I manage LogRhythm’s user and entity behavior analytics (UEBA) solution. I work directly with the software developers and machine learning (ML) engineers and other cross-functional teams at LogRhythm. Tracking user behavior and applying advanced analytics, such as ML, to detect anomalies is key for customers who want to be able to detect potential threats that otherwise could stay undetected.
I worked as a development engineer in the beginning of my career, mostly in automotive, dealing with brake noise. I then moved to manage global automotive projects, including a new plant launch. Through my passion for data and signal analysis, I embraced the artificial intelligence field and decided to be involved in a job where I could feel that I was more directly helping people, which brought me into the cybersecurity world.
The challenges involved in applying machine learning in cybersecurity and the constant changing threat landscape fascinate me.
I embrace a mix of technical and business skills and I am passionate about creating product applications using data science and machine learning to help our customers have a better defense coverage. I aim to achieve the highest possible added value to the customer while keeping the other balancing constrains in mind.
M.S and B.S in mechanical engineering, Universidade de Sao Paulo.