Dr. Francesco Zonta has a background in Theoretical and Mathematical Physics, specializing in Statistical Mechanics and Thermodynamics. He completed his Ph.D. in Physics at Padua University, where he studied the connection between statistical and topological properties of polymers. During his doctoral work, his research interests shifted towards simulating biological macromolecules, particularly DNA and proteins. After completing his Ph.D., he worked as a postdoctoral researcher at the Venetian Institute of Molecular Medicine (VIMM) in Padua. There, he developed a computational model using Quantum Mechanics and Molecular Dynamics simulations to study gap-junction hemichannels. He then moved to the Shanghai Institute for Advanced Immunochemical Studies (SIAIS) at ShanghaiTech University as a Research Associate Professor. At SIAIS, he directed the Informatics and Computation Platform and later became a Co-PI in the Laboratory of Computational Biology. In 2023, Dr. Francesco Zonta joined Xi'an Jiaotong-Liverpool University (XJTLU) as an Associate Professor in the Department of Biological Sciences. His current research focuses on developing computer-aided methods for drug design, especially for antibodies. He also works on multiscale simulations of biological systems and the development of machine learning force fields.

My research focuses on modeling biological systems using multiscale approaches, with an emphasis on important drug targets. I specialize in studying Connexin hemichannels, investigating how mutations alter their permeation properties and contribute to major diseases. This work has expanded to include modeling and designing antibodies that can interact with Connexin hemichannels and other targets, aiming to treat previously incurable genetic disorders. Additionally, my research encompasses developing new force fields using Machine Learning techniques to enhance molecular simulations, as well as modeling COVID-19 spread in populations to understand how interventions can mitigate infections. Throughout these projects, I employ various computational methods, ranging from atomistic Molecular Dynamics simulations to larger-scale population models, to gain comprehensive insights into complex biological systems and their interactions.

2023 - Associate Professor, XJTLU, Department of Biological Sciences, School of Science

2015-2023 - Research Associate Professor, ShanghaiTech University, SIAIS

                     Director of the Bioinformatic and Computational Biology Platform
                     Co-PI of the Laboratory of Computational Biology

2011-2015 - Young Researcher, Padova University, Department of Physics and Astronomy

2007 - 2011 - Post Doc, Venetian Institute for Molecular Medicine

2023/24 BIO311 Modeling for Computational Biology

2023/24 SCI002 Scientific Principles and Methods

2022/23 APH408 Computer-assisted Drug Development