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External Events

Below is a list of externally-hosted workshops and seminars to support your data science literacy and analytics capacity. 

To request event promotion on our website, please contact dash.coordinator@ubc.ca.

September 21: UBC Healthy Aging Research Seminar - "New Uses for Bedside Ultrasound in the Older Adult Patient"
WEDNESDAY, SEPTEMBER 21, 2022
2:00PM – 3:00 PM
ZOOM MEETING & IN-PERSON (RUDY NORTH LECTURE THEATRE, DJAVAD MOWAFGHIAN CENTRE FOR BRAIN HEALTH)

Dr. Michael Kobor, the Edwin S.H. Leong UBC Chair in Healthy Aging – A UBC President’s Excellence Chair, will provide a welcome and introduction to the new Edwin S.H. Leong Healthy Aging Program.

Following this, Dr. Kenneth Madden, Professor in the Division of Geriatrics in the Department of Medicine at UBC will present on “New uses for bedside ultrasound in the older adult patient”. This presentation will describe some of the latest research done by the Gerontology and Diabetes Research Laboratory (GDRL) on establishing point-of-care ultrasound as a technique useful in answering specific clinical questions at the bedside of an older adult patient.

Learning Objectives

  1. To recognize the increasing importance of bedside ultrasound in both medicine in general and in care for older adults specifically.

  2. To be able to describe newer uses and limitations for this technology in common issues seen in this population, such as sarcopenia, frailty and diabetes.

We invite you to join in person if possible to get to know others at UBC doing work related to healthy aging. Snacks and refreshments will be provided. For those who can’t attend in person, there is also an option to join via Zoom

Register

September 22-23: World Data Congress 2022 "AI & Data Science - What's Next"

AUGUST 23-26, 2022
SAN FRANCISCO, USA

The WDC conference series is where professionals meet the best and brightest innovators in AI and Data Science. The conference aims to bring together top industry and C-level executives to help you understand how AI and data science can transform your business, leading to the next industrial revolution. Two days Conference is part of the World Data Congress series, which is one of the leading series dedicated to Data Science & AI worldwide.

World Data Congress aims to deliver the advancements of AI & data science, its management, innovation, application, latest research, and comprises of keynotes sessions, expert presentations, high-stake panels and round-table discussions to highlight AI & Data Science scenario, industries automation process, AI implementation and research and other relevant topics. WDC-2022 will provide a valuable opportunity for innovators, researchers and industry experts to exchange their ideas.

Industries covered include Finance, IT, Healthcare, Biotech, Pharma, Travel, Energy, Manufacturing, Retail, Marketing, Transportation, and more.

Register

September 26: UBC Research Data Management Strategy Project - Health Disciplines (CIHR) Focus Session
MONDAY, SEPTEMBER 26, 2022
1:00PM – 2:00 PM
ZOOM MEETING

Have your say on UBC's new draft Research Data Management Strategy.

An initial draft has been created based on our consultations with the UBC community in late 2021 and early 2022 and by following the Research Infrastructure Self-Evaluation (RISE) model. The UBC Advanced Research Computing (ARC) group will host town halls and focus group sessions to incorporate your feedback on the draft. The virtual focus group sessions will be themed around specific communities and interest areas. Everyone is welcome to attend the sessions.

Learn More

Register

October 3-7: UBC ARC Research Computing Back to School Bootcamp
OCTOBER 3-7, 2022
HYBRID (IN-PERSON & VIRTUAL) - LOCATION TBA

UBC's Advanced Research Computing (ARC) group will offer hands-on training on UBC ARC Sockeye and UBC ARC Chinook, referencing the research lifecycle and practical tips and tricks to help attendees apply lessons learned immediately in their research. Registrants can attend in-person or virtually. Those who attend in person will benefit from multiple ARC staff supporting them during the instruction.

Instructions will be provided on the following course topics:

  • Unix

  • Software Installation

  • Running Jobs

  • GPU Usage

  • Parallel Computing

  • Data Management

  • Data Transfer

All disciplines and skill levels are welcome. No cost affiliated with training. 

Register

October 12: UBC Research Data Management Strategy Project - Natural Sciences and Engineering (NSERC) Focus Session
WEDNESDAY, OCTOBER 12, 2022
1:20PM – 2:30 PM
ZOOM MEETING

Have your say on UBC's new draft Research Data Management Strategy.

An initial draft has been created based on our consultations with the UBC community in late 2021 and early 2022 and by following the Research Infrastructure Self-Evaluation (RISE) model. The UBC Advanced Research Computing (ARC) group will host town halls and focus group sessions to incorporate your feedback on the draft. The virtual focus group sessions will be themed around specific communities and interest areas. Everyone is welcome to attend the sessions.

Learn More

Register

December 7-8: UBC Sauder School of Business Executive Education - Big Data Leadership
DECEMBER 7-8, 2022
ONLINE

Everywhere you turn, people are talking about the revolutionary potential of big data in combination with the latest digital technologies. Yet most organizations struggle to unlock this potential, as a growing number of digital-native competitors redefine the way business is done. 

This program demystifies the world of big data by providing a practical strategic guide for planning and implementing a digital transformation plan. Examine how data can influence your organization’s value proposition. Develop an agile performance approach to achieve actionable results. Prepare to implement a performance strategy that can propel your organization forward in today’s digitally-charged environment.

This program is for business managers and senior leaders who seek to improve their understanding of data analytics and the cultural, operational and technical issues involved in launching and leading a digital transformation plan.

Register

Past Events
2021
June 24: Health Data Research Network Webinar

UBC Health recognizes the growing need for research collaborations that address the increasingly complex and interconnected problems facing society. The recent addition of research to the scope of UBC Health illustrates our commitment to addressing these complex challenges by providing a variety of supports to cultivate newly developing ideas, ambitions, and teams while leveraging and extending existing institutional expertise, relationships, and infrastructure at UBC. 

As part of our objective to foster a community of practice for health scholars and students at UBC, Dr. Kim McGrail, Director of Research at UBC Health will deliver a webinar about Health Data Research Network (HDRN) Canada on June 24. 

The virtual presentation will provide an overview of HDRN Canada, how the network operates, and objectives for and progress on their work building the SPOR Canadian Data Platform. The SPOR platform and its data access support hub provide new supports to researchers who are interested in using routinely-collected data for multi-jurisdictional research. The presentation will be followed by a Q&A session. 

THURSDAY, JUNE 24, 2021
12:00 – 1:00 PM
ZOOM MEETING

REGISTER

Space is limited, so we encourage you to register soon. Online registration closes on Wednesday, June 23 at 12pm. After this time, please email ubchealth.admin@ubc.ca to register. 

ABOUT HDRN

Incorporated as a non-profit corporation in 2020, Health Data Research Network (HDRN) Canada connects individuals and organizations across the country to share expertise, identify opportunities for collaboration, and foster innovation in ways that respect public expectations and Indigenous data sovereignty. Access to multi-jurisdictional data allows researchers to address health challenges that cross boundaries, leading to advances that help develop innovative solutions and build Canada’s international leadership in the health field. For more information, visit HDRN Canada. 

ABOUT THE SPEAKER

Kim McGrail is a Professor in the School of Population and Public Health and the Centre for Health Services and Policy Research at UBC; Scientific Director of Population Data BC and the SPOR Canadian Data Platform; and Director of Research at UBC Health. 

Her research interests are quantitative policy evaluation, aging and the use and cost of health services, and the ethical and technical aspects of the development and operation of large linked data systems. Her research is conducted in collaboration with policy and decision makers, clinicians, and the public.

Kim is a founding member of the International Population Data Linkage Network and founding Deputy Editor of the International Journal of Population Data Science. She was the 2009-10 Commonwealth Fund Harkness Associate in Health Care Policy and Practice, a 2016 recipient of the Cortlandt JG Mackenzie Prize for Excellence in Teaching, and 2017 recipient of a UBC award for Excellence in Clinical or Applied Research. She holds a PhD in Health Care and Epidemiology from UBC, and a Master’s in Public Health from the University of Michigan.

As Director of Research for UBC Health, Kim works to initiate and support collaborations among academic and clinical faculty and other stakeholders on relevant translational health research issues, and in partnership with UBC academic leaders and stakeholders, engage them in aligning the use of health data in translational research and in the application of knowledge to health systems.

June 28: UBC Health Awards Celebration

UBC Health is hosting a virtual celebration of the 2019 and 2020 UBC Health Awards and Scholarship recipients.
 
The virtual celebration will include opening remarks by Dr. Dermot Kelleher, Vice-President, Health and awards presentations by Dr. Anne Martin-Matthews, Associate Vice-President, Health, and members of the UBC Health Senior Leadership Team.

View the list of award and scholarship recipients who will be recognized at this event.

MONDAY, JUNE 28, 2021
3:00 – 4:30 PM
ZOOM MEETING

REGISTER

Space is limited, so we encourage you to register soon. Online registration closes on Thursday, June 24 at 3 pm. After this date, please email ubchealth.admin@ubc.ca to register.

ABOUT THE AWARDS

The UBC Health Awards are offered annually by UBC Health to recognize individuals and teams who embody excellence in interprofessional collaboration, health education, and research and have made significant contributions to the advancement of health education and practice. 

July 12-14: 2021 Research Computing Bootcamp

UBC Advanced Research Computing (ARC) is hosting a 3-day Research Computing Bootcamp from Monday, July 12 to Wednesday, July 14 2021. This virtual program will explore introductory and intermediate topics in Linux, Cloud Computing, GPU Programming, and more. This Bootcamp is ideal for researchers interested in building knowledge and skills for computational research.

REGISTER
July 14: Health After 2020 Launch and Public Lecture

UBC Health is launching Health After 2020 with an inaugural public lecture.

LOOKING BACK AND MOVING FORWARD: SUPPORTING HEALTH AFTER 2020
WEDNESDAY, JULY 14, 2021
12:00 – 1:00 PM
ZOOM MEETING

REGISTER

Space is limited, so we encourage you to register soon. Online registration closes on Monday, July 12 at 12 pm. After this date, please email ubchealth.admin@ubc.ca to register.

ABOUT THE LECTURE

Great moments in history often spur equally great changes in society. We will likely look back on 2020 as one of these great moments. The COVID-19 pandemic put a spotlight on a number of existing societal issues, accelerated the pace of change in others, and created some new ones, too. For example, concerns about the quality and safety of long-term care services are not new, but they certainly became more apparent to a far larger number of people during 2020. The speed and starkness of changes such as this—but far beyond this as well—create an opportunity and motivation to reassess our understanding of health. Perhaps more importantly, it is an opportunity to reduce inequities in who has access to and who uses and benefits from the resources that promote health and wellbeing. The Health After 2020 series is UBC Health’s contribution to making sure we seize this opportunity.

ABOUT THE SPEAKERS 

Kim McGrail
Kim McGrail is Professor in the School of Population and Public Health and the Centre for Health Services and Policy Research at UBC; Scientific Director of Population Data BC and the SPOR Canadian Data Platform; and Director of Research at UBC Health. 

Her research interests are quantitative policy evaluation, aging and the use and cost of health services, and the ethical and technical aspects of the development and operation of large linked data systems. Her research is conducted in collaboration with policy and decision makers, clinicians, and the public. 

Kim is a founding member of the International Population Data Linkage Network and founding Deputy Editor of the International Journal of Population Data Science. She was the 2009-10 Commonwealth Fund Harkness Associate in Health Care Policy and Practice, a 2016 recipient of the Cortlandt JG Mackenzie Prize for Excellence in Teaching, and 2017 recipient of a UBC award for Excellence in Clinical or Applied Research. She holds a PhD in Health Care and Epidemiology from UBC, and a Master’s in Public Health from the University of Michigan. 

As Director of Research for UBC Health, Kim works to initiate and support collaborations among academic and clinical faculty and other stakeholders on relevant translational health research issues, and in partnership with UBC academic leaders and stakeholders, engage them in aligning the use of health data in translational research and in the application of knowledge to health systems.

Jeffrey Morgan

Jeffrey Morgan is a Vanier Scholar and PhD student in the School of Population and Public Health at UBC. He is affiliated with the BC Centre on Substance Use, Centre for Health Services and Policy Research, and Community-Based Research Centre. His research uses community-based and participatory approaches that meaningfully involve community members and patient partners at every step of the research process, particularly on projects that advance health equity for people who use substances and sexual minority people. Jeffrey’s PhD research seeks to validate and utilize health administrative data in the context of substance use in order to better understand our system of addiction care.

Arjumand Siddiqi
Arjumand Siddiqi is a social epidemiologist and Professor and Division Head of Epidemiology at the Dalla Lana School of Public Health, University of Toronto, where she holds the Canada Research Chair in Population Health Equity. She also holds cross appointments in Public Policy and Sociology at the University of Toronto, as well as an adjunct appointment at the Gillings School of Global Public Health, University of North Carolina – Chapel Hill. 

Her research centres on understanding why health inequalities are so pervasive and persistent, and what can be done about this, with an emphasis on the role of societal conditions (policy, politics, economy, and so on). In recent years, she has focused on (a) evaluating of the impact of specific social policies on population health and health inequalities, (b) examining the causes of contemporary trends in population health and health inequalities (e.g., the recent, unusual decline in life expectancy in the liberal welfare states; the widening of racial and socioeconomic health inequalities in many societies; the social distribution of the COVID-19 pandemic), and (c) reflections on concepts and methods used in health inequalities research. 

Arjumand also engages with governmental and non-governmental entities, including the Government of Ontario, the Government of Canada, and the World Health Organization.

Michael Stepner
Michael Stepner is an Assistant Professor in the Department of Economics at the University of Toronto. His research examines the relationship between health and economic inequality, with a focus on how public policy can improve the health and financial security of low-income populations. He also serves as the network leader for Health Trends and Inequalities research at the NBER Center for Aging and Health Research, and as a guest editor for the COVID-19 special issue for the Canadian Public Policy journal. Michael received his PhD from MIT in 2019, and his dissertation research was awarded the top dissertation award from the National Academy of Social Insurance.

July 15 & 23: Health Care Delivery at the Point-of-Care with 5G

This 2-part workshop series to generate new research proposals was developed by the ongoing UBC-Rogers partnership around 5G communications. To be considered for funding, researchers are required to attend both discovery workshops and submit a proposal for evaluation by a joint UBC-Rogers Steering Committee.

THURSDAY, JULY 15, 2021
10:00AM - 12:00PM PST
  • Brainstorming and challenge definition: This session will bring together Rogers teams and UBC researchers to explore what challenges exist in the healthcare space and narrow down sub-themes where 5G may help solve these challenges.

  • Pre-read: There will be a primer on the intended goals of the partnership and a 5G primer.

  • Action item: Formulate high level ideas around possible research projects independently or in collaboration with other UBC researchers.

FRIDAY, JULY 23, 2021
10:00AM - 12:00PM PST
  • Initial project ideas: Share your initial project ideas (short paragraph) with a smaller breakout group, solicit/provide feedback, and further refine your ideas. You will be able to connect with others to form a research team and to get feedback from UBC-Rogers Steering Committee.

  • Action item: Create and submit your research proposal.

For participation, please RSVP to marina.tischenko@ubc.ca by Friday, July 9.

July 20-21: Machine Learning in Health Summit
TUESDAY, JULY 20 - WEDNESDAY, JULY 21, 2021
6:00AM - 1:00PM PST

Join the Healthcare Machine Learning Community's annual gathering.

20 speakers will explore applications of Machine Learning from both the business and technical areas of expertise plus 3 bonus hands-on workshops. Bonus workshops take place July 20th and summit talks on July 21st.

Attendees will have opportunities to meet with both academic researchers and industral parties active in the healthcare sector in order to gain new perspectives from each other's scope of work.

Presentation abstracts, event agenda, and registration are available on the event website.

July 20-21: Everything You Aspired to Know About Machine Learning - But Were Afraid to Ask!
TUESDAY, JULY 20 - FRIDAY, JULY 21, 2021
10:30AM - 12:30PM PST

This workshop is the first in a series on Machine Learning. It's main focus is to present the languages of machine learning in an intuitive way. The philosophical thread that links these workshop sessions is to emphasize synthesis rather than prerequisites. In other words, the ultimate goal is accessibility without the weight of having to do math remediation or requiring a background in coding.

Participants are expected to commit to all 4 sessions of the workshop. 

Basic coding elements will be introduced while material is being presented. The main vehicle for computing will be the Jupyter notebooks which incorporate computer code, visualizations and descriptive text. The sessions will be interactive and presentation-light.

TOPICS
  • Introduction: The languages of machine learning, installing and using Jupyter notebooks

  • Calculus in one day: The basic concepts of calculus using a physical simulator

  • The puzzles of probability: How do we count event occurrence

  • Field laboratory: Measuring slopes — the fastest way down a mountain

VENUES AND TIMES
  • July 20th 10:30am – 12:00pm Zoom

  • July 21st 10:30am – 12:00pm Zoom

  • July 22nd 10:30am – 12:00pm Zoom

  • July 23rd 10:30am – 12:30pm Hands-On Workshop*

*Location: outdoors around UBC Vancouver Campus

REGISTER
July 21: Introduction to the Data Innovation Program for Academic Researchers
WEDNESDAY, JULY 21, 2021
1:00PM - 2:00PM PST

The Government of British Columbia, Ministry of Citizens' Services, in partnership with Population Data BC, recently launched the Data Innovation Program for academic researchers, allowing access to cross-sector data from multiple provincial ministries and organizations for the first time.

The Data Innovation Program (DI Program) is a data integration and analytics program for government analysts and academic researchers. While every BC ministry and broader public sector organization collects and manages its own data, the DI Program securely links and de-identifies cross sector data for a better understanding of BC's complex issues. The Program supports population-level analysis (not individual- or case-level analysis), unlocking the potential for new insights that can lead to better programs and services for British Columbians.

With over 20 years of experience in providing data access to Canadian researchers, PopData is a partner in the DI Program, providing services related to data linkage, project and data management, and a secure virtual research environment.

This webinar will provide an overview of the Program and partnership, outline the data available, the access process and end with a Q and A session.

ABOUT THE SPEAKERS

Brittany Decker is Director, Client Engagement, Digital Platforms and Data Division, Ministry of Citizens' Services, Government of British Columbia.

Kim McGrail is a Professor in the UBC School of Population and Public Health and Centre for Health Services and Policy Research, Director of Research for UBC Health, and Scientific Director of Population Data BC and Health Data Research Network Canada.

Her research interests are quantitative policy evaluation and all aspects of population data science. Kim is Deputy Editor of the International Journal of Population Data Science, the 2009-10 Commonwealth Fund Harkness Associate in Health Care Policy and Practice, 2016 recipient of the Cortlandt JG Mackenzie Prize for Excellence in Teaching, 2017 recipient of a UBC award for Excellence in Clinical or Applied Research, and in 2019-2020 participated as a member of the Canadian Institute for Advanced Research Task Force on AI4Health.

She holds a PhD in Health Care and Epidemiology from the University of British Columbia, and a Master’s in Public Health from the University of Michigan.

REGISTER
August 24: R/Medicine Virtual Conference

The R/Medicine conference and community promote the development and use of R based tools to improve clinical research and practice.

Check their page for updates on workshops, speakers and to submit an abstract.

October 5: Biomedical Imaging and Artificial Intelligence (BMIAI) Invited Lecture Series - Reading Race: AI Recognises Patient's Racial Identity in Medical Images

TUESDAY, OCTOBER 5, 2021
12:00PM

Join UBC's Biomedical Imaging & AI and Data Science & Health Research Clusters in welcoming Dr. Judy Gichoya for a virtual invited lecture. 

ABOUT THE SPEAKER

Dr. Judy Gichoya is a multidisciplinary researcher, trained as both an informatician and a clinically active radiologist. She is an assistant professor at Emory university, and works in Interventional Radiology and Informatics. She is seconded to the National Institutes of Health as a data scholar to help with the Open Data Science Platform (OSDP) component of the DSI Africa Initiative to “Harness Data Science for Health In Africa”. Her career focus is on validating machine learning models for health in real clinical settings, exploring explainability, fairness, and a specific focus on how algorithms fail. She has worked on the curation of datasets for the SIIM (Society for Imaging Informatics in Medicine) hackathon and ML committee. She volunteers on the ACR and RSNA machine learning committees to support the AI ecosystem to advance development and use of AI in medicine. 

Learn More

October 14: FDA - Transparency of AI/Machine Learning-Enabled Medical Devices Workshop
THURSDAY, OCTOBER 14, 2021
7:00AM - 12:30PM PST

The Food and Drug Administration (FDA) is announcing a virtual public workshop on transparency of Artificial Intelligence/Machine Learning (AI/ML)-enabled medical devices to patients, caregivers, and providers. The role of transparency that enhances safe and effective use of AI/ML-enabled medical devices will be discussed, with an emphasis on information sharing methods such as labeling. 

The purpose of the workshop is to 1) identify unique considerations in achieving transparency for users of AI/ML-enabled medical devices and ways in which transparency might enhance the safety and effectiveness of these devices; and 2) gather input from various stakeholders on the types of information that would be helpful for a manufacturer to include in the labeling of and public facing information of AI/ML-enabled medical devices, as well as other potential mechanisms for information sharing. 

Learn More

October 14: Biomedical Imaging and Artificial Intelligence (BMIAI) Fall Research Showcase

THURSDAY, OCTOBER 14, 2021
9:00AM - 11:00PM

Join BMIAI this Fall to discover the exciting research being conducted by their multi-disciplinary members.

The Research Showcase aims to expose participants to BMIAI's research activities and provide a platform for engagement and collaboration.

The Showcase will also feature the launch of BMIAI's new project repository. The project repository will be an online database of research questions where members, collaborators, and potential industry partners can submit their project ideas.  The objective of the repository is to increase collaborations and act as a matchmaking mechanism. If you would like to submit a research problem to the repository, you can do so here.

The day will include:

  • Lightning Talks by BMIAI members

  • Virtual video presentations exhibiting BMIAI members' work

  • Official launch of the BMIAI repository

Learn More

October 14: INOVAIT Regulation of AI in Healthcare
THURSDAY, OCTOBER 14, 2021
10:00AM - 11:00AM

In this lecture, Michaela will discuss the regulation of digital technologies and software as a medical device (SaMDs). In today's digital world, e-health interventions and software play a significant role in healthcare management and delivery. The regulation of these technologies differs significantly from traditional medical devices and requires a more streamlined regulatory oversight. This session will provide participants with a fundamental understanding of the standards and guidelines of regulations for SaMDs and AI-based medical technologies.

ABOUT THE SPEAKER

Michaela Shaw is a regulatory consultant with 15 years of experience within the medical device industry, leading a variety of start-up companies through the FDA, Health Canada and EU regulatory approval process. Michaela’s experience includes many noteworthy, product and device regulatory approvals in the area of medical imaging, cardiovascular and respiratory therapy, medical device software and point-of-care diagnostic devices. She is the founder of Shaw Quality Solutions, guiding clients through certification and management of ISO13485 and FDA compliant Quality Management Systems, and regulatory submissions for market approvals in US, Canada, Europe, Australia and Asia.

Register

November 17 & 18: Image-Guided Therapeutics and Diagnostics Symposium
WEDNESDAY, NOVEMBER 17 - THURSDAY, NOVEMBER 18, 2021
9:00AM - 12:30PM

Ryerson, Sunnybrook, and the Universities of British Columbia and Colorado invite you to Image-Guided Therapeutics and Diagnostics.

Building off the success of the IGT webinar series, Image-Guided Therapeutics and Diagnostics is a 2-day symposium that will bring together clinicians, researchers, students, and industry organizations who are interested in emerging diagnostic and therapeutic health technologies.

There will be invited talks on themes such as diagnostic imaging, artificial intelligence, and image-guided therapies for a multitude of applications. The symposium will provide an opportunity to network and identify opportunities for collaboration and partnership. The meeting will serve as a showcase for new innovations and products for industry partners.

ABOUT THE SPEAKERS

Dr. Purang Abolmaesumi is internationally recognized and has received numerous awards for his pioneering developments in medical image analysis and image-guided interventions. He carries out research in medical imaging, machine learning, and image-guided diagnosis and interventions. Artificial intelligence and machine learning techniques are applied to diagnosis in ultrasound, magnetic resonance imaging, digitized pathology slides and other tissue images.

Dr. Terry Peters' laboratory tackles problems related to Image-guided interventions. His lab is identifying brain pathologies through multi-spectral imaging and histology correlations and developing minimally-invasive heart surgery using ultrasound and augmented reality to repair structures in the beating heart! Other research aims to assist the safe delivery of anesthetic agents to critical regions such as the spine using Ultrasound and augmented reality, and the application of novel image processing approaches for prostate resection using the daVinci robot. All of these projects are supported by shared platforms of image segmentation, image registration, 3D-visualization, and instrument tracking.

Dr. Maria Drangova's research is focused on the development and evaluation of imaging techniques for the diagnosis and treatment guidance of cardiovascular diseases.  The scope of her research spans from basic developments of imaging techniques to their integration into therapeutic procedures, including device development.  Recent contributions from Dr. Drangova’s lab include a rapid technique for three dimensional micro computed tomography of the murine heart; the development of a remote catheter driver for delivering percutaneous, minimally invasive therapies from a location remote to the patient; she is also working on techniques for multidimensional motion correction in MRI.

Dr. Robin Shandas has a long history of translating engineering ideas into successful clinical products and techniques. He pioneered the Echo PIV technique, an opaque flow velocimetry technique for measuring details of cardiovascular blood flow through high frame rate ultrasound imaging coupled with contrast backscatter. In pediatric cardiology, he helped develop the idea that the large pulmonary arteries play a key role in maintaining right-ventricular pumping action (the RV-PA dual-ventricle) during pulmonary hypertension. In pediatric cardiac surgery, he co-developed novel methods to assist the failing Fontan. Over the last 10 years, he co-founded 8 companies in a variety of medtech areas including new shape memory polymers for cardiovascular and ophthalmic applications (EndoShape, ShapeTech, Shape Ophthalmics), Echo PIV for hemodynamic vascular profiling (Illumasonix), new surgical bed for hip arthroscopy (MITA), and new techniques to quantify esophageal inflammation (EnteroTrack).  Many of these companies have products in the clinic; one (MITA) was recently acquired by Stryker.  Dr. Shandas founded the first bioengineering department in Colorado and established the BS, MS, and PhD degrees in bioengineering.

Learn More

2022
January 12: Disaggregated Data Dialogue Series - Moving Forward on the Pan-Canadian Health Data Strategy
WEDNESDAY, JANUARY 12, 2022
12:00 – 1:00 PM
ZOOM MEETING

The COVID-19 pandemic sparked a number of commentaries and conversations about the need to strengthen our health data foundations in Canada. The federal government responded to this by announcing the intent to develop a Pan-Canadian Health Data Strategy. This talk will summarize the group’s work and current thinking about recommendations as well as invite university-based input into these ongoing conversations. The session will be led by Kim McGrail, Director of Research at UBC Health and member of the Pan-Canadian Health Data Strategy expert advisory group.

Register

January 20: AI in Med Lecture - Dr. Anne Martel

WEDNESDAY, JANUARY 12, 2022
12:00 – 1:00 PM
ZOOM MEETING

ABSTRACT

The introduction of scanners that are capable of digitizing microscopic slides at high magnification has led to an explosion of interest in computational pathology in general and deep learning applied to whole slide images (WSIs) in particular. In my lab at Sunnybrook, we are developing AI models that can detect cancer, automatically segment regions of interest, and learn predictive and prognostic models that can be used to guide treatment decisions. In this talk I will outline some of the unique challenges of working with these extremely large WSIs and discuss some of the approaches that we have developed to overcome the problems of sparse annotations and weak, noisy labels, including self-supervision and multiple instance learning. I will also outline some of the challenges in deploying AI algorithms to the clinic.

SPEAKER

Anne Martel is a Professor in Medical Biophysics at the University of Toronto, a Senior Scientist at Sunnybrook Research Institute, and a Vector Faculty Affiliate. Her research program is focused on medical image and digital pathology analysis, particularly on applications of machine learning for segmentation, diagnosis, and prediction/prognosis. In 2006 she co-founded Pathcore, a software company developing complete workflow solutions for digital pathology. Dr Martel is an active member of the medical image analysis community and is a fellow of the MICCAI Society which represents engineers and computer scientists working in this field. She has served as board member of MICCAI and is currently on the editorial board of Medical Image Analysis.

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January 27: Correlation and Linear Regression (UBC Statistics & Graduate Pathways to Success Webinar Series)

This webinar series provides an overview of foundational statistical concepts using examples of various data structures. They will discuss types of study designs, methods, models and appropriate application of statistical tests along with interpretations of the results obtained from different statistical tools. The aim is to equip the attendees with a deeper understanding of the key concepts of statistical methodology, rather than solving specific project problems or providing hands-on guidance.

Each webinar is a self-contained introduction to different statistical concepts, but as topics become increasingly complex with each consecutive webinar, some aspects will be built on concepts taught in the previous sessions. 

Previous Workshops

THURSDAY, JANUARY 27, 2022
1:00 – 3:00 PM

This is the 4th workshop in a 6-part series focused on the foundations of statistics.

Understanding relationships is a key part of the scientific inquiry process. You will learn how to describe relationships between two numerical quantities through correlation measures and simple linear regression models. This will also be extended to multiple linear regression for including additional predictor variables.

Specific topics include:

  • Correlation vs Causation

  • Interpretation of Regression Model Coefficients

  • Assessing the "Fit" of a Model

  • Model Selection

*Registration opens on the Monday, a week prior to the event.

Register

January 28: Data Privacy Day 2022 Discussion
FRIDAY, JANUARY 28, 2022
11:00 AM – 12:00 PM
ZOOM MEETING

Did you know that recent changes to British Columbia's Freedom of Information and Protection of Privacy Act could greatly affect how you learn and work at UBC? Come join the Privacy Matters @ UBC team as to celebrate Data Privacy Day on Jan 28 with a very important discussion about changes to Data Residency Restrictions in British Columbia.The event will discuss: How will the removal of certain data residency restriction affect UBC from a security, financial, and procurement perspective? How will these changes affect the use of cloud-based technology and digital tools for faculty, staff, and students? All UBC faculty and staff are encouraged to register and join the conversation.

Register

February 17: Logistic and Poisson Regression (UBC Statistics & Graduate Pathways to Success Webinar Series)

This webinar series provides an overview of foundational statistical concepts using examples of various data structures. They will discuss types of study designs, methods, models and appropriate application of statistical tests along with interpretations of the results obtained from different statistical tools. The aim is to equip the attendees with a deeper understanding of the key concepts of statistical methodology, rather than solving specific project problems or providing hands-on guidance.

Each webinar is a self-contained introduction to different statistical concepts, but as topics become increasingly complex with each consecutive webinar, some aspects will be built on concepts taught in the previous sessions. 

Previous Workshops

THURSDAY, FEBRUARY 17, 2022
1:00 – 3:00 PM

This is the 5th workshop in a 6-part series focused on the foundations of statistics.

Learn about generalized linear models (GLM) for categorical and count outcomes. Necessary for understanding and using these models, the following will be covered:

  • Interpretation of Odds, Odds Rations and Rate Ratios

  • Variable "Exposure" Times

  • Overdispersion

  • Negative Binomial Regression

  • Considerations for Likert Scale Outcomes

  • Handling Excess Ratios

*Registration opens on the Monday, a week prior to the event.

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February 23: Ethics in Technology

WEDNESDAY, FEBRUARY 23, 2022
12:00 – 1:15 PM
ZOOM MEETING

Ethics in Technology is the second installation of Ethics for UBC, a five-part speaker series that will explore the current landscape of ethics scholarship and education across the Vancouver and Okanagan campuses of our university.

In attending this interactive 75-min panel discussion, you will have the opportunity to learn about the current ethics-related endeavours taking place at UBC, pressing ethical issues that exist across a wide range of disciplines, and the ways in which you can become more involved.

This panel discussion will focus on ethics across a variety of disciplines that involve technology, from engineering and architecture to neuroscience and nursing.

ABOUT THE SPEAKERS

Welcome byGail Murphy, PhD; Professor, Computer Science; Vice President – Research and Innovation, University of British Columbia

Moderated byAri Rotenberg, BA; MSc Candidate, Experimental Medicine; Neuroethics Canada, University of British Columbia 

Panelists

Shahria Alam, PhD; Professor, School of Engineering; Director, Green Construction Research Training Centre, University of British Columbia – Okanagan Campus

Fionn Byrne, MLA; Assistant Professor, School of Architecture and Landscape Architecture, University of British Columbia

Julie Robillard, PhD; Assistant Professor of Neurology, Faculty of Medicine; Faculty, Neuroethics Canada, University of British Columbia

Patricia Rodney, PhD; Associate Professor Emerita, School of Nursing, University of British Columbia

March 17: Mixed Effects Models (UBC Statistics & Graduate Pathways to Success Webinar Series)

This webinar series provides an overview of foundational statistical concepts using examples of various data structures. They will discuss types of study designs, methods, models and appropriate application of statistical tests along with interpretations of the results obtained from different statistical tools. The aim is to equip the attendees with a deeper understanding of the key concepts of statistical methodology, rather than solving specific project problems or providing hands-on guidance.

Each webinar is a self-contained introduction to different statistical concepts, but as topics become increasingly complex with each consecutive webinar, some aspects will be built on concepts taught in the previous sessions. 

Previous Workshops

THURSDAY, MARCH 17, 2022
1:00 – 3:00 PM

This is the 6th and final workshop in a 6-part series focused on the foundations of statistics.

This webinar is critical for understanding when linear regression models aren’t applicable and how to model dependent data. Topics that will be covered are:

  • Consequences of Ignoring Dependence (Increased Risk of False Conclusions)

  • Repeated Measures and Other Examples of Dependent Data

  • Variance Components

  • Interpretation in the Linear and Generalized Linear Mixed Effects Context

*Registration opens on the Monday, a week prior to the event.

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June 27-30: Bootcamp on Systems-Data Science - Practical Combining Data Science and Systems Science for Health
JUNE 27-30, 2022
ONLINE & IN-PERSON OPTIONS

The Bootcamp on Systems-Data Science presents industrial-strength methods combining the power of machine learning, big data and dynamic modeling to improve health decision making. In addition to more than a dozen previous health uses, these methods have been at the heart of regular reporting by the instructor to inform health system decision-making in SK (daily), for each Canadian province (via PHAC), and for First Nations reserves across 9 Canadian provinces (via FNIHB).

This bootcamp characterizes these techniques, how to use them effectively, provides overviews of how they work, describes their use with other approaches, case studies & example implementations.  The event offers a particular focus on how these methods can be used with “big data” offering high volume, velocity, variety, and veracity, with examples showing the particular ways that they can regularly reground models with data from wastewater sampling, social media, smartphones/wearables, and search data in addition to traditional epidemiological data.

In greater detail, systems science and data science are two rapidly developing areas of computational science that have been demonstrated to offer tremendous capacity for informing health understanding, and which are applied by a growing number of projects in health and health care.  While each of these approaches taps the power of computational models, they have traditionally largely been pursued in isolation from each other.  Such fragmentation is particularly unfortunate, because the techniques are not merely highly compatible -- for example, in each using computational or informatics mechanisms to provide temporally and locationally fine grained longitudinal understanding across multiple generative pathways -- but synergistic, with each tradition opening strong opportunities for empowering the other, and with the combination of both yielding opportunities for insight and improved decision making far beyond the sum of what each can bring in isolation.  We present here a proven set of Systems-Data Science methods that achieve this “whole greater than the sum of its parts” and that allow each approach to better fulfill its full potential. 

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August 23-26: R/Medicine Conference
AUGUST 23-26, 2022
ONLINE

The goal of the R/Medicine conference and community is to promote the development and use of R-based tools to improve clinical research and practice.

R is a free and open-source programming language for reproducible statistical computing, data visualization, and application development. R is the gold standard for reproducible research in academia and industry and has powerful capabilities to create highly-customizable interactive analytic dashboards, as well as predictive models that employ machine learning, deep learning, and artificial intelligence.

R/Medicine was formed through a collaborative effort of the R Consortium with academic and industry partners including Yale University, Stanford University, the Mayo Clinic, and RStudio, PBC. Presentations at R/Medicine conferences showcase how the R ecosystem is currently leveraged in medical applications including clinical trial design and analysis, personalized medicine, the development of machine learning models using patient records and clinical laboratory data, and reproducible research.

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August 22-27: Agent-Based & Hybrid Modeling Bootcamp & Incubator for Health & Health Care - Conceptualization, Formulation, Implementation for Insight
AUGUST 22-27, 2022
HYBRID (ONLINE & IN-PERSON OPTIONS FOR BOOTCAMP; IN-PERSON ATTENDANCE REQUIRED FOR INCUBATOR)

The Agent-Based and Hybrid Modeling Bootcamp & Incubator for Health Researchers is an intensive, hands-on tutorial and dynamic model incubator that seeks to provide systematic, practical and technically detailed guidance in conceptualizing, designing and implementing agent-based and hybrid system science modeling for health and health care, using familiar language and concepts.  This year’s bootcamp & incubator will focus on agent-based modeling, but with a particular emphasis on insightful, practical and performant hybrids with System Dynamics modeling and discrete event modeling, such as for health care service delivery and patient flow.  

To help ease participants in overcoming the learning curve in applying the techniques taught herein to domains of individual interest, those registering for the “incubator” side of the event will further leverage the extensive experience of the instructor, other expert modelers, and teaching assistants (TAs), who will provide ongoing advice, guidance, tips and close hands-on assistance as these participants and their partnered TAs work to build, explore, and debug the start of their own models addressing participant research interests. Participants interested in taking their initial models far further can elect to remain for the full-scale model incubator/hackathon the subsequent week, in which the instructor and teams of TAs will partner with attendees to deliver more evolved models capable of contributing substantive health insights. Attendance to the incubator portion of this event is constrained by the availability of teaching assistants -- please reserve early to ensure an incubator spot.

Using lectures and guided exercises, this bootcamp will introduce a broad set of topics in designing & building agent-based and hybrid modeling, offer optional material for those seeking additional depth of coverage, and emphasize the complementary insights when agent-based and hybrid modeling is combined with traditional health sciences approaches. Course material is drawn from the instructor’s semester-long interdisciplinary courses at MIT and the University of Saskatchewan, as well as previous bootcamps, including those hosted at UCLA, University of New South Wales, NCSU/UNC, Flinders University, Deakin University, the Sax Institute, and beyond.  

Participants will be provided with over 50 example models drawn from across diverse spheres of health and health care.  Health & health care modeling case studies for chronic disease, communicable illnesses, health service delivery, and environmentally driven infectious diseases from around the world will support participants in helping to conceptualize fruitful model designs, scopes and the form of effective modeling projects.  Such models will showcase Agent-Based, System Dynamics and Discrete Event modeling, including -- but not limited to -- use of agents some of whose states are driven by System Dynamics stocks & flows, agent-based epidemiological models linked to discrete event models capturing patient care pathways and patient flow, highly performant hybrid models in which System Dynamics is used for low-risk populations and in which agents are individuated at a certain point in risk progression or where interacting agents drive flow rates, multi-scale models, and case studies combining all three types of modeling.

The optional final day of the bootcamp will give participants the opportunity to brainstorm with the instructor and teaching assistants concerning ideas for modeling projects, and to discuss concrete design and implementation strategies for such projects.

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August 29 - September 2: Agent-Based & Hybrid Modeling for Health & Health Care Hackathon
AUGUST 29 - SEPTEMBER 2, 2022
IN-PERSON

This hackathon will provide participant wrap-around assistance in conceptualizing, building, exploring, and debugging models addressing their particular research or practitioner interests and vision.  To do so, this event will leverage the extensive experience of the instructor and teams of teaching assistants, who will provide ongoing advice, guidance, tips and hands-on assistance to attendees, allowing delivery of more evolved models capable of contributing substantive health insights.  Attendees for this event can either attend this hackathon as a stand-alone event or stay on from the bootcamp & incubator the previous week (thereby building on their learning from that event and continuing on any model substantively started in the incubator portion of that event).  

Attendance to the hackathon is constrained by the availability of TA teams -- please reserve early to ensure a spot.

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August 29: CAIDA Seminar - Differentially Private Fine-Tuning of Language Models

AUGUST 29, 2022
11:00AM - 12:00PM
UBC VANCOUVER CAMPUS, ICCS X836
ABSTRACT

We give simpler, sparser, and faster algorithms for differentially private fine-tuning of large-scale pre-trained language models, which achieve the state-of-the-art privacy versus utility tradeoffs on many standard NLP tasks. We propose a meta-framework for this problem, inspired by the recent success of highly parameter-efficient methods for fine-tuning. Our experiments show that differentially private adaptations of these approaches outperform previous private algorithms in three important dimensions: utility, privacy, and the computational and memory cost of private training. On many commonly studied datasets, the utility of private models approaches that of non-private models. For example, on the MNLI dataset we achieve an accuracy of 87.8% using RoBERTa-Large and 83.5% using RoBERTa-Base with a privacy budget of ϵ=6.7. In comparison, absent privacy constraints, RoBERTa-Large achieves an accuracy of 90.2%. Our findings are similar for natural language generation tasks. Privately fine-tuning with DART, GPT-2-Small, GPT-2-Medium, GPT-2-Large, and GPT-2-XL achieve BLEU scores of 38.5, 42.0, 43.1, and 43.8 respectively (privacy budget of ϵ=6.8,δ= 1e-5) whereas the non-private baseline is 48.1. All our experiments suggest that larger models are better suited for private fine-tuning: while they are well known to achieve superior accuracy non-privately, we find that they also better maintain their accuracy when privacy is introduced. No knowledge of differential privacy will be assumed. Based on joint work with Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin A. Inan, Janardhan Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, and Huishuai Zhang. Paper appeared in ICLR 2022, and available on arXiv (https://arxiv.org/abs/2110.06500).

ABOUT THE SPEAKER

Dr. Gautam Kamath is an Assistant Professor at the David R. Cheriton School of Computer Science at the University of Waterloo. He has a B.S. in Computer Science and Electrical and Computer Engineering from Cornell University, and an M.S. and Ph.D. in Computer Science from the Massachusetts Institute of Technology, where he was advised by Constantinos Daskalakis. His research interests lie in methods for statistics and machine learning, with a focus on challenges which arise in modern data analysis, including data privacy and robustness. He was a Microsoft Research Fellow, as a part of the SimonsBerkeley Research Fellowship Program at the Simons Institute for the Theory of Computing. He is recipient of an NSERC Discovery Accelerator Supplement, and was awarded the Best Student Presentation Award at the ACM Symposium on Theory of Computing in 2012.

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