Bio & CV

As of 2021 I am focusing on writing fiction (!!)

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.  You are welcome to contact me if you are interested in something like that.

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).

Contact Info:

You can e-mail me.
You can also find me on Linkedin and here is my Google Scholar page.
I have a Twitter handle that I don’t use it.

Some of My Youtube Presentations:

Deep Learning for Self Driving Cars

AI for the Rest of Us

AI in Canada

More can be found here

For my official bio & headshot please use the below:

Inmar Givoni writes fiction.

She is also a start-up mentor, AI consultant, advisory board member, and a public speaker on AI, tech leadership and other topics. She volunteers her time mentoring women in tech and AI in Toronto and elsewhere. 

Before turning to writing, she was a Director of Engineering at Uber Advanced Technology Group, Toronto, where she led a team who brought from research and into production cutting-edge deep-learning models for self-driving vehicles. She received her PhD (Computer Science) in 2011 from the University of Toronto, specializing in machine learning, and was a visiting scholar at the University of Cambridge. She worked at Microsoft Research, Altera (now Intel), Kobo, and Kindred at roles ranging from research scientist to VP, Big Data, applying machine learning techniques to various problem domains and taking concepts from research to production systems. She is an inventor of several patents and has authored numerous top-tier academic publications in the areas of machine learning, computer vision, and computational biology. She is a regular speaker at AI events, and is particularly interested in outreach activities for young women, encouraging them to choose technical career paths. For her volunteering efforts, she has received the Arbor Award from UofT. She has been recognized as one of Canada’s 50 inspiring women in STEM (2018), one of Canada’s Tech Titans: Top 19 of 2019, and one of Forbes Magazine’s Women in AI to watch (2020). She was featured in Marie Claire, Toronto Life, The Globe and MailTWIML & AI podcast, ReWork’s list of 30 influential women in Canadian AI, UofT’s News, and other media venues, as well as the 2021 “See It Be It Stem It” calendar.