Matteo’s research is very inter-disciplinary, spanning different disciplines such as analytical chemistry and data analytics. He is primarily involved in the development of new solutions, based on cutting-edge instrumental and/or computational methods, to improve current capabilities for the analysis of chemical traces, as well as the interpretation of related findings in a forensic context. In particular, he is interested in the identification of chemical residues in complex matrices, as well as their source attribution and association, through the application of advanced profiling techniques and machine-learning methods. Notable recent achievements include the development of an AI-driven approach for the reconstruction of mutable chemical profiles to enhance evidential linking of energetic materials in the investigation of shooting incidents and terrorist attacks. His interests further extend in the assignation of evidential values to the acquired evidence through the use of probabilistic methods.
The ultimate aim of Matteo’s research is to provide the scientific community with novel tools to enhance the information extracted from forensically-relevant materials, in order to promote the impact of chemical evidence in both investigative and judicial settings.
Research Student Supervision Interests(1) Development of next-generation analytical and data treatment approaches for enhancing possibilities in forensic profiling of chemical residues; (2) Developing new, high-throughput and comprehensive, headspace approaches for the forensic analysis of ignitable liquids
PhD, Chemistry, University of Lausanne
PhD in Forensic Science2010 - 2015
MSc, Chemistry, University of Lausanne
MSc in Forensic Science2008 - 2010
BSc (Hons), Chemistry, University of Lausanne
BSc in Forensic Science2005 - 2008
Fellow of the Higher Education Academy, FHEASep 2019 -
Professional Member of the Chartered Society of Forensic Sciences, MCSFSSep 2017 -
Member of the Royal Society of Chemistry, MRSCNov 2016 -