CQAM events are your chance to explore
the cutting edge of mathematical research
June 17-18, 2019
The Fields Institute, Room 210
We are bringing together leaders in Data Science, Artificial Intelligence and Clinical care to highlight how we can deliver the next generation of patient care.
At the Fields-CQAM-DAC-Vector Data Workshop, researchers will attempt to answer complex clinical questions using de-identified primary care data of over 110,000 diabetic patients. A wide variety of research methods will be used including advanced mathematical modelling, machine learning algorithms and artificial intelligence.
Results and lessons learned will be shared with the group and the end of Day 2.
June 20 - 21, 2019
AI, and machine learning in particular, is enjoying its golden age. Machine learning has changed the face of the word over the past two decades but we are still a long way from achieving a general artificial intelligence. In Machine Learning in the Presence of Class Imbalance, Ali Ghodsi will discuss a couple of elements that he believes are missing from common practice in machine learning, including incorporating causality and creating a new framework for unsupervised learning.
Public Lecture – Thursday, June 20 (Health Science Building, Rm 1301)
Full-day Workshop – Friday, June 21 (Residence Commons)
July 1 - August 29, 2019
The Fields Institute
The Fields Undergraduate Summer Research Program (FUSRP) welcomes carefully selected undergraduate students from around the world for a rich mathematical research experience in July and August.
The project experience, quality mentorship, and team/independent work are intended to foster enthusiasm for continued research. Students work closely with each other and with their supervisor in a collaborative research team. This competitive initiative matches a group of up to five excellent students with faculty from Fields Principal Sponsoring or Affiliate Universities, visiting scientists, or researchers in industry.
July 5, 2019
The Fields Institute, Room 230
ONGrad, an Ontario Graduate School Program Discovery Day, is an opportunity for those participating in an Undergraduate Summer Research Program (NSERC UGSRP/FUSRP) or the MITACS Globalink Internship Program to learn about graduate school possibilities. Join us at the Fields Institute in Toronto - one of the world’s most dynamic and diverse cities - and discover the exciting graduate school opportunities offered at some of Ontario’s top-ranked universities.
This is event is being hosted by the Master of Science in Applied Computing (MScAC) Program, University of Toronto.
August 12 - 16, 2019
University of Waterloo
Cryptography plays a central role in securing communication and information technology services around the world. Academic research in cryptography runs a broad spectrum, from pure mathematics to applied computer science and software and electrical engineering. Selected Areas in Cryptography (SAC) is Canada's research conference on cryptography, held annually since 1994. SAC consists of contributed talks on refereed scientific papers selected by an international program committee. This year, as for the past few years, SAC will be preceded by the SAC Summer School, which will feature invited instructors lecturing on advanced topics in cryptography, oriented primarily towards graduate students, post-doctoral, and industry researchers working in cryptography.
August 12-16, 2019
Bahen Centre 1210
This workshop aims to equip graduate students and postdoctoral fellows in mathematics and related disciplines with the tools necessary to solve common problems encountered in the pharmaceutical industry. The focus will be on development of pharmacometric skills to approach questions centred on drug development and dose/therapy optimization using a variety of state-of-the-art quantitative systems pharmacology (QSP) methodologies, also known as systems modeling.
Registration for this event is by invitation only.
August 19 - 23, 2019
Bahen Centre 1210
The Summer School on Data Science Tools and Techniques in Modelling Complex Networks will explore various theoretical and practical aspects of relational data representation and mining. The format of the course will be a mix of lectures and demonstrations of various techniques over relational datasets using Python, Julia and Jupyter Notebooks.
Bogumil Kaminski - Warsaw School of Economics
Pawel Pralat - Ryerson University
Przemyslaw Szufel - Warsaw School of Economics
François Théberge - Tutte Institute for Mathematics and Computing