Mihaela-Diana obtained her Bachelor’s Degree in Biomedical Engineering from Politecnico of Milan in Italy, followed by a Master’s in Life Science Engineering at EPFL in Switzerland.
During her Master’s, she attended biological and computational courses and conducted research projects in the EPFL’s laboratories of Behavioral Genetics, and Computational Biology and Theoretical Biophysics. In her final year, she also completed an internship at Nestle’s Research in the Data Analytics Department. These experiences strengthened her interest in the intersection of biology and computational methods, leading her to undertake her Master’s Thesis at Yale University in Renato Polimanti’s Lab of Psychiatric Genetics. During her time there, she worked on a project entitled “Brain-Wide Mendelian Randomization of Anxiety Disorders and their Symptoms,” analyzing GWAS summary statistics from UK Biobank, Million Veteran Program, and FinnGen biobanks.
She developed a deep interest in genetics, particularly in causal inference analysis. Motivated by this, she decided to join the Statistical Genetics group at the University of Lausanne as a Ph.D. student. In her doctoral research, she will continue exploring causal inference methods and their application, with a main focus on non-linear Mendelian Randomization.