Cross-sectoral innovation powered by A.I.
Speakers @Datrix
- Matteo Bregonzio, CTO
- Giulia De Poli, Senior Data Scientist
Abstract
Today Datrix is helping public and private companies in finding and accelerating innovation paths within the digital sphere.
In fact, thanks to A.I. it becomes possible to gather and analyse large volumes of data in order to better understand processes and extract insights on how to improve the services. As an example, Datrix is currently working on multiple healthcare and cybersecurity projects where A.I. is adopted to overcome limitations and speed-up processing; in both cases the ability of processing and extracting information from Big Data represent a game changer in supporting professionals in taking the right decision in a timely fashion.
Specifically, in the healthcare/oncology sector we are researching and developing a medical imaging platform capable of collecting, processing and analysing hyperspectral data collected by coherent Raman microscopies. Those next-generation bio-photonics devices are based on vibrational spectroscopy, with the potential to revolutionise the study of the cellular origin of diseases allowing for novel approaches towards personalised therapy. Deep learning ralgorithms are developed to address multiple challenges, from spectral denoise and removal of spectral signatures from the data acquisition equipment to cellular classification and disease detection. For further information on the Cloud-based platform: https://ramapp.3rdplace.com.
Within the cybersecurity space Datrix is working at AIA Guard, the very first European solution for assessing Adversarial Machine Learning vulnerabilities. Artificial intelligence can be both a blessing and a curse for cybersecurity; in fact adding A.I. modules to business products implicitly also means introducing new potential vulnerabilities that can cause data stealing, model drift, and performance degradation. In this context, statistical learning and deep learning are used to analyse both the A.I. algorithm and datasets used for training in order to identify vulnerabilities. This is achieved via a multi-step analysis that includes data privacy & sanitization at dataset level, static program analysis, penetration testing and data poisoning.
Importantly, this hybrid infrastructure is designed to be GDPR compliant and capable of monitoring, detecting and mitigating AI models vulnerabilities.
Keywords: A.I., machine learning, Big Data, cybersecurity, healthcare
Program
13:30 - Welcome by prof. Bruno Crispo, Department of Information Engineering and Computer Science
13:35 - Company presentation
13:40 - Case study presented by Datrix
14:10 - Skills for the future
14:15 - Q&A session
About the company
Datrix is a tech Group of Augmented Analytics & Machine Learning listed on Euronext Growth Milan. They develop sustainable AI-based solutions to grow companies, applying AI in their business to add value and measurability.
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