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Dr Matteo Gallidabino

Senior Lecturer

Department: Applied Sciences

Matteo has a comprehensive education in forensic science that he obtained at the prestigious School of Criminal Justice (Ecole des Sciences Criminelles, ESC) of the University of Lausanne in Switzerland. Here, he received his BSc degree in 2008 and his MSc degree in 2010, both with First Class final awards. He later enrolled for a PhD programme and obtained his degree in 2016, with a thesis on the headspace analysis of volatile gunshot residue for estimating the time since discharge of spent cartridge casings.

During his time at ESC, Matteo held the positions of Graduate Teaching Assistant, Lecturer and Part-Time Researcher. He was particularly involved in teaching chemical criminalistics, forensic ballistics and gunshot residue analysis as part of both UG and PG programmes. In addition to this, he was involved in casework as an expert witness for a number of national and international cases, as well as in the development of enhanced learning web platforms to assist students in approaching evidence interpretation.

After his PhD, Matteo was awarded a personal research fellowship by the Swiss National Science Foundation (SNSF) for a Post-Doctoral Fellow position at King’s College London (KCL). Here, he led several research projects in forensic and environmental sciences, and was particularly involved in the development of a novel non-targeted, mass spectrometry method for the profiling of energetic materials. At the end of this two-years research stay, he joined Northumbria University in 2018, as a Senior Lecturer in forensic science.

Despite being still early on in his career, Matteo has published many papers in highly-ranked forensic and analytical journals. For his outstanding academic performance and high quality of research, he received two excellence awards, including a Faculty Prize in recognition of the exceptional results of his PhD thesis. Furthermore, he has been a Visiting Researcher at a number of police institutions, for example the Italian Carabinieri in Rome. Matteo has a successful track record in obtaining research grants and strong connections with a number of people in his field, thanks to collaborations with academic and industrial partners. He is a member of both the Royal Society of Chemistry and the Chartered Society of Forensic Science.

Matteo Gallidabino

Campus Address

A403, Ellison Building
Northumbria University
Newcastle upon Tyne
NE1 8ST

Qualifications

  • Chemistry PhD
  • Chemistry MSc
  • Chemistry BSc (Hons)
  • Fellow of the Higher Education Academy FHEA 2019
  • Professional Member of the Chartered Society of Forensic Sciences MCSFS 2017
  • Member of the Royal Society of Chemistry MRSC 2016

Research Themes and Scholarly Interests

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.

Key Publications

  • Please visit the Pure Research Information Portal for further information
  • A study on contactless airborne transfer of textile fibres between different garments in small compact semi-enclosed spaces, Sheridan, K., Palmer, R., Saltupyte, E., Gallidabino, M. 1 Oct 2020, In: Forensic Science International
  • Ion beam analysis (IBA) and instrumental neutron activation analysis (INAA) for forensic characterisation of authentic Viagra® and of sildenafil-based illegal products, Romolo, F., Sarilar, M., Antoine, J., Mestria, S., Strano Rossi, S., Gallidabino, M., Soares de Souza, G., Chytry, P., Ferraz Diaz, J. 4 Nov 2020, In: Talanta
  • Time since last discharge of firearms and spent ammunition elements: state of the art and perspectives, Gallidabino, M., Weyermann, C. 1 Jun 2020, In: Forensic Science International
  • Comparative Assessment of a novel photo-anthropometric landmark-positioning approach for the analysis of facial structures on two-dimensional images, Flores, M., Machado, C., Gallidabino, M., de Arruda, G., da Silva, R., de Vidal, F., Melani, R. May 2019, In: Journal of Forensic Sciences
  • Prediction of bioconcentration factors in fish and invertebrates using machine learning, Miller, T., Gallidabino, M., Macrae, J., Owen, S., Bury, N., Barron, L. 15 Jan 2019, In: Science of the Total Environment
  • Quantitative profile-profile relationship (QPPR) modelling: a novel machine learning approach to predict and associate chemical characteristics of unspent ammunition from gunshot residue (GSR), Gallidabino, M., Barron, L., Weyermann, C., Romolo, F. 21 Feb 2019, In: The Analyst
  • Targeted and non-targeted forensic profiling of black powder substitutes and gunshot residue using gradient ion chromatography – high resolution mass spectrometry (IC-HRMS), Gallidabino, M., Irlam, R., Salt, M., O’Donnell, M., Beardah, M., Barron, L. 23 Sep 2019, In: Analytica Chimica Acta
  • Age estimation by assessment of pulp chamber volume: a Bayesian network for the evaluation of dental evidence, Sironi, E., Taroni, F., Baldinotti, C., Nardi, C., Norelli, G., Gallidabino, M., Pinchi, V. 1 Jul 2018, In: International Journal of Legal Medicine
  • DNA methylation-based age prediction using massively parallel sequencing data and multiple machine learning models, Aliferi, A., Ballard, D., Gallidabino, M., Thurtle, H., Barron, L., Syndercombe Court, D. Nov 2018, In: Forensic Science International: Genetics
  • Machine learning for environmental toxicology, Miller, T., Gallidabino, M., Macrae, J., Hogstrand, C., Bury, N., Barron, L., Snape, J., Owen, S. 20 Nov 2018, In: Environmental Science and Technology

PGR Supervision

Blake Kesic Start: 01/10/2019

Further Information

Enquiries are welcome about self-funded PhD projects on the above research themes. In particular, calls are currently open for the following projects:

  1. Development of next-generation analytical and data treatment approaches for enhancing possibilities in forensic profiling of chemical residues (Ref: SF20/APP/GALLIDABINO);
  2. Developing new, high-throughput and comprehensive, headspace approaches for the forensic analysis of ignitable liquids (Ref: SF20/APP/GALLIDABINO2).

Please, click on the links above to apply or visit FindAPhD.com.


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