Events

May
30
Thu
Technical Talk: Recent Results and Open Problems in Evolutionary Multiobjective Optimization @ Colonel By (CBY), Room A-707, University of Ottawa
May 30 @ 18:30 – 20:30
Technical Talk: Recent Results and Open Problems in Evolutionary Multiobjective Optimization @ Colonel By (CBY), Room A-707, University of Ottawa | Ottawa | Ontario | Canada

You are invited to the technical talk entitled

Recent Results and Open Problems in Evolutionary Multiobjective Optimization

Date

Thursday May 30th, 2019

Time

6:15 PM Arrival and networking (light snacks available)

6:45 PM Approximate start of talk (40-60 mins)

7:45 – 8:00 PM Q&A period

8:00 – 8:30 PM Post-talk networking and discussion

Location

Colonel By (CBY) A-707

Faculty of Engineering
University of Ottawa
161 Louis Pasteur Private, Ottawa, K1N 6N5

admission is free but registration is required on EventBrite

Speaker

Professor Carlos Coello, CINVESTAV-IPN, Mexico, IEEE CIS Distinguished Lecturer

Abstract

Evolutionary algorithms (as well as a number of other metaheuristics) have become a popular choice for solving problems having two or more (often conflicting) objectives (the so-called multi-objective optimization problems). This area, known as EMOO (Evolutionary Multi-Objective Optimization) has had an important growth in the last 15 years, and several people (particularly newcomers) get the impression that it is now very difficult to make contributions of sufficient value to justify, for example, a PhD thesis. However, a lot of interesting research is still under way. In this talk, we will review some of the research topics on evolutionary multi-objective optimization that are currently attracting a lot of interest (e.g., handling many objectives, hybridization, indicator-based selection, use of surrogates, etc.) and which represent good opportunities for doing research. Some of the challenges currently faced by this discipline will also be delineated.

Speaker Biography

Carlos Artemio Coello Coello received a PhD in Computer Science from Tulane University (USA) in 1996. His research has mainly focused on the design of new multi-objective optimization algorithms based on bio-inspired metaheuristics, which is an area in which he has made pioneering contributions. He currently has over 470 publications which, according to Google Scholar, report over 43,900 citations (with an h-index of 83). He has received several awards, including the National Research Award (in 2007) from the Mexican Academy of Science (in the area of exact sciences), the 2009 Medal to the Scientific Merit from Mexico City’s congress, the Ciudad Capital: Heberto Castillo 2011 Award for scientists under the age of 45, in Basic Science, the 2012 Scopus Award (Mexico’s edition) for being the most highly cited scientist in engineering in the 5 years previous to the award and the 2012 National Medal of Science in Physics, Mathematics and Natural Sciences from Mexico’s presidency (this is the most important award that a scientist can receive in Mexico). He is also the recipient of the prestigious 2013 IEEE Kiyo Tomiyasu Award, “for pioneering contributions to single- and multiobjective optimization techniques using bioinspired metaheuristics” and of the 2016 The World Academy of Sciences (TWAS) Award in “Engineering Sciences”. Since January 2011, he is an IEEE Fellow. He is also Associate Editor of several journals including the two most prestigious in his area: IEEE Transactions on Evolutionary Computation and Evolutionary Computation. He is currently Vicepresident for Member Activities of the IEEE Computational Intelligence Society (CIS), an IEEE CIS Distinguished Lecturer and Full Professor with distinction at the Computer Science Department of CINVESTAV-IPN in Mexico City, Mexico.

 

Jun
20
Thu
Fields-CQAM Public Lectures: What is missing from common practice in machine learning? @ Carleton University
Jun 20 @ 19:00 – 20:00

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 REGISTER HERE.

Jun
21
Fri
FIELDS CENTRE OF QUANTITATIVE MODELLING AND ANALYSIS: WORKSHOP ON Machine Learning in the Presence of Class Imbalance @ Residence Commons, Carleton University
Jun 21 @ 08:30 – 16:30
FIELDS CENTRE OF QUANTITATIVE MODELLING AND ANALYSIS: WORKSHOP ON Machine Learning in the Presence of Class Imbalance @ Residence Commons, Carleton University | Ottawa | Ontario | Canada

 

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
Abstract

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

 

Sep
2
Wed
Characterization and Modeling of GaN HEMT Trapping Effects for Microwave Circuit Design
Sep 2 @ 11:00 – 12:00

 

IEEE Ottawa Section: MTT-S / AP-S Chapter presents:

Title: Characterization and Modeling of GaN HEMT Trapping Effects for Microwave Circuit Design

Date: September 2nd, 2020

Time: 11 AM (ET)

Register at: https://events.vtools.ieee.org/m/238482

This talk will review some recent advancements achieved on the characterization and modelling of the trapping effects felt in GaN HEMT transistors, and their impact on microwave circuit design. Because of their nowadays importance, a particular attention will be payed to applications on high power amplifiers for mobile wireless infrastructure and pulsed radar applications.

For that, the talk will start by recollecting the most common model formulations adopted for the various levels of RF engineering, from the device level (physics) to the transistor (circuit) and amplifier (system) level. Starting by the Shockley-Read-Hall capture and emission processes we will be able to understand one of the fundamental signatures of trapping effects, the significantly different charge and discharging time constants, and its impact on power amplifier nonlinear distortion behavior. Then, some widely adopted approaches of the channel current transients’ characterization are addressed and the talk concludes by presenting some illustrative cases of application to RF high power amplifiers.

Speaker: Jose C. Pedro

José C. Pedro received the Diploma, Ph.D., and Habilitation degrees in electronics and telecommunications engineering from the Universidade de Aveiro, Aveiro, Portugal, in 1985, 1993, and 2002, respectively.

He is currently a Full Professor with the Universidade de Aveiro and head of the Aveiro site of the Instituto de Telecomunicações. He has authored 2 books and authored or co-authored more than 200 papers in international journals and symposia. His current research interests include active device modelling and the analysis and design of various nonlinear microwave circuits.

Dr. Pedro was a recipient of various prizes including the 1993 Marconi Young Scientist Award, the 2000 Institution of Electrical Engineers Measurement Prize, the 2015 EuMC Best Paper Microwave Prize, and the Microwave Distinguished Educator Award. He has served the scientific community as a Reviewer and an Editor for several conferences and journals, namely, the IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, for which he was the Editor-in-Chief.

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