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.
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.
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 firstname.lastname@example.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
· Storytelling with data will soon become a “must
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
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
Deep Learning for Medical Image Analysis
Wednesday, June 26, 2019
359 Terry Fox Drive, Suite 200, Kanata, Ontario
11:30 – 13:30
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.
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
is free, but space is limited. All
participants must register in advance.
follow the link to register
For more information, please contact: Kexing Liu email@example.com
Antennas for Autonomous Vehicles:
What You Need to Know!
and reliable positioning recently became a critical property of autonomous
vehicles like drones, driverless cars and more. Tallysman Wireless will explain
why the GNSS antenna is the most important component for accurate positioning
and will present the challenges of selecting the appropriate GNSS antenna for
diverse types of autonomous vehicles. Multiple properties of a GNSS antenna
like its phase center variation, ability to reject interferences or multipath
and sensibility to its environment will be analysed and guide lines will be
Refreshments will be served!
Location: 4359 Mackenzie Building, Carleton University.
Time: 6:00 – 7:00 PM
Date: July 17th , 2019
Hautcoeur received the M.Sc. degree in radio communication systems and
electronics from the Ecole Polytechnique of the University of Nantes, Nantes,
France, in 2007 and the Ph.D. degree in signal processing and
telecommunications from the Institute of Electronics and Telecommunications of
Rennes 1, Rennes, France, in 2011. In 2011, he was involved in postdoctoral
training at the University of Quebec in Outaouais (UQO), Gatineau, QC, Canada.
His research field was optically transparent antenna systems for telecommunications.
Since 2014 he works at Tallysman Wireless in Ottawa, Canada and specialized in
the design of high performance GNSS antennas and associated electronics.