Alessandro Barberis

Hi everyone, my name is Alessandro and I am a Senior Computational Biologist at WhiteLab Genomics, a French company pioneering the use of artificial intelligence (AI) for gene and cell therapy development. At WhiteLab Genomics, I leverage my expertise to propel these advancements, including analysing single-cell data for Adeno-Associated Virus (AAV) vector design, leading synthetic promoter projects, and developing computational pipelines.

I am also an Academic Visitor in the Nuffield Department of Surgical Sciences at the University of Oxford, where I exploit machine learning methodologies to identify biological markers of diagnosis, prognosis, and response to treatment in cancer cohorts.

biography

I graduated from the University of Pavia (Italy) in Computer Science Engineering with a Thesis focusing on the identification of an order parameter in Monte Carlo simulations of dipolar systems on hexagonal lattices.

After completing my Master’s Degree, I started a PhD in Electronics, Computer Science, and Electrical Engineering within the Custom Computing and Programmable Systems group at the same University. During my doctoral years, I specialised in High Performance Computing and Data Processing, focusing on Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs) technologies to develop real-time solutions for image analysis. Despite my strong interest in computer science, I have always been passionate about biomedical sciences. This led me to attend extra courses during my doctorate, including Physiology and Histology courses held at my University and the Massachusetts Institute of Technology (MIT) online course “7.00x: Introduction to Biology - The Secret of Life,” for which I earned an Honor Code Certificate.

In 2014, I joined the Department of Oncology as a postdoc in the Computational Biology and Integrative Genomics group. Under the guidance of Professor Francesca Buffa, I have been able to expand my computational expertise, while building my knowledge of cancer genomics.

In 2022, I accepted a senior position in Professor Valentine Macaulay’s IGF laboratory within the Nuffield Department of Surgical Sciences. In Professor Macaulay’s group, I continued working on cancer genomics, focusing on the contribution of insulin-like growth factors (IGFs) to prostate cancer biology.

In 2024, I began my role as a Senior Computational Biologist at WhiteLab Genomics while continuing to contribute to the academic community as an Academic Visitor at the University of Oxford.

research summary

The explosion of biomedical data production in recent years has provided unprecedented opportunities to deepen our knowledge in this field and revolutionize medical diagnosis and treatment. My research interests lie at the intersection of computer science and biology, and I am passionate about developing and applying innovative computational methodologies that can help us better leverage this wealth of data to ultimately enable personalized medicine.

My research activity can be broadly summarised into two main areas:

(1) The development of novel, robust, and reproducible computational methodologies that can enable more rigorous and reliable research.

(2) The identification of new biological markers that have the potential to transform medical diagnosis and treatment.

Examples of projects I am working on include:

• The investigation of the contribution of insulin-like growth factors (IGFs) to prostate cancer biology.
• The derivation of unimodal and multimodal classifiers in different cancer types.
• The identification of circulating biomarkers to improve radiotherapy effectiveness in glioblastoma.
• The integration of multiple omics via artificial intelligence techniques.
• The development of software for the robust and reproducible derivation of machine learning models.