Lorenzo Mandelli
Junior Sales Engineer
ficonTEC
My journey in the tech world started in 2014 when I joined the European Sci-Tech Challenge sponsored by ExxonMobil in Rome. After winning the first challenge I have been given the chance to participate in the final phase at the McLaren Technology Center in London.
The year after, I joined the Beam Line for School competition, sponsored by CERN and INFN.
Right after awarding my high school diploma in 2016 I won a scholarship offered by OFFICINE TERENZIO which payed my university studies in Sapienza, University of Rome.
My university career started in 2016 with a bachelor of engineering in automation and computer science and ended in 2022 with a MsC in Artificial Intelligence and Robotics. During the last months of my university career I have taken a step toward the research and development world, joining research projects sponsored by Sapienza, majorly dealing with Neuroscience, Neuroimaging, Robotics and AI.
Since November 2021 I have been living in Bremen, Germany. Here I have produced my MsC thesis together with ficonTEC.
On November 2022 I joined the 38th PhD programme in Engineering in Computer Science, held by Sapienza, university of Rome, winning a scholarship sponsored by ficonTEC. I live and work at my PhD in Bremen, now developing data driven solutions for PICs manufacturing systems' performance optimization. I now principally deal with real data acquisition processes and subsequently, the modeling by means of Machine Learning and Deep Learning, which goal is to make complex production scenarios, smarter.
Presentations
How Photonic Intelligent Manufacturing Enables Artificial Intelligence at Scale
The continuously growing demand for automated assembly, testing, and packaging of Photonic Integrated Circuits (PICs) is increasingly driven by the need for high-volume manufacturing, placing new constraints on throughput, cost efficiency, and time-to-market. The intrinsic complexity of photonic production processes—combined with short product life cycles and the need for rapid ramp-up to high volume—requires smarter, more adaptive manufacturing solutions to ensure high yield and low cycle time. Traditional process optimization approaches are reaching their limits. Data-driven and AI-enabled optimization of production opens new opportunities to improve PIC assembly and testing beyond conventional technology constraints. By leveraging intelligent manufacturing frameworks—integrating automation, real-time data analytics, and closed-loop process control—photonic production can scale with the reliability, speed, and efficiency required to support next-generation AI, cloud computing, and high-performance computing infrastructures. In this context, photonic intelligent manufacturing emerges as a critical enabler for the deployment of Artificial Intelligence at scale, bridging the gap between advanced photonic technologies and the industrial capacity required to monetize AI.