Joaquín B. González

As Senior Innovation Engineer at LEM International , I drove the company's future vision by leading R&D strategy and innovation from ideation to Proof of Concept (PoC). A key strategic duty was conducting comprehensive 3-, 5-, and 10-year R&D horizon analyses, aligning priorities with emerging IoT, AI, and sensor trends. I acted as the crucial board-to-developers liaison , advising Global Product Management (GPM) on technical feasibility, market alignment, and technology investments. I successfully implemented hybrid Agile (sprints) and Waterfall methodologies for prototyping and the Software Development Life Cycle (SDLC).

On the technical front, I specialized in high-complexity embedded systems and full-stack integration. I served as a DevOps Engineer, automating workflows for IoT edge devices and streamlining processes via AWS cloud integration and cost-performance optimization. My expertise included developing IoT firmware for EV charging and smart grids using microcontrollers like ESP32 (FreeRTOS/ESP-IDF) and ST MP1. A significant technical achievement was pushing controller limits to realize high-precision sub-millisecond clock synchronization (35µS) over Wi-Fi hotspots. Furthermore, I designed automated testing frameworks in Python and C# and prototyped self-supplied sensor systems using BeagleBone Black and STM32/ESP32 , focusing on energy harvesting and low-power design. This combination of strategic leadership and deep technical expertise ensured the delivery of market-ready innovation

As the AI / Solution Engineering Manager at Cogito Instruments SA, I was critical in pivoting the company’s technology stack from closed proprietary hardware to an open, scalable ecosystem built on FPGA and embedded systems. Reporting directly to the CEO and COO, I led the end-to-end development and industrialization of Artificial Intelligence solutions, guiding the company through a challenging transitional period where resources were scarce. My strategic leadership involved translating complex technical capabilities into actionable business assets during crucial negotiations with major partners like Clemessy-Eiffage, ST Microelectronics, and Georg Fischer Machining solutions, where my accurate prediction of time and resources was a decisive asset.

On the technical execution side, I led the architecture design and defined the full requirements set for the next-generation system in a record time. This platform supported the development and commercialization of the DCblue machine vision product, which was successfully integrated and commercialized by SunRock Technologies. My work encompassed the full stack, from low-level FPGA/embedded firmware design (including the Core1 prototype for neural network acceleration ) to the deployment of industrial AI algorithms. I specialized in taking initial concepts and rapidly prototyping comprehensive, complex systems, demonstrating the capability to design large and intricate machines. My success was rooted in my ability to swiftly adapt my skills (including C/C++ and VHDL) to new hardware architectures, ensuring project continuity and earning customer commendation

During my tenure at CERN (2015–2018), I served as a key engineer and technical expert for the Solid State Detector (SSD) team, deeply involved in the CMS High Granularity Calorimeter (HGCAL) upgrade project. My role was focused on delivering high-reliability, high-throughput solutions for detector characterization and data acquisition (DAQ) in mission-critical physics environments.

On the technical front, I pioneered and managed complex high-level laboratory measurement equipment for radiation damage studies. I developed comprehensive LabVIEW-based control and DAQ software for the Charge Collection Efficiency (CCE) and Transient Current Technique (TCT) systems , which involved the parallel control of multiple instruments and high-speed data acquisition from oscilloscopes. A major achievement involved redesigning the DAQ software to accelerate measurement times by 8x and implementing effective Electromagnetic Interference (EMI) mitigation strategies, which successfully improved the Signal-to-Noise Ratio (SNR) by 23 dB.

Furthermore, I architected and implemented a robust 50 TB/week data storage pipeline to handle the immense data flow from beam tests, achieving a crucial milestone of zero downtime despite constant changes in experimental requirements. My hardware expertise included designing specialized PCBs to facilitate parallel testing and thermal management of SiPM sensors within climate chambers. Beyond core project work, I managed all computing infrastructure for the SSD team, acting as the primary technical point-of-contact for all electronics and computing queries. I leveraged this technical depth to support the next generation of engineers by supervising students during the ESIPAP and CERN summer schools.