Connor Ricotta graduated from the automation systems engineering technology (B.Tech) program at McMaster University in December 2022. He began his M.A.Sc. in January 2023 under the supervision of Dr. Ali Emadi and transitioned into the Ph.D. program in electrical and computer engineering in September of the same year. His research focuses on control architectures for electrified autonomous vehicles, with emphasis on energy-efficient system integration, V2X-enabled decision-making, and advanced driver assistance systems (ADAS).
Full Profile:
Connor Ricotta’s passion for engineering grew from early hobbies like woodworking and experimenting with computers and electronics. This curiosity led him to McMaster University’s automation systems engineering technology (B.Tech) program. There, he strengthened his technical skills through hands-on labs and team-based projects. In his fourth year, he joined the EcoCAR Challenge as an electrical member of the System Design and Integration team, where he gained experience integrating hardware and software in a real vehicle platform. After starting graduate studies, he joined the Connected and Automated Vehicles team and later became team lead, a role he still holds.
During his undergraduate studies, Connor completed several co-op placements. At Zeton, he worked as a junior controls specialist on PLC controls and HMI systems for chemical process plants. He also served as a research assistant with the CERC@MARC team, helping develop a programmable shifting robot for chassis dynamometer testing. His EcoCAR work included building custom automotive wire harnesses, developing and manufacturing PCBs, and implementing ADAS features such as adaptive cruise control, lane centering, and intersection navigation. He integrated these systems into a stock vehicle architecture, gaining experience across both hardware and software domains.
Connor began his M.A.Sc. in electrical and computer engineering in January 2023 under the supervision of Dr. Ali Emadi. He transferred into the Ph.D. program in September 2023. His research focuses on control architectures for electrified autonomous vehicles, with emphasis on energy-efficient system integration, V2X-enabled supervisory decision-making, and advanced driver assistance systems (ADAS).
