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 |
The inaugural OSDforum will take place in Ottawa this September 18. It is of interest to System architects, software designers, hardware designers and researchers from government, industry and academia.
RISC-V is the 5th generation of the Reduced Instruction Set Computer (RISC-V) Instruction-Set Architecture (ISA), the OpenHW Group is a not-for-profit global organisation aiming to boost the adoption of open-source processors by providing a platform for collaboration, creating a focal point for ecosystem development, and offering open-source IP for processor cores.
Don’t miss out the opportunity to join this exciting new development platform and get your own RISC-V development board to keep. All this while learning from leading industry and academic experts focused on IoT, Edge and Machine Learning development that leverage open source SW and HW.
Space is limited and we have all indications that the event will sell out. Register today.
Title: 5G for Smart Everything: From Smart Meters to the New Power Grid. What is needed to get there ?
Speaker: Akshay Sharma, Executive Research Fellow, neXtCurve: www.next-curve.com
Date/Time:Â Tuesday, November 12, 2019, from 2 – 3 pm.
Admission: Free, but registration is required for security purposes. Please contact by e-mail: branislav @ieee.org or ajit.pardasani@ieee.org.
Abstract: This talk discusses how 5G with Edge Computing, and Ultra-low latency (sub-5ms) with Gigabit speed bandwidth will be a game changer with Smart Meters and a new Electric Grid can be enabled with Smart Lamposts. As we transition to DevOps, AIOps, newer Closed Loop Automation systems will occur. As we connect AI-powered Virtual Personal Assistants to IoT devices in the home, now we have to imagine the entire macro-infrastructures being all hyper-connected. What is needed to get there will be discussed at the seminar.
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Speaker’s Bio: Akshay Sharma is originally from Ottawa, B. Eng Computer Systems Engineering from Carleton, a tech analyst, formerly from Gartner, having authored or co-authored over 280 research notes, on emerging technologies like SD-WAN, 5G, mobile video, cloud CDN, IoT, etc. in the past decade. A frequent speaker at tech events, he is often quoted in leading institutions like CNN, Wall St. Journal, etc. He is a former CTO of one of the first video/WiFi smartphone firms, former Chief Architect at Siemens Mobile, and has been given awards by the NJ IEEE Chapter on talks he gave on 5G and Cybersecurity. He is on the tech advisory board for 5G and DevOps startups: LB-N, Kovair, along with others. Mr Sharma’s recent publications include: Search Results for “akshay†– neXt Curve