Gfeller Lab members

unil web full screen image 1200x300 (5).png

Mariia BILOUS
Gfeller Lab Mariia Bilous-crop588x572.jpg

PhD student
CONTACT ME 

Research interest

I am interested in computational methods applied to biological issues, in particular, cancer. For my PhD, I am developing a method for the simplification of large and complex scRNA-seq data, named super-cell. I am also investigating whether and how simplified scRNA-seq data can be used for the downstream analyses. Another fascinating part of my PhD is the analysis of scRNA-seq data of tumor-infiltrating immune cells.

Background

For my Master's degree, I worked on the mathematical modeling of the dynamic of brain metastases at Inria, Bordeaux. I studied Biomechanical Engineering at Ecole Polytechnique / Paris-Saclay and System Analysis at Taras Shevchenko National University of Kiev. I joined the laboratory of Pr David Gfeller in November 2017.

Giancarlo CROCE
Gfeller Lab Giancarlo Croce-crop851x925.jpg

Postdoctoral researcher
CONTACT ME

Research interest

I’m currently a postdoctoral researcher & Marie Curie fellow in the Gfeller Lab. My work centers on developing data-driven approaches to model and predict the interactions between T cells and cancer epitopes. Accurate predictions can narrow down the list of T cell candidates for personalized cancer immunotherapies, and significantly accelerate cancer immunotherapy clinical developments.

Background

I completed my PhD within the Martin Weigt Statistical Genomics and Biological Physics Lab at Sorbonne University, Paris in 2019. A fundamental question in computational biology is how to extract the key properties of a protein from its amino acid sequence. By combining tools from machine learning with up-to-date approaches from statistical physics, I developed sequence-based computational tools to model and predict protein structures, interaction networks and evolutionary dynamics. Prior to my PhD, I completed a B.Sc. at the University of Pavia (Italy) and an M.Sc. at the Ecole Normale Supérieure, Paris in theoretical and statistical physics.

Simon EGGENSCHWILLER
seggen.jfif

PhD student
CONTACT ME

Research interest

I focus on the development of a pan-allele HLA-I binding predictor. I incorporate recent peptide data that has been generated by Mass Spectrometry to have the most accurate and complete dataset available. In addition, I also integrate phosphorylated peptides to continue previous work that has been done by people in the group.I focus on the development of a pan-allele HLA-I binding predictor. I incorporate recent peptide data that has been generated by Mass Spectrometry to have the most accurate and complete dataset available. In addition, I also integrate phosphorylated peptides to continue previous work that has been done by people in the group.

Background

I finished my studies at the EPFL in 2018, where I obtained my MSc in physics. Along with that Master's degree, I also did a Minor in Computational Sciences. Combining these two fields, I was fortunate to work in the research group of Paolo De Los Rios, where I applied neural networks to understand the conformation of proteins.

Aurélie GABRIEL
Gfeller Lab Aurelie_Gabriel-crop1301x1352.jpg

Postdoctoral researcher
CONTACT ME

Research interest 

To expand my background on cancer genomics and motivated by my interest in immuno-oncology, I joined the lab of Pr David Gfeller in March 2021 as a postdoctoral researcher. I work on computational methods for the analysis of cellular diversity in tumors. These include immune deconvolution methods predicting the cellular composition of bulk samples and methods simplifying and improving the analysis of single-cell datasets which have enabled to study tumor heterogeneity with high precision in the past years.

Background 

I graduated in 2017 from INSA Lyon, where I specialized in bioinformatics. During that time, I undertook two internships in cancer research, at the Synergie Lyon Cancer bioinformatics platform and at IARC-WHO, during which I analyzed next generation sequencing data (WGS ,WES). I then completed a PhD in oncogenomics under the supervision of Dr McKay and Dr Foll at IARC-WHO, in the Genetic Cancer Susceptibility group. My work consisted in integrating somatic and germline multi-omics data to improve our understanding of lung cancer, using computational biology.

Julien RACLE
jracle-crop217x222.jfif

Research associate
CONTACT ME

Research interest

I am developing novel computational tools to study and analyze the interactions between cancer and immune cells. I am building upon large HLA peptidomics datasets and other data to build tools to predict the best candidate (neo-)epitopes that could then be used e.g. to develop vaccines against cancer or other viruses. I am also studying the tumor microenvironment, which plays a fundamental role in patients' survival and response to immunotherapy. For this, I develop tools to estimate the fraction of immune and cancer cells based directly on bulk RNA-seq data.

Background

I joined the laboratory of Pr David Gfeller in 2015 as a postdoctoral researcher and became a research associate in 2020. I had previously done my PhD thesis at EPFL, the Swiss Federal Institute of Technology in Lausanne, working in computational systems biology under the supervision of Pr Vassily Hatzimanikatis. During my thesis, I undertook a 7-month internship at Merrimack Pharmaceuticals, Cambridge, MA (USA), a company developing drugs against cancer. I had also obtained my master's at the EPFL, working in particle physics and cosmology, where, in addition to the rigor of physics, I obtained a strong background in mathematics and programming.

Marthe SOLLEDER
msolleder-1.jfif

PhD student
CONTACT ME

Research interest

My research focusses on deciphering the landscape of HLA-I and HLA-II phosphopeptidomes as well as the prediction of phosphorylated HLA-I and HLA-II ligands. Through curation of data generated by Mass Spectrometry – based immunopeptidomics approaches, phosphorylated peptide interactions with HLA-I and HLA-II molecules are identified and specific characteristic of these antigens detected. Additionally, I am working on developing computational tools to facilitate future identification of such phosphorylated peptides as well as their role in immune recognition of infected or malignant cells.

Background

I did my bachelor’s and master’s studies at the Freie Universität/Charité Universitätsmedizin in Berlin during which period I worked as a student assistant at the Konrad Zuse Institut. I then moved to Pr David Gfeller’s laboratory at the Université de Lausanne for my PhD, which I finished in October 2020.

Daniel TADROS
Gfeller Lab Daniel Tadros-crop1573x1606.jpg PhD student
CONTACT ME

Research interest

I have been working as a PhD student, under the supervision of Pr David Gfeller in his laboratory, since May 2021 on the development of algorithms for epitope predictions. The main goal of the project is to unravel the rules of antigen presentation and T-cell recognition specificity which are the cornerstone of cancer immunotherapy.

Background

I obtained my Bachelor and Masters' degrees in Life Sciences engineering from the École Polytechnique Fédérale de Lausanne (EPFL). I carried out my MSc thesis in the Medical Image Processing Lab of Pr Dimitri Van De Ville. The project focused on fMRI data processing and statistical analysis to study the dynamic properties of brain activity in preterm children.

TOP ^

images (c) unsplash/ian schneider-tam/helena lopes

Follow us:  

CONTACT

DO_Pls-2665.jpg

David Gfeller
Associate Professor
Ludwig adjunct scientist

Laboratory D. Gfeller

Department of oncology UNIL CHUV
Ludwig Institute for Cancer Research Lausanne

Ludwig Lausanne RGB-crop461x374.jpg (Print)

Phone +41 21 545 10 69
E-mail david.gfeller@unil.ch

TOP ^

The Gfeller Lab is based at:

AGORA Cancer Research Centre
Rue du Bugnon 25A
CH-1005 Lausanne
Switzerland

Agora_2018_151_-crop3166x3841-resize158x191.jpg

Ch. des Boveresses 155 - CH-1066 Epalinges
Switzerland
Tel. +41 21 692 59 92
Fax +41 21 692 59 95
Ludwig Cancer Research Université de Lausanne Centre Hospitalier Universitaire Vaudois (CHUV)