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Welcome to my personal webpage!
Hello! I am Gian Maria Campedelli, Research Scientist in the MobS Lab at Fondazione Bruno Kessler, in Italy.
Interested in crime and computational sciences? You might be in the right place then.
In February 2020, I obtained a Ph.D. in Criminology at Università Cattolica del Sacro Cuore (Milan).
From 2020 to 2023, I was a Postdoctoral Research Fellow in Computational Sociology at the University of Trento, funded by the Department of Excellence initiative of the Italian Ministry of University and Research.
I am also a former researcher at Transcrime and former visiting research scholar at Carnegie Mellon University (Institute for Software Research - Center for Computational Analysis of Social and Organizational Systems), under the supervision of Prof. Kathleen M. Carley.
Any curiosity? Write at:
gcampedelli AT fbk.eu
You can find my works/projects also on Google Scholar (https://scholar.google.com/citations?user=7n4yK_0AAAAJ&hl=it) and ResearchGate (https://www.researchgate.net/profile/Gian_Maria_Campedelli)
NEWS & HIGHLIGHTS:
August 2024: WONDERFUL NEWS! I am honored to share that I won the 2024 Early Career Award from the European Society of Criminology! 🎉 Read the jury motivations here.
August 2024: New working paper out with Gianmarco Daniele and Marco Le Moglie. Can we use machine learning to predict mafia infiltration in local politics? "Mafia, Politics and Machine Predictions" has the answer: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4912204.
March 2024: My solo paper "Homicides involving Black victims are less likely to be cleared in the United States" is finally out in Criminology! Read it here: https://onlinelibrary.wiley.com/doi/abs/10.1111/1745-9125.12362 . (Chek out also what The Guardian says about it!).
November 2023: The article "Organized Crime, Violence and Support for the State", co-authored with Gianmarco Daniele, Andy Martinangeli and Paolo Pinotti has been published in the Journal of Public Economics (See: https://www.sciencedirect.com/science/article/abs/pii/S0047272723002116 )
September 2023: Exciting news! The article "Reducing cartel recruitment is the only way to lower violence in Mexico", a joint work with Rafael Prieto-Curiel and Alejandro Hope, is now out in Science! Here's the open access article: https://www.science.org/doi/10.1126/science.adh2888
June 2023: The article "Evidence on the impact of the Prudential Center on crime in downtown Newark", co-authored with Eric Piza (Northeastern), Alex Piquero (U Miami) and Justin Kurland has been published in the Journal of Experimental Criminology. Read the paper here (open access): https://link.springer.com/article/10.1007/s11292-023-09576-8
May 2023: The article "Crime, inequality and public health: a survey of emerging trends in urban data science" co-authored with colleagues at the University of Trento and Fondazione Bruno Kessler has been published in Frontiers in Big Data. Here's the open access link: https://www.frontiersin.org/articles/10.3389/fdata.2023.1124526/full
December 2022: I have been invited to contribute to the next Routledge Handbook of Homicide Studies with a chapter on homicide and criminal careers! More news to come!
June 2022: BIG NEWS! My first book is now out and available! Purchase your copy of "Machine learning for criminology and crime research: at the Crossroads" here: https://www.routledge.com/Machine-Learning-for-Criminology-and-Crime-Research-At-the-Crossroads/Campedelli/p/book/9781032109190!
April 2022: "The geometrical shapes of violence: predicting and explaining terrorist operations through graph embeddings" has been published in the Journal of Complex Networks! Co-authored with colleagues at Boise State University. Link here: https://academic.oup.com/comnet/article-abstract/10/2/cnac008/6564024
March 2022: My new solo paper "Explainable machine learning for predicting homicide clearance in the United States" is now out in the Journal of Criminal Justice! Read it here: https://www.sciencedirect.com/science/article/abs/pii/S0047235222000186 (or get access to the pre-print version at https://arxiv.org/pdf/2203.04768.pdf)