Farnood Gholami
About Farnood Gholami
Farnood Gholami is an Engineering Manager with extensive experience in integrating AI and machine learning into software solutions. He holds a PhD in Mechanical Engineering from McGill University and has over a decade of experience in various engineering roles, currently working at sherpa° in Montreal.
Current Role at sherpa°
Farnood Gholami serves as an Engineering Manager at sherpa° since 2022. In this role, he focuses on developing cloud-based web applications that automate travel document issuance using AI solutions. His expertise in integrating AI and machine learning into software solutions enhances the company's capabilities in the travel technology sector. Gholami's leadership in engineering projects contributes to the advancement of innovative solutions at sherpa°.
Education and Expertise
Farnood Gholami holds a Bachelor of Science (B.Sc.) in Aerospace, Aeronautical and Astronautical/Space Engineering from Amirkabir University of Technology - Tehran Polytechnic, completed from 2003 to 2008. He further pursued a Doctor of Philosophy (PhD) in Mechanical Engineering at McGill University, graduating in 2016, and obtained a Master of Engineering (M.Eng.) from the same institution from 2008 to 2010. Additionally, he earned a certificate in Basic Business Skills for Non-Business Graduate Students from McGill University in 2013.
Professional Background
Gholami has over a decade of experience in engineering roles across various organizations. He worked at CM Labs Simulations as Engineering Manager from 2017 to 2022 and previously held positions as Simulation Specialist and Mechanical Engineer/Simulation Specialist at the same company. His experience also includes serving as an Application Engineer at Maplesoft for 11 months in 2017 and as a Research Assistant at the University of Tehran from 2006 to 2007. He was a Postdoctoral Fellow at McGill University from 2008 to 2017.
Technical Skills and Specializations
Farnood Gholami specializes in data engineering and statistical analyses, focusing on cloud connectivity and IoT. He possesses a strong background in digital twins and transformation, contributing to advanced robotics and automated systems. His comprehensive understanding of modeling and control, along with design and optimization, supports his work on engineering projects that integrate AI and machine learning.