The first lecture was given by Jibran Jahshan, Vice President, Software Engineering at NVIDIA on the topic of Deep Learning for Autonomous Driving and work being done at NVIDIA in this area, as part of the ‘Computer Vision and Deep Learning’ course that is offered at LAU School of Engineering by Dr. Lina Karam. The talk concentrated on a brief recent history of how application of AI has become so pervasive and touched on some key challenges NVIDIA is solving to bring DL based solutions for Autonomous Vehicles to market. 

On February 22, 2021, Gregory Akiki, Senior Director of Quality at GLOBALFOUNDRIES, will be giving a lecture on AI applications within Semiconductor manufacturing. His lecture will also cover the business imperatives driving AI and key areas of AI implementation and Challenges. Akiki has over 35 years of semiconductor and is currently working with teams to accelerate the implantation of AI-based applications within the manufacturing environment.  

On Monday April 12, 2021, Dr. Roland Menassa gave a one-hour webinar on the future technology trends, challenges and opportunities in the Automotive, Aerospace and e-Commerce industries, focusing on the rise of automation and the use of artificial intelligence, machine learning and data analytics across industry sectors. The webinar was attended by over 60 students from the Seminar course on Contemporary Issues in Industrial and Mechanical Engineering at the Lebanese American University (LAU) in Byblos, Lebanon. Dr. Menassa answered questions from the students on the tradeoffs of automation in terms of efficiency improvements versus future job prospects and environmental concerns. He offered students career advice about developing the right engineering skills and soft skills early on to be ready for the changing job market.

On Thursday April 29, Charlie Matar, VP at Synopsys Inc, gave a seminar to LAU students on manufacturing & AI in semiconductors industries with an introduction on 5G and cloud computing. His seminar went over AI hardware trends and big data and IoT/sensors and AI Hardware trends (architecture, process technology & packaging). Matar manages the system design solution team responsible for silicon development, leveraging Synopsys technologies across all chip development phases. He also manages Synopsys Machine Learning R&D team focused on using AI in design implementation, power, DTCO and architectural definition. Charlie has over 30 years of experience in product, chip design and technology.