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SUMMARY:Python Project-based Workshop: How to build your own intelligent agent
DESCRIPTION:On Friday\, November 13\, 2020 at 10:00 a.m.\, Enas Tarawneh will present “Python Project-based Workhsop: How to build your own intelligent agent”. \nDay & Time: Friday\, November 13\, 2020\n10:00 a.m. – 12:00 p.m. \nSpeaker: Enas Tarawneh \nOrganizers: IEEE Toronto WIE\, IM/RA\, York University WiCSE \nLocation: Virtual \nContact: Ayda Naserialiabadi \nAbstract: The workshop will focus on creating an intelligent agent that can listen to questions given through natural language and generate natural language responses. The workshop will also dabble into customizing the voice used in these responses. This workshop includes: \na) Programming speech recognition. \nb) Leveraging cloud-based resources such as speech-to-text\, text-to-speech and AI querying to generate responses. \nc) Connect these together to create a turn taking intelligent agent. \nd) Customizing the voice used in these generated responses. \nRegister: Please click here to register. \nBiography: Enas Tarawneh is a PhD student at York University in the department of Computer Science and Electrical Engineering. She works in the Vision\, Graphics and Robotics (VGR) Laboratory as a research assistant. Her most recent research involves the development and evaluation of a cloud-based avatar (intelligent agent) for human-robot interaction that is part of a project funded by VISTA. She holds an OGS and VISTA doctoral scholarship. Prior to this\, Enas worked as an academic Lead\, instructor\, and e-learning coordinator in the Institute of Applied Technology in UAE in which she received an award for “Distinguished Curriculum Support” and another for “Excellence in E-learning coordination”. Most importantly\, Enas is a wife and mother of three\, that believes that open-mindedness and positivism is the best accomplishment and the source of true happiness.
URL:https://www.ieeetoronto.ca/event/python-project-based-workshop-how-to-build-your-own-intelligent-agent/
CATEGORIES:Instrumentation & Measurement,Women in Engineering
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DTSTART;TZID=America/Toronto:20201113T180000
DTEND;TZID=America/Toronto:20201113T200000
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LAST-MODIFIED:20210615T010123Z
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SUMMARY:IEEE Toronto Virtual AGM 2020
DESCRIPTION:The IEEE Toronto Section is happy to announce our first ever online IEEE Toronto section Annual General Meeting (AGM).  Since we are not restricted to a limited number of physical participants\, we are happy to open this even up to all IEEE Toronto members\, as well as any guests who they would like to invite.  Please feel free to pass this information along to any interested parties. \nWe will hear from the IEEE Toronto section\, IEEE Canada\, and IEEE Global representatives\, as well as keynote speakers from local industry.  Awards will be presented to oustanding contributors for the past year\, and prizes will be available for all attendees.  You must register for the event using the link on this page in order to qualify for prizes.  Only IEEE members will be eligible for prizes. \nDate: Friday\, November 13\, 2020\n6:00 p.m. – 8:00 p.m. \nLocation: Virtual – WebEx \nRegister: Please visit https://events.vtools.ieee.org/m/241427 for the registration link and event link. \nAgenda: \n\n6:00pm: Introduction and online meeting details\n6:05pm: Section Chair report from Ali Nabavi\n6:15pm: IEEE Global update from Kathy Land\n6:30pm: Prize draw\n6:35pm: Keynote presentation from Dr. Inmar Givoni\, Director of Engineering at Uber Advanced Technology Group\, Toronto\n7:05pm: IEEE Canada update from Maike Luiken\n7:20pm: Keynote presentation from Dr. Martin Snelgrove\, CTO at Untether AI\n7:50pm: Awards presentation and prize draw\n\nKeynote Speakers: Dr. Inmar Givoni\, Dr. Martin Snelgrove \nTopic: AI for Self-Driving Cars (Dr. Inmar Givoni) \nAt the Uber ATG R&D centre\, we are working on advanced state-of-the-art models for solving a large range of problems in self driving – perception and prediction\, motion planning\, mapping and localization\, sensor simulation\, and more. All that work is publicly available through academic conferences and venues. In this talk I will cover some exciting recent advances and also discuss the path to production – how we go from research prototypes to deployed systems on vehicle. \nTopic: Building Cool Silicon in the Frozen North (Dr. Matin Snelgrove) \nBiographies: \n\n\n\nDr. Inmar Givoni\nInmar Givoni is a Director of Engineering at Uber Advanced Technology Group\, Toronto\, where she leads a team whose mission is to bring 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 2017 Arbor Award from UofT. In 2018 she was recognized as one of Canada’s 50 inspiring women in STEM and recently recognized as one of Canada’s Tech Titans: Top 19 of 2019.. She was featured in Marie Claire\, Toronto Life\, The Globe and Mail\,  TWIML & AI podcast\, ReWork’s list of 30 influential women in Canadian AI\, UofT’s News\, and other media venues. \nDr. Martin Snelgrove \n\n\n\nMartin is CTO of Untether AI\, who have just announced their first product: a high-performance AI chip that puts Peta-operations per second onto a board. The magic to getting the massive computing power AI needs is to be very careful with the femtoJoules: you can only fit so many watts in a box\, so you have to use them very carefully. It turns out that to do that you have to rethink John von Neumann’s 1947 computer architecture\, and it turns out that understanding AI as a workload lets you do that.    Martin was a professor at the University of Toronto\, then had a Nortel/Mitel-supported industrial research chair at Carleton. Over 16 years of teaching he saw the vast majority of the students Canada paid for head straight down to California. So he moved over to the dark side\, and has been in the founding team for three tech companies in Toronto; Soma\, Kapik and now Untether. It turns out that because Canada produces great engineers\, you can give them a great place to work by putting teams together. Top-grade talent likes working with top-grade talent.
URL:https://www.ieeetoronto.ca/event/ieee-toronto-virtual-agm/
LOCATION:Toronto\, Canada
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