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.
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
Status of the Internet in Canada and the importance of Canadian IXP’s
Chief Technology Officer, CIRA/.CA
A quick overview of the Canadian Internet exchange landscape from coast to coast to coast. Canada has its share of challenges and opportunities in building and growing the IXP infrastructure near the Canadian border, and also to support the need of the rural communities.
As an expert in developing innovative, leading-edge IT solutions, Jacques has established CIRA as a global leader among ccTLD registries. He has 25+ years of experience in the private and not-for-profit sectors and as CIRA’s CTO,is currently leading CIRA Labs, CIRA’s innovation hub and providing leadership and direction for the management and security of the .CA registry and its underlying DNS.
A visionary in the Internet community, Jacques led the development of CIRA’s Internet Performance Test, is an outspoken advocate for the adoption of IPv6 and represents the .CA registry internationally as a member of a variety of working groups and advisory groups, including being a member of ICANN’s Security and Stability Advisory Committee (SSAC), TLDOPS standing committees and TechDay and DNSSEC Planning Program Committee.
Jacques is committed to the development of a new Canadian Internet architecture. He has served as the catalyst for the creation of a national Canadian IXP association, CA-IX, and is a member of the Manitoba Internet Exchange’s (MBIX) and the DNS-OARC Board of Directors.
Jacques holds an Electronics Engineering Technologist diploma from Algonquin College in Ottawa, is ITIL v3 Foundation certified and is a certified Agile ScrumMaster.
11:30 – 12:00 Lite Lunch, Networking, and Welcoming Remarks
12:00 – 13:00 Seminar
Fields-CQAM Public Lectures: Ali Ghodsi, University of Waterloo
What is missing from common practice in machine learning?
AI, and machine learning in particular, is enjoying its golden age. Machine learning has changed the face of the world over the past two decades but we are still a long way from achieving a general artificial intelligence. In this talk, I will discuss a couple of elements that I believe are missing from common practice in machine learning, including incorporating causality and creating a new framework for unsupervised learning.
Ali Ghodsi is a Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. His research involves statistical machine-learning methods. Ghodsi’s research spans a variety of areas in computational statistics. He studies theoretical frameworks and develops new machine learning algorithms for analyzing large-scale data sets, with applications to bioinformatics, data mining, pattern recognition, robotics, computer vision, and sequential decision making.
THURSDAY, JUNE 20TH, 2019.
6:00 PM – 7:00 PM.
7:00 PM – 8:00 PM.
HEALTH SCIENCE BUILDING, RM. 1301 (LOCATED ON THE GROUND FLOOR), CARLETON UNIVERSITY.
FREE ADMISSION FOR THIS PUBLIC LECTURE.
PLEASE REGISTER HERE.
|8:30 am – 9:00 am||Registration|
|9:00 am – 9:15 am||Opening Remarks||Rafik Goubran||Carleton University|
|9:15 am – 10:00 am||Keynote Presentation:
Data Mining and Machine Learning for Authorship and Malware Analyses
|Benjamin C. M. Fung
|10:00 am – 10:30 am||Break|
|10:30 am – 11:45 am||Cybersecurity: Top 5 class imbalance ML challenges and data sets
|Class Imbalance in Fraud Detection
|MindBridge Analytics Inc.|
|Handling class imbalance in natural language processing
|IMRSV Data Labs|
|11:45 am – 12:45 pm||Lunch|
|12:30 pm – 2:10 pm||Adaptive learning with class imbalanced streams
|Herna L. Viktor
|University of Ottawa|
|Radar-based fall monitoring using deep learning
|Privacy-preserving data augmentation in medical text analysis
|National Research Council|
|Failure modelling of a propulsion subsystem: unsupervised and semi-supervised approaches to anomaly detection
|Julio J. Valdés
|National Research Council|
|2:10 pm – 2:25 pm||Break|
|2:25 pm – 3:40 pm||TBD||Reddy Nellipudi||DB Schenker|
|AuditMap.ai: Hierarchical Sentence Classification in Unstructured Audit Reports
|Deep Learning techniques for unsupervised anomaly detection
|RANK Software Inc.|
|3:40 pm – 3:50 pm||Closing Remarks|