My name is Simone Raponi, I am a dedicated Senior AI/ML Cybersecurity Engineer at Equixly.
You may be wandering what an AI/ML Cybersecurity Engineer is, well.. I am a Machine Learning Scientist/Engineer with a strong background in Cybersecurity. I have always been working in the intersection between Artificial Intelligence and Cybersecurity.
My academic achievements trace back to Sapienza, University of Rome, Italy, where I obtained both my Bachelor's and Master's Degrees with honors in Computer Science, My Bachelor's Thesis, guided by Prof. Francesco Parisi Presicce, introduced a theoretical model for the Attribute-Based Access Control paradigm. My Master's thesis, under the expert supervision of Dr. Julinda Stefa, delved deep into AI techniques to unveil adversaries lurking in the Dark Web, resulting in two noteworthy publications in top-tier venues.
I pursued a Ph.D. in Computer Science and Engineering, mentored by Prof. Roberto Di Pietro and co-mentored by Dr. Gabriele Oligeri, I was honored with the Best Ph.D. in Computer Science and Engineering Award, and the Computer Science and Engineering Outstanding Performance Award.
My research allowed me to harness Artificial Intelligence potential to tackle ambitious Cybersecurity challenges. This dedicated effort resulted in 1 book, 11 journal papers, 11 conference papers, and 2 notable patents.
After my Ph.D., I worked as a Machine Learning Scientist at the esteemed NATO Center for Maritime Research and Experimentation.
I am currently leading the Artificial Intelligence division of Equixly, an AI-Powered Hacker that is currently reshaping the security testing landscape.
I was an intern Machine Learning Scientist in the Iberdrola's Smart Grid Lab, where I developed and implemented a synchronous distributed data acquisition algorithm for Power Line Communication devices located in geographically distant points. The acquired data allowed the creation of a rich database to research on the communication delay of Power Line Communication devices adopted worldwide with the goal of making AI-based inferences.
Machine Learning Scientist in the Smart Grid Lab. Development and Implementation of an Artificial Intelligence-driven noise forecasting model (RNN-LSTM) for Power Line Communication devices.
Machine Learning and Big Data Scientist. Analysis and Experimentation of the impact of Artificial Intelligence on the privacy of users interacting with Internet services.