Speaker Series

Illuminate your understanding of data science, health informatics, machine learning and many more fascinating global pursuits. Join us while we embark on a journey to teach, inspire and motivate!

Upcoming Event



Past Events


111 Days Later - CHI's COVID-19 Modelling

June 24, 2020

One-hundred and eleven days ago, the Centre for Health Informatics (CHI) at University of Calgary spear-headed the development of a set of surveillance tools as part of the University of Calgary's effort to help monitor the spread of COVID-19. This talk will focus on the COVID-19 modelling efforts undertaken at CHI. We will discuss some of the projects that CHI was part of, the different research questions these studies addressed, and the learned lessons about COVID-19 from these efforts.Additional discussions will include roles ranging from where CHI aided modelling-related efforts, where we have served as consulting and data-wrangling conduits, to developing our own simulation models that have provided a sober, second analysis into the current state of COVID-19 in Alberta from the public health perspective.

 

Frank Lee

Frank Lee is a member of the Centre for Health Informatics, Data Intelligence for Health Lab and a PhD Candidate in Epidemiology in the Department of Community Health Sciences, University of Calgary. He completed his Masters of Public Health at the University of California, Berkeley. Frank’s research interest lies in data science methodologies surrounding health care and public health.

David Vickers

Dr. David Vickers holds an Interdisciplinary PhD applying Dynamical Systems theory to Epidemiology. Before joining the Libin Cardiovascular Institute's Mozell Core Analysis Lab in October 2019, he has worked as an analyst with Infection Prevention and Control at Alberta Health Services, and a Research Associate in the Division of Immunology at the Imperial College London. His interests are based on the premise that many afflictions in Public Health persist, not despite our prosperity and technical progress, but because of them.


Alberta's Tomorrow Project

May 21, 2020

Dr. Grace Shen-Tu’s experience lies within research, knowledge translation, and evaluation. She is committed to moving research discovery to where it can have the greatest impact. Before joining ATP, she led many knowledge translation and evaluation projects within the Alberta Cancer Prevention Legacy Fund. In her current role as Research Lead with ATP, she encourages collaboration with external scientists using longitudinal data to reveal causes and preventions of cancer and chronic disease.


Rei Safavi-Naini

Blockchain and its Application to Healthcare

Feb. 20, 2020

Rei Safavi-Naini is the NSERC/Telus Industrial Chair and Alberta Innovates Strategic Research Chair in Information Security here at the University of Calgary. She has extensive background in post-quantum cryptography, cloud security and security of blockchain and decentralized systems. As such, she came to visit the CHI and spoke on the ground breaking technology of blockchain. 


James White and Hude Quan

The Libin Cardiovascular Institute and the Centre for Health Informatics Present:

Feb. 5, 2020

Hude Quan

Hude Quan is the Director of the Centre for Health Informatics. A major theme of Dr Quan's research is to develop novel methods for analyzing “big data” and improving its quality to enable optimal use for health research and precision medicine. Different members of Dr. Quan's team - Elliot Martiin, Natalie Wiebe, Stephanie Garies, and Bing Li - all spoke on their current research underway at the centre.

James White

James is the Director of the Stephenson Cardiac Imaging Centre at the Libin Cardiovascular Institute. He is a cardiologist and a clinician scientist who is leading innovation in cardiovascular MRI care and advanced heart disease research. 


Filipe Lucini - Speaker Series December 2019

The use of artificial intelligence to improve medical decision making…But wait! Can we really trust computers?

Dec. 19, 2019

Dr. Filipe Lucini is a member of the DIH Lab and a Postdoctoral Associate in the Department of Critical Care Medicine. He spoke on the difference between AI, machine learning and and deep learning and fooled us all with examples of how seamlessly a computer controlled robot can perform a human activity like creating a poem. Large studies have shown that when comparing a healthcare professional to an AI counterpart, the AI clinicians are making similar dosage amounts for IV fluids and are able to detect abnormalities in diagnostic medical photographs. Lucini exemplified the possibilities that are opening for integrating machine learning and health care decision making as well as pointing out key challenges that arise when corroborating "big data" and real life patients.


Jacqueline Harris

From Raw Data to Model Inputs; the Importance of Feature Engineering

Nov. 21, 2019

Jacqueline Harris is a PhD student in Computer Science at the University of Alberta under the supervision of Dr. Russell Greiner. She is a member of the University of Alberta Computational Psychiatry research team and an AI student ambassador with Intel. Her research is primarily focused on predictive modelling in depression, and feature extraction techniques for functional magnetic resonance imaging (fMRI).
 

Data has become widely available, driving much of the success and interest in machine learning. The reality though, is most of this data is not in a form that is appropriate to serve as an input to machine learning models. The choice of how to transform raw data to model inputs (features) can be vital to the success of a model; so, before jumping into data modelling it is important to consider different approaches to feature engineering. In this talk, Jacqueline spoke on the difference between structured and unstructured data, some general approaches to feature engineering, and provide some specific examples from functional magnetic resonance imaging.


Zahra Shakeri

Does more data beat better learning algorithms?

Oct. 24, 2019

Zahra Shakeri is a member of the Data Intelligence for Health (DIH) Lab and a Postdoctoral Associate of Health Data Science in the Department of Community Health Sciences, University of Calgary. She completed her PhD in Computer Science at the University of Calgary in August 2018. During her M.Sc. and PhD programs, she conducted several in-depth studies in the areas of cognitive science, human-computer interaction, software engineering, social media analysis, and emergency management, using statistical and qualitative analysis as well as machine learning techniques. Zahra's research interests are currently focused on the intersection of machine learning, data visualization, public health surveillance, critical care, and social media analysis. She spoke to us about the importance of data availability and methodology in data science projects.


Dr. David Anderson

The field of “precision health” with a focus on integrating ‘omics’ and other types of “big” data in a clinical context

Sept. 26, 2019

Dr. David Anderson is a tenure-track instructor and the Director of the bioinformatics major in the U of C BHSc. program. His teaching interests have been focused both on primary bioinformatics education and on the integration of “big data” molecular biology and the clinical environment. His research interests are focused at the intersection between molecular functions, biochemistry and genetic variation, looking at the ways in which physical interactions between mutations at different sites (i.e. epistasis) govern the functions of key biological molecules. Dr. Anderson has developed a suite of different statistical analysis tools that estimate the effect of distinct mutations on a single quantitative function, which allows for the simultaneous assessment of potential molecular interactions between them.