Cellular Engineering Lab - Research
Our lab works at the interface between physics, mathematics, computer science, engineering and biology. We aim at establishing end to end engineering principles for biological systems, from designing and building tools to imaging and learning from experiments, to infer prime principles of biological dynamics.
Computer Vision for Cellular Analysis
Using off the shelf methods to analyze cellular images is not ideal. The collection of large cellular datasets makes it important to create new instruments and algorithms for image analysis that are general enough to be portable to different microscopy environment, yet tailored to the problem at hand.
Our group works on all the aspects of image analysis of cells, from building novel paradigms in microscopy to using supervised and semi-supervised data annotation, to cellular detection, segmentation, image reconstruction and tracking.
We make use of custom supervised and unsupervised algorithms for cellular image analysis, spanning multiple scales, which use machine learning to obtain ultra-accurate results.
Computer-Aided Synthetic Biology
Synthetic biology is the science which aims at engineering new biological structures. In most industrial applications, synthetic biology undergoes long and costly trial and error phases.
We work on rationalizing the process of making new biological structures using both forward (mathematical) models and data-driven (machine learning) methods, with the intent of extracting, inferring and establishing design principles for biological machines.
Design of synthetic antivirals and study of viral dynamic a multiple scales
Viruses, especially RNA viruses, undergo rapid evolution during the infection process. This makes is very hard to engineer effective antivirals. By making use of rational design, and through a thorough understanding of the dynamic and evolution of the viral populations at multiple scales, we aim at producing candidate synthetic constructs to combat viral infections.
This process allows us to uncover, in many cases, fundamental features characterizing the viral infection process, the evolution of the viral species, and, more generally, the forces which shape the evolution of rapidly mutating organisms.