altText copyrightStatement

Francesco Zonta

Associate Professor

Calculated based on number of publications stored in Pure and citations from Scopus

Research activity per year

Personal profile

Personal profile

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.

Research interests

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

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Education/Academic qualification

Ph.D. in Physics, Padova University, 2007

MSc in Physics, Padova University, 2003

External positions

Adjunct Lecturer, Taylor's University Malaysia

1 Jan 202431 Dec 2025

Person Types

  • Staff


Dive into the research topics where Francesco Zonta is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
  • 1 Similar Profiles

Collaborations and top research areas from the last five years

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or