Fernando Franco

Fernando Franco

Senior Software Engineer

Ph.D. SW Engineer with a solid professional background in the overall SW life-cycle: requirements gathering, design, implementation, testing, integration and maintenance. Good knowledge of real-time, embedded and safety-critical systems and significant research experience in computer vision and image processing. Passionate about developing algorithms and experimenting with new technologies. Highly organized with strong capacity to prioritize workload, reach the goals and complete the projects within deadlines.

Hofwiesenstrasse 153, 8057, Zurich,
Fernando Franco



Senior Software Engineer at Varian Medical Systems, Baden, Switzerland

Varian Medical Systems is the world’s leading manufacturer of medical devices and software for treating and managing cancer. Ethos is a comprehensive, revolutionary new therapy system that is patient-centric and personalized from initial planning to on-couch adaptation and treatment monitoring.


  • Algorithms for image processing and analysis
  • Cloud Computing
  • Development of software components using dotnet

Senior Software Developer at ABB, Turgi, Switzerland

ABB is a leading global technology company with a portfolio including electrification, robotics, automation and motion. The AC 800PEC is an efficient and flexible controller family used in industry and traction applications. It enables high-performance applications with extremely fast control algorithms (cycle times up to 100 microseconds).


  • Scrum master of a 5 people team in a SAFe agile setup.
  • Design, development, implementation and testing of software components for the AC 800PEC embedded platform: communication protocols, downloadable kernel modules, device drivers, interfaces with Simulink blocks.
  • Resolution of Customer Cases: rewarded for the record of bugs found and solved in 2019.
  • Handling of configuration management, build processes and test environments.

Software Engineer TCMS at Bombardier Transportation AG, Zürich, Switzerland

Bombardier is a global leader in the transportation industry. The Transportation division covers a full spectrum of rail solutions including trains, sub-systems, signalling systems, e-mobility technology and data-driven maintenance services.


  • Development of the next generation SW solution for the driver display according to the ETCS standard.
  • Design, development and testing of visualization software for TRAXX South Africa locomotives. The SW received the full customer acceptance has been succesfully commissioned.
  • Concept preparation, requirements formulation and implementation of diagnostic software for TRAXX MS locomotives. The assessment chas been completed within the deadline.
  • Execution of module and system test in the laboratory and on the locomotives.

Software Engineer Embedded at General Electric Transportation, Florence, Italy

GE Transportation is one of the largest producer of diesel-electric locomotives and related products, such as railroad signaling equipment. GE Tempo is a generic real-time and safety critical platform used for train control and signaling applications.


  • Design, development and testings of software components for the GE Tempo embedded platform: multiplatform microkernel and memory-management system; device drivers and communication protocols; bootloaders for remote upgrade of firmware.
  • Design, implementation and testing of software for an high-precision odometer system equipped with different sensors (wheel speed, radar motion, balise transmission module)


Doctor of Philosophy (Ph.D.) in Computer Science, multimedia systems and telecommunication from University of Florence, Italy with GPA of


  • Computer Vision and Image Processing
  • Machine learning and Pattern Recognition

Master degree (M.Sc.) in Computer Science, multimedia systems and telecommunication from University of Florence, Italy with GPA of 110/110 cum laude


Bug Slayer Prize from ABB

Record of bugs found and solved in 2019.


Local pose estimation from a single keypoint. by Third Workshop on Non-Rigid Shape Analysis and Deformable Image Alignment (NORDIA, CVPR)

This paper presents a novel learning-based approach to estimate local homography of points belong to a given sur- face and shows that it is more accurate than specific affine region detection methods.


Fluency: Native speaker
Fluency: Full professional proficiency
Fluency: Limited working proficiency


Level: Master
  • C++
  • C
  • C#
  • Python
Embedded Systems
Level: Master
  • Operating Systems
  • Device drivers
  • Memory management
Computer Vision
Level: Intermediate
  • 3D pose estimation
  • Object Recognition
  • Features Detection
  • Image Processing and Analysis


  • Football
  • Running
  • Skiing
  • Family
  • AS Roma
  • Nintendo Switch
  • The Legend of Zelda
  • Super Mario Bros

© 2021 Franco Fernando. All rights reserved.