Tech Talk 30 - January 23rd 2020

Guest Speakers and subjects:

Elimar Macena - Federal Institute of Espírito Santo (IFES) - Campus Serra, Brazil - Watch Recording
Studying Crime Patterns in São Paulo state between 2006 and 2016

Intelligence led policing (ILP) refers to technology-driven crime data analysis activities to support the design of effective crime prevention and prosecution strategies. This is a new approach to fighting crime that has been gaining strength due to the convergence of two technological streams: the digitization and release of public information related to the occurrence of crimes and the development of technological platforms that allow the proper handling of such information, such as the HPCC Systems platform. Elimar's project used the HPCC platform to analyze crime patterns in the state of São Paulo in Brazil between the years of 2006 and 2016.
Elimar is a student at the Federal Institute of Espirito Santo located at Campus Serra, Brazil and is finishing a Bachelor of Science degree in Information Systems, with the final project based on granite image classification using Python. He currently works as an intern for our LexisNexis Risk Solutions Group Sao Paulo office within the ETL group. His prior work experience include web development, using ASP.NET MVC on the C# Framework.
Muiredach O'Riain - Goldsmiths, University of London - Watch Recording
Machine Learning and the Forensic Applications of Audio Classification: An exploration of the forensic applications of sound classification using Artificial Neural Nets

The goal of Muiredach's intern project is to use HPCC Systems to help build a reliable classification model that is able to accurately classify an input sound file to its location. His project intends to not only demonstrate a proof of concept for this technology, but also to lay the groundwork for what could be the next step in forensic audio analysis and a new means of gathering information through sound. This project is another piece of research that allows him to combine his knowledge of computing with his love and understanding of music, to produce some interesting insights.

Muiredach holds a Bachelor of Science degree in Music with Computing from Goldsmith's, University of London. During his degree, he designed a smart sampler instrument to use sound recognition and data mining techniques along with AI, to match an input sound to the closest corresponding sound from a bank of samples in real time. This meant he could take, for example, a beat boxer and match each 'hit' to the corresponding sound from the sample bank, converting the human voice into an electronic drum machine. Muiredach has also designed a C++ and DSP music application to combine physical modeling synthesis with an intuitive, interactive visual interface to create interesting soundscapes.