Events
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.
Biography
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.
DATE:
THURSDAY, JUNE 20TH, 2019.
PRESENTATION
6:00 PM – 7:00 PM.
NETWORKING
7:00 PM – 8:00 PM.
LOCATION
HEALTH SCIENCE BUILDING, RM. 1301 (LOCATED ON THE GROUND FLOOR), CARLETON UNIVERSITY.
FREE ADMISSION FOR THIS PUBLIC LECTURE.
PLEASE REGISTERÂ 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 Biography |
McGill University |
10:00 am – 10:30 am | Break | ||
10:30 am – 11:45 am | Cybersecurity: Top 5 class imbalance ML challenges and data sets Abstract |
Stephan Jou Biography |
Interset |
Class Imbalance in Fraud Detection Abstract |
Robin Grosset Biography |
MindBridge Analytics Inc. | |
Handling class imbalance in natural language processing Abstract |
Isuru Gunasekara Biography |
IMRSV Data Labs | |
11:45 am – 12:45 pm | Lunch | ||
12:30 pm – 2:10 pm | Adaptive learning with class imbalanced streams Abstract |
Herna L. Viktor Biography |
University of Ottawa |
Radar-based fall monitoring using deep learning Abstract |
Hamidreza Sadreazami Biography |
McGill University | |
Privacy-preserving data augmentation in medical text analysis Abstract |
Isar Nejadgholi Biography |
National Research Council | |
Failure modelling of a propulsion subsystem: unsupervised and semi-supervised approaches to anomaly detection Abstract |
Julio J. Valdés Biography |
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 Abstract |
Daniel Shapiro Biography |
Lemay.ai | |
Deep Learning techniques for unsupervised anomaly detection Abstract |
Dušan Sovilj Biography |
RANK Software Inc. | |
3:40 pm – 3:50 pm | Closing Remarks |
Ottawa Life Member Affinity Group presents:Â Ottawa L5, the first integrated Connected & Autonomous Vehicle (CAV) test environment in North America.
The Ottawa L5 private test track is a 1,866 acre, fenced and gated private facility with 16 kilometres of paved roads. The largest secure test facility for CAVs in Canada, the Ottawa L5 private test track creates an ideal proving ground for the safe and productive pre-commercial development, testing, validation and demonstration of CAV technologies. The Ottawa L5 testing facilities are equipped with GPS (RTK), dedicated short range communications (DSRC), Wi-Fi, 4G/LTE and 5G telecommunications and networking infrastructure, making it the first integrated CAV test environment of its kind in North America. Find more information at:Â https://www.investottawa.ca/ottawal5
Tour will last about an hour involving a walk around the site and a group discussion of various technical aspects of the L5 facility. An additional treat is the possibility of an autonomous shuttle ride at the site for some attendees.
Please register in advance with wolfram.lunscher@ieee.org by Friday October 11. Priority will be given to Life members. All members and family are welcome. There is an online liability waiver to be signed. The link will be provided to registrants.
Date and Place: The event will be held online on September 26th and 27th, 2020.
“Every accomplishment starts with the decision to try†~ John F. Kennedy
What?
New to Hackathons? Are you also interested in participating in IEEEXtreme 14.0? IEEE WIE Ottawa presents the first ever Mock Hackathon in Ottawa! Win Exciting Prizes and get experience with us. No need to think of an idea! The questions will be given to you. Our mentors will further help you to get a head start in your hackathon journey! This is a practice event just for you! Learn more about IEEEXtreme here-> https://ieeextreme.org/
When?
September 26th and 27th, 2020
Where?
The event is fully online including the mentorship*.
Agenda
September 26th, 2020
01:00 PM The opening ceremony
02:00 PM Commencement of Hackathon
05:00 PM Final Submission
September 27th, 2020
01:00 PM Results declaration webinar
01:30 PM Prize announcement
02:00 PM The closing ceremony
For More Details Visit: https://wie.ieeeottawa.ca/hack613-the-ottawa-hackathon/
Online Talk: From bees to Drones: Exploring bio-inspired machine vision applications for precision agriculture
Bees are used as vectors for pollination and transport of agricultural chemicals in outdoor agriculture and greenhouses. However, in certain situations the use of natural pollinators is problematic. Small unmanned aerial vehicles (UAVs) could serve as an alternate pollination vector in such situations and perform other functions. A step towards the deployment of such a tool is to bring the ability to locate, classify, and analyze flowers aboard a drone.
More info and registration: https://wie.ieeeottawa.ca/event/from-bees-to-drones-exploring-bio-inspired-machine-vision-applications-for-precision-agriculture/.
A presentation by IEEE WIE Ottawa.