Bio

As of September 2016, I am the Director of Machine Learning at Kindred, an AI+Robotics startup with offices in Toronto, San Francisco, and Vancouver. I spend most of my time in Toronto.

Prior to that, I was at Kobo‘s big data team, which I joined in 2013 as a senior research scientist working on content analysis and website optimization. In 2014 I became 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 among other things.

Before that, I was a member of technical staff at Altera. 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 neuro-scientist 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).

 

For my official bio & headshot please use the below:

Inmar Givoni is the Director of Machine Learning at Kindred, where her team develops algorithms for machine intelligence, at the intersection of robotics and AI. Prior to that, she was the VP of Big Data at Kobo, where she led her team in applying machine learning and big data techniques to drive e-commerce, customer satisfaction, CRM, and personalization in the e-pubs and e-readers business. She first joined Kobo in 2013 as a senior research scientist working on content analysis, website optimization, and reading modelling among other things. Prior to that, Inmar was a member of technical staff at Altera where she worked on optimization algorithms for cutting-edge programmable logic devices.

Inmar 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. During her graduate studies, she worked at Microsoft Research, applying machine learning approaches for e-commerce optimization for Bing, and for pose-estimation in the Kinect gaming system. She holds a BSc in computer science and computational biology from the Hebrew University in Jerusalem. 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 big data, analytics, and machine learning events, and is particularly interested in outreach activities for young women, encouraging them to choose technical career paths.