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 | ||
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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 |
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. Â
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
The Ottawa Section of the Institute of Electrical and Electronics Engineers (IEEE) and the Canada Aviation and Space Museum cordially invite you to:
The dedication of the IEEE engineering milestone “First Search and Rescue Using Satellite Technology, 1982â€
Join us at the museum for this special event, where we will also celebrate space-related technical achievements as part of the commemoration of the fiftieth anniversary of humans landing on the Moon.
WHO:
The keynote speaker at the dedication ceremony is renowned Canadian astronaut, Dr. Robert Thirsk. Special guests include IEEE President, Dr. José Moura, and IEEE Canada President, Dr. Maike Luiken.
WHAT:
A dedication and unveiling ceremony for two plaques (English and French), recognizing the historical significance of this satellite technology application.
WHEN:
Monday, September 9, 2019 at 2 p.m.
WHERE:
The grounds of the Canada Aviation and Space Museum, 11 Aviation Parkway, Ottawa, ON.
AGENDA:
2 p.m. – 2:45 p.m.:
- Opening remarks and welcome by IEEE Ottawa Section Chair, Dr. Winnie Ye, and IEEE History Committee Chair, Dr. Branislav Djokic
- Welcome address by the Director General of the Canada Aviation and Space Museum, Mr. Chris Kitzan
- Historical perspective on this IEEE milestone by Dr. Michael A. Stott
- Welcome address by IEEE Canada President, Dr. Maike Luiken, and IEEE President, Dr. José Moura
- Keynote speech by Dr. Robert Thirsk
- Unveiling of the plaques by Dr. Robert Thirsk
- Closing remarks by IEEE Ottawa Section Vice-Chair, Mr. Ajit Pardasani
2:45 p.m. – 3:30 p.m.:
- Light refreshments and networking
RSVP:
Ajit Pardasani at Ajit.Pardasani@ieee.org by September 3, 2019.
Advanced Optical Sources for Spectrally Efficient Photonic Systems
Liam Barry,
Dublin City University
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Abstract
The continuing growth in demand for bandwidth (from residential and business users), necessitates significant research into new advanced technologies that will be employed in future broadband communication systems. Two specific technologies which are becoming increasingly important for future photonic
systems are wavelength tunable lasers and optical frequency combs. Although these topics have been studied for over two decades their significance for the development of future ultra-high capacity photonic systems has only recently been fully understood. Wavelength tunable lasers are currently becoming the
norm in optical communication systems because of their flexibility and ability to work on any wavelength. However, as their operating principles are different to standard single mode lasers they can effect how future systems will operate.
For example as optical transmission systems move towards more coherent transmission (where the data is carried using both the intensity and phase of the optical carrier), the phase noise in these tunable lasers will become increasingly important. Optical frequency combs also have many applications for
future photonics systems, and for telecommunications they can be used to obtain the highest spectral efficiency in optical transmission systems by employing the technology of optical frequency division multiplexing (OFDM) that has been widely employed to increase spectral efficiency in wireless systems. Wavelength tunable lasers and optical frequency combs are thus topics at the leading edge of current photonics systems research, and their detailed understanding promises new applications in all-optical signal processing, optical sensing and metrology, and specifically telecommunications. This talk will focus on the development and characterization of various wavelength tunable lasers and optical frequency combs, and then outline how these sources can be employed for developing optical transmission systems and networks which make the best use of available optical spectrum.
Bio
Liam Barry received his BE (Electronic Engineering) and MEngSc (Optical Communications) from University College Dublin and his PhD from the University of Rennes. His main research interests are: all-optical signal processing, optical pulse generation and characterization, hybrid radio/fibre communication
systems, wavelength tuneable lasers for reconfigurable optical networks, and optical performance monitoring. He has worked as a Research Engineer in the Optical Systems Department of France Telecom’s Research Laboratories (now known as Orange Labs), and a Research Fellow at the Applied Optics Centre in Auckland University. He is currently a Full Professor in the School of Electronic Engineering at Dublin City University, establishing the Radio and Optical Communications Laboratory, and is a Principal Investigator for Science Foundation Ireland. He has published over 500 articles in internationally peer reviewed journals and conferences, holds 9 patents in the area of optoelectronics, and has co-founded two companies in the photonics sector.