Research in this area covers the broad spectrum of intersection between computer science and chemistry, from the traditional aspects of scientific programming, high-performance (HPC) and high-throughput (HTC) computing, to the integration of machine-learning approaches and cutting edge virtual-reality technology (from head-mounted displays for the exploration of potential-energy surfaces to a room-sized environment for the immersive analysis of chemical bonding). Current interest is in the exploitation of artificial-intelligence techniques in chemistry, with a focus on generative models for molecular discovery.

Research in this area focuses on the analysis of intermolecular interactions in terms of electron-charge redistribution and has led to the development in collaboration with others of the Natural Orbitals for Chemical Valence/Charge Displacement (NOCV/CD) analysis scheme, providing a framework whereby different bond components (such as σ-donation and π-backdonation) can be quantitatively disentanlged. Applications target coordination bonding and noncovalent interactions. The methodology has been extended to the relativistic context and further refined for the treatment of local and/or curvilinear charge flows. Another research topic in the area of electronic structure is relativistic DFT, with applications to heavy- and superheavy-element chemistry.

Research activity in this area focuses on the development and application of methods and tools for the modeling of gas-phase few-atom reaction dynamics and kinetics, and includes the development of the Grid-Empowered Molecular Simulator GEMS with applications to atom-diatom reactive systems including H + H2, N + N2, O + O2, Li + HF, and C + CH+,  the development of StarRate, a computer program for modeling the kinetics of multi-step astrochemical reactions, and exploring the versatility of unconventional coordinates for the description of reactive processes. Current interest is in quantum and mixed quantum-classical approahces to nonadiabatic nulcear dynamics.

In collaboration with Prof. Antonino Polimeno and Prof. Mirco Zerbetto, research in this area focuses on the computational development of techniques and tools for the stochastic modeling of the dynamical behaviour of macromolecules in solution, with emphasis on the prediction of spectroscopic (e.g. NMR) observables and on the exploration of interpretative tools for molecular flexibility, such as the roto-conformational tensor obtained by imposing a diffusive regime to a previously defined Fokker-Planck framework.