Ragavan has over 5 years of experience designing and deploying deep learning for enterprises from diverse industry sectors, ranging from agriculture to finance. Passionate about taking Canada’s AI industry to the next level, Ragavan designs and builds deep learning solutions that drive business value for enterprises around the world. Ragavan led DeepLearni.ng’s recent development of the world’s first deep learning system for retail banking at Scotiabank, which has already saved the bank millions of dollars. Ragavan learned the ropes of entrepreneurship at Canada’s prestigious NEXT 36 program, where he was mentored by some of the world’s leading business experts. He also studied Computer Engineering at York University’s Lassonde School of Engineering, where he graduated at the top of his class.
Adam El-Masri, Co-Simulation & Experimentation Lead for aUToronto, is a software engineer with a wide variety of experience working at various projects and companies. He is also currently a teaching assistant at University of Toronto, and a founder of a non-for-profit organization in social innovation. Adam is inspired by the potential of his work to make the world a better place, particularly his work with self-driving cars.
Zachary Kroeze is a Postdoctoral fellow at the University of Toronto Institute for Aerospace Studies and a newly joined member of the aUToronto team. His education background is in Electrical Engineering, specifically in control systems.
Jacob is a first-year student at University of Toronto studying Computer Science. He currently joined aUToronto Autonomy team. His career passion is to join the autonomous driving industry.
Hardware & Software training for #aUToronto team hosted by Intel Autonomous Driving group in Phoenix, Arizona. #GoTeamaUToronto
Keenan Burnett is the Technical Team Lead for aUToronto. He is also a Master of Applied Science at the University of Toronto Institute for Aerospace Studies under the supervision of Professors Angela Schoellig and Tim Barfoot. His research interests are in control systems design, computer vision, and self-driving cars.
Q: What is your motivation to be the Technical Team Lead of aUToronto?
aUToronto is hosting an information session for leaders to introduce their team responsibilities and talk with the students. If you are interested in finding out the what we are doing now and how to potentially get involved, come join us on Sep 22nd!
Date: September 22nd
Start Time: 6 p.m.
Location: SF 1105
Register through Facebook Event page at https://goo.gl/GteTYu
The Autonomy team is preparing for data collection next week. They will collect data that can be used for both sensor calibration and testing autonomy algorithms. Furthermore, they are also making progress on various topics such as object tracking, lane detection and path tracking control.
The Software team is currently working on interfacing with hardware systems including bumblebee, velodyne and CAN, with the help from the Autonomy team.
The Hardware team has been working towards refining the power and communication interface & strategy for Zeus, as well as sourcing off-the-shelf components. They are also in the process of reviewing the current version of the electrical hardware design with engineers from GM.
The System team is finalizing the JIRA task tracking system and loading in the first set of tasks. They have decided to follow an Agile methodology with two-week long sprint cycles. Each sprint cycle will result in a demonstrable capability on the vehicle!
We are now accepting applications for General Members! Click below for instructions on how to apply. Applications will close on July 25th.