A talk on AI (Artificial Intelligence) titled “Managing the development of AI and Machines that learn” presented by the CEO of nuenergy.ai, Niraj Bhargava.

Abstract:

It is widely acknowledged that AI technology will
transform organizations and society around the globe – and with recent
advancements in processing power, data accessibility, and algorithms we
suddenly find ourselves at the beginning of this transformation.
Introducing the Machine Trust Index (MTI), assisting us to boldly
proceed with a responsible, innovative spirit. The goal of the MTI is to
establish an open and versatile framework for measuring and managing
trust in the evolving sphere of AI. The MTI provides measurable
evidence, transparency and accountability of an AI solution, allowing
providers to effectively communicate the value of their solutions as
well as their measurable trustworthiness.

Biography:

Niraj Bhargava is Founder and CEO of NuEnergy.ai,
the developers of the Machine Trust Index™ (MTI) for managing AI
deployments. He is also Chair of the Innovation Committee of the Board
at the Royal Ottawa. Niraj was President and CEO of Enerstat
Limited, and led it through its turnaround and acquisition, Founding CEO
of QCED Inc., a faculty member in Entrepreneurship at Queen’s
University, a Director of the Queen’s Executive MBA, and then Dean of
the Business School at Royal Roads University. Niraj practiced
engineering at Bell-Northern Research and global marketing at General
Electric, and was the founding General Manager of GE Energy Management. Niraj was the founding CEO of Fluent.ai in Montreal and Co-Founder, Chairman and Chief Executive Officer of Energate Inc.

The PATW is a global competition for Young professionals and students within engineering to develop and showcase presentation skills. Membership to the IET is not a requirement to enter, but you must be 18-30 years of age and be prepared to;

Deliver a 10 minute presentation on any engineering or technology related area. Enhance your knowledge, develop your skills, increase your profile, and open doors for your career.

For more details see : https://www.theiet.org/PATW

Contact kyle.manel@ietvolunteer.org for event information and/or for registration.

Why should you attend?

 

·      Data analytics is a priority for many organizations

·      Many jobs now call for some level of analytic
knowledge

·      Storytelling with data will soon become a “must
have” skill

 

What is Cognos Analytics?

 

“IBM® Cognos® Analytics integrates data preparation,
reporting, modeling, self-service analysis, dashboards, stories, event
management and now automated predictive analytics into one stack. Moreover, the
latest release makes extensive use of AI, including machine learning, natural
language processing (NLP) and natural language generation (NLG), in order to
automate as many features for the end user as possible, in an effort to make
BI, analytics and predictive analysis easy for business users.”

About the speaker:

Mohammed Omar Khan is an Offering Manager on the IBM Cognos
Analytics. He works with the development, design, sales, marketing, support and
more teams to make Cognos Analytics a leader in the BI market. He is a Carleton
University Alumni. Some of his achievements include 2nd place in Data Day 5.0
Poster Competition held at Carleton University, IBM VP Award, and IBM Managers
Choice Award.

Career Fair

Algonquin College – School of Advanced Technology

MORE THAN 40 PART-TIME FACULTY POSITIONS AVAILABLE

SATURDAY, MAY 25, 2019

9am to 1pm

Join the learner-driven workforce of one of the National Capital Region’s Top Employers.

Enjoy a career you can be proud of by helping our learners become the leaders of tomorrow. We are looking for part-time faculty members in the following programs:

• Aviation Management – General Arts and Science

• Computer Engineering Technology – Computing Science

• Electro-Mechanical Engineering Technician

• Manufacturing Engineering Technician

• Mechanical Engineering Technology

• Computer Programmer

• Computer Systems Technician

• Computer Systems Technology – Security

• Bachelor of Information Technology – Network Technology

CLICK HERE TO REGISTER

IEEE Ottawa Seminar Series on AI and Machine Learning

Hosted by IEEE Ottawa PHO Chapter, EMBS Chapter, CS Chapter, and SP Chapter Jointly with Vitesse Reskilling

Application of
Deep Learning for Medical Image Analysis

Fatemeh Zabihollahy

Carleton University

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Wednesday, June 26, 2019

359 Terry Fox Drive, Suite 200, Kanata, Ontario

11:30 – 13:30

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Medical imaging, (e.g., computed tomography (CT), magnetic resonance
imaging (MRI), positron emission tomography (PET), mammography, ultrasound,
X-ray) has advanced at a rapid speed over last decades. Currently, the medical
image interpretation is mostly performed by human experts, which is a tedious
task and subject to high inter-operator variability. Deep learning is providing
exciting solutions for medical image analysis problems. Recent advances in deep
learning have helped to identify, classify, and quantify patterns in medical
images. In this seminar, we introduce the principles and methods of deep
learning concepts, particularly convolutional neural network (CNN). We show how
CNN operates. I will describe several interesting applications of deep learning
for medical image analysis, including my recent works on segmenting myocardial
scar (injured) tissue in the heart, prostate tumor detection, and kidney lesion
localization in 3D MRI and CT images.

Biography

Fatemeh Zabihollahy is currently
a Ph.D. candidate at Carleton University. She obtained her MASc (2016) and BASc
(2001) both in Biomedical Engineering from Carleton University, Canada and
Shahid Beheshti University, Iran, respectively. She worked in the medical
devices industry as an R&D engineer for ten years. Her research interest is
in the field of application of deep learning techniques for medical image
analysis.

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Event
is free, but space is limited.  All
participants must register in advance.   

Please
follow the link to register

https://ieeeottawaaiml2019jun26.eventbrite.ca

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For more information, please contact: Kexing Liu kexing.liu@ieee.org