Events
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 Sciencesâ€. 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.
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 |
Speaker 1: Hisham Abed, P.Eng., Ericsson
Topic:Â Power Integrity – Best design practices
Speaker 2: Dr. Ihsan Erdin, Celestica
Topic:Â Power Integrity Optimization amidst MLCC shortage
Parking:Â Free
Registration: Free, and is on a first to reply basis. Preference given to IEEE EMC and CPMT society members. Seating is limited. E-mail reservation is required.
Pizza and soft drinks will be served.
Organizer: Dr. Syed Bokhari, Chairman, IEEE Ottawa
EMC chapter
Syed.Bokhari@fidus.com,
Office :(613) 595 – 0507 Ext. 377, Cell: (613) 355 – 6632
Directions:Â Â Â www.fidus.com
IEEEÂ Distinguished Lecturer Presentation hosted jointly by the IEEE Ottawa EMC and CASS/SSCS/EDS Chapters:
Speaker :   Dr. Marcos Rubinstein, Professor, University of Applied Sciences of Western Switzerland
Topic  :   The Lightning Phenomenon
Date   :   Tuesday October 22, 2019
Time   :   12(noon) – 1pm
Location :Â Â Â 4124-ME (Meckenzie Building), Carleton University, 1125 Colonel By Drive, Ottawa – K1S5B6
Registration:Â Free, Please E-mail Ram Achar (achar@doe.carleton.ca)
Refreshments: Served
Parking : Payment based Metered Parking spots in the campus
Organizers:
        Ram Achar, Dept. of Electronics, Carleton University
        Chairman CASS/SSCS/EDS Chapters
        achar@doe.carleton.ca
        Dr. Syed Bokhari, Chairman, IEEE Ottawa EMC chapter
Abstract
Lightning is one of the primary causes of damage and malfunction of telecommunication and power networks and one of the leading causes of weather-related deaths and injuries.
Lightning is composed of numerous physical processes, of which only a few are visible to the naked eye.
This lecture presents various aspects of the lightning phenomenon, its main processes and the technologies that have been developed to assess the parameters that are important for engineering and scientific applications. These parameters include the channel-base current and its associated electromagnetic fields.
The measurement techniques for these parameters are intrinsically difficult due to the randomness of the phenomenon and to the harsh electromagnetic environment created by the lightning itself.
Besides the measurement of the lightning parameters, warning and insurance applications require the real-time detection and location of the lightning strike point. The main classical and emerging lightning detection and location techniques, including those used in currently available commercial lightning location systems will be described in the lecture. The newly proposed Electromagnetic Time Reversal technique, which has the potential to revolutionize lightning location will also be presented.
Biography
Marcos Rubinstein received the Master’s and Ph.D. degrees in electrical engineering from the University of Florida, Gainesville.
In the decade of the 1990’s, he worked as a research engineer at the Swiss Federal Institute of Technology, Lausanne and as a program manager at Swisscom in the areas of electromagnetic compatibility and lightning. Since 2001, he is a professor at the University of Applied Sciences of Western Switzerland HES-SO, Yverdon-les-Bains, where he is currently responsible for the advanced Communication Technologies Group. He is the author or coauthor of 300 scientific publications in reviewed journals and international conferences. He is also the coauthor of nine book chapters and the co-editor of a book on time reversal. He served as the Editor-in-Chief of the Open Atmospheric Science Journal, and currently serves as an Associate Editor of the IEEE Transactions on EMC.
Prof. Rubinstein received the best Master’s Thesis award from the University of Florida, the IEEE achievement award and he is a co-recipient of the NASA’s Recognition for Innovative Technological Work award. He also received the ICLP Karl Berger award. He is a Fellow of the IEEE and an EMP Fellow, a member of the Swiss Academy of Sciences and of the International Union of Radio Science.