.
2022 Genomics England Research Summit (Giulio)
2022 Laboratory Meeting Epiphany (Giulio)
Principal Investigator
Prof. Giulio Caravagna, PhD
Current positions
- Associate Professor. Department of Mathematics and Geosciences, University of Trieste.
- Core Faculty, PhD program in Applied Data Science & Artificial Intelligence, University of Trieste.
- Adjoint Faculty, PhD program in Theoretical and Scientific Data Science, SISSA.
- Honorary fellow, The Institute of Cancer Research, UK.
Training:
- 2017-20, The Institute of Cancer Research, UK. With Andrea Sottoriva.
- 2015-17, University of Edinburgh, UK. With Guido Sanguinetti.
- 2011-15, University of Milan-Bicocca, Italy. With Giancarlo Mauri and Marco Antoniotti.
- 2011, PhD in Computer Science (University of Pisa, Italy).
- BSc, MSc in Computer Science (University of Pisa, Italy).
Postdoctoral scientists
PhD students
Dr. Alice Antonello
Applied Data Science & Artificial Intelligence PhD program (University of Trieste, Italy).
Training:
- MSc in Quantitative and Computational Biology (University of Trento, Italy);
- BSc in Biotechnology (University of Turin, Italy);
Topic: Bayesian models for aneuploidy from whole-genome sequencing.
Dr. Elena Buscaroli
Applied Data Science & Artificial Intelligence PhD program (University of Trieste, Italy).
Training:
- MSc in Data Science and Scientific Computing (University of Trieste, Italy);
- BSc in Genetics (University of Bologna, Italy);
Topic: statistical models for high-resolution image demultiplexing.
Dr. Salvatore Milite
Computational Biology PhD Program (European School of Molecular Medicine, Italy). Co-mentored with Andrea Sottoriva (Human Technopole).
Training:
- MSc in Data Science and Scientific Computing (University of Trieste, Italy);
- BSc in Molecular Biology (University of Padua, Italy);
Topic: statistical methods for longitudinal single cell sequencing.
Dr. Lucrezia Patruno
Computer Science PhD Program (University of Milan-Bicocca, Italy). Co-mentored with Marco Antoniotti and Alex Graudenzi (Milan-Bicocca)
Training:
- MSc in Computer Science (University of Milan-Bicocca, Italy);
- BSc in Computer Science (University of Milan-Bicocca, Italy);
Topic: integration of single-cell RNA and ATAC sequencing.
Dr. Giovanni Santacatterina
Applied Data Science & Artificial Intelligence PhD program (University of Trieste, Italy). Co-supervised with Leonardo Egidi.
Training:
- MSc in Data Science and Scientific Computing (University of Trieste, Italy);
- BSc in Physics (University of Trento, Italy);
Topic: model-based statistical methods for single-cell data analysis.
Dr. Arianna Tasciotti
Applied Data Science & Artificial Intelligence PhD program (University of Trieste, Italy). Sponsored by an industrial fellowship from Plus.
Training:
- MSc in Data Science and Scientific Computing (University of Trieste, Italy);
- BSc in Physics (University of Trento, Italy);
Topic: inference of morphological features from tissue images.
Dr. Lucrezia Valeriani
Applied Data Science & Artificial Intelligence PhD program (University of Trieste, Italy). Co-supervised with Alberto Cazzaniga and Alessio Ansuini (Area Science Park).
Training:
- MSc in Data Science and Scientific Computing (University of Trieste, Italy);
- BSc in Genetics (University of Bologna, Italy);
Topic: statistical methods for long-reads sequencing.
Master and Bachelor students
Azad Sadr
Program: MSc Data Science and Scientific Computing.
Topic (MSc thesis): Bayesian mutational signatures from whole-genome sequencing data.
Lorenzo Taroni
Program: MSc Data Science and Scientific Computing.
Topic (MSc thesis): variational autoencoders for single-cell gene-set enrichment analysis
Clara Canavese
Program: MSc Physics of Complex Systems (Polytechnic University of Turin).
Topic (MSc thesis): stochastic processes for clonal evolution in cancer
Edoardo Insaghi
Program: BSc Statistics
Topic (BSc thesis): variational generalised linear models for differential expression.