Inmar Givoni

For the time being, I am still involved in a variety of professional activities such as mentoring new ventures, supporting women in tech, sitting on advisory boards, AI consulting, and organizing events for the tech community.

I also still give presentations about machine learning, algorithms, big data, and their applications to high-school kids, university students, researchers, and non-technical audiences.  I also participate in various career panels and career mentoring events.

I’m particularly interested in outreach activities for young women, encouraging them to choose technical career paths. For my volunteering and mentoring work I received the University of Toronto’s 2017 Arbor Award, and was recognized as one of the 2018 inaugural cohort of 50 inspiring Canadian women in STEM. I was recognized as one of Canada’s Tech Titans: Top 19 of 2019, featured as one of Women in AI to Watch on Forbes in 2020, and am featured on the 2021 “See It Be It Stem It” calendar.

I like helping build communities, especially in Toronto. I am a co-organizer of the ML Ensemble and Canadian Tech@Scale conferences and am a long-standing contributor to CanCwic –the Canadian Celebration of Women in Computing, and WiML–Women in Machine Learning.

Previously, I was a director of engineering at Uber ATG Toronto. I built and led a team of research engineers working on bringing from research and into production cutting-edge deep-learning models for self-driving vehicles.

Before Uber, I oversaw all machine learning and software development efforts at Kindred, an AI & Robotics startup focusing on autonomous grasping for warehouse automation.

Prior to that, I was at Kobo‘s Big Data team, which I joined as a senior research scientist working on content analysis and website optimization, and was later the VP of Big Data, leading the team in the development and productization of algorithms for recommendations, search optimization, data science and analytics, content analysis and website optimization.

Before that, I was a member of technical staff at Altera (now Intel). I worked on optimization algorithms for FPGA packing and placement problems, as well as logic utilization estimation and reporting.

I obtained my Ph.D. in computer science at the University of Toronto, specializing in Machine Learning. I worked under the supervision of Professor Brendan Frey at the PSI lab. During my studies, I collaborated with the Boone Lab at the University of Toronto. I spent a term as a visitor of the CBL lab at the University of Cambridge, and interned with Microsoft Research. My first internship was with Search Labs where I worked on e-commerce search. My second internship was with the Machine Learning and Perception lab at MSR Cambridge, working on project Kinect.

I received my undergraduate degree in Computer Science and Computational Biology from the Hebrew University in Jerusalem. Back then I thought I’ll be a neuroscientist when I grew up, and during my studies, I spent a summer at the Weizmann Institute studying the rat’s visual cortex at Ilan Lampl’s lab, and studied octopuses (octopii?) motor control with Benny Hochner’s group . To this day, I remain a staunch octopus lover (not as food).