Matthias Goerges

Associate Professor

Research Interests

Digital health
predictive analytics
decision support systems
Critical Care Medicine
Biomedical Technologies
Health Care Technologies
Human Computer Interaction and Design
Medical informatics
Software Development
patient-oriented research
Data sharing / open data

Relevant Thesis-Based Degree Programs

Affiliations to Research Centres, Institutes & Clusters

Research Options

I am interested in and conduct interdisciplinary research.


Matthias Görges is a Principal Investigator at the Research Institute, BC Children’s Hospital, where he co-leads the Clinical & Community Data, Analytics & Informatics group. He is a biomedical engineer with extensive clinical research experience, and an Associate Professor (Partner) in the Anesthesiology, Pharmacology & Therapeutics department at the University of British Columbia. As part of an inter-disciplinary team of engineers, computer scientists, and health care providers, he is involved in a wide range of projects focusing on the development and application of new technologies in the pediatric anesthesia and intensive care setting. His research interests are patient monitoring alarms, medical displays, decision support systems, mobile health applications, and data integration/communication platforms. Matthias’ goal is to extract clinically-useful information from vital signs and other clinical data, and to transform these data into information for better, more timely, and more efficient decision-making by clinicians.

Research Methodology

Predictive analytics
mHealth / mobile app development
participatory design
System engineering
Usability testing
Statistical modeling
Decision support
Patient-Oriented Research


Master's students
Doctoral students
Postdoctoral Fellows

The introduction of information technology in medicine has enabled a transformational change in recent decades. The coronavirus pandemic further accelerated the introduction of virtual care and digital health solutions. Thus, most of my work focuses on designing, implementing, and evaluating ways that leverage technology to improve patient-relevant outcomes.

Clinical context is essential, as understanding the real-world setting where technical innovations are applied is crucial in any engineering discipline. I collaborate with medical experts, including nurses and physicians across several disciplines, engineers, data scientists, and patients and their families, to solve real-world problems. I believe it is essential to appreciate a) that technology supports and enables people, b) we need to integrate data from a wide variety of sources to generate meaningful information to guide decision-making, c) good usability is vital to workflow, and d) high levels of situational awareness are required to ensure patient safety. 

My research program focuses on two key objectives:

  1. Digital health platforms: Develop a research data integration and exchange platform that leverages data from multiple sources, including patient-generated health data and patient-reported outcomes. It will enable (future) linking against electronic medical record data.
  2. Applications for predictive analytics: Design and implement outcome prediction pipelines that integrate and analyze clinical, patient-provided, and physiological data and create risk stratification models using statistical and machine learning techniques. This is primarily focusing on pediatric anesthesia and pediatric critical care.

Previously, I also worked on a) data displays for clinical decision support, b) vital signs collection infrastructure, and c) closed-loop control of anesthesia.

I consider trainees with biomedical engineering or clinical informatics backgrounds, as my program focuses on predictive analytics and digital health applications in Biomedical Engineering. I occasionally recruit trainees in Experimental Medicine for digital health research projects. Pharmacology is too far from my research interests and core training; therefore, I don't recruit Pharmacology students

Next, it is helpful for you to outline which projects you are interested in and why you are an excellent fit for my program. Finally, with a CV, it is easier for me to assess your suitability as a candidate, so please include this (and, ideally, a transcript and, if applicable, English test scores) with your application.

I support experiential learning experiences, such as internships and work placements, for my graduate students and Postdocs.
I am open to hosting Visiting International Research Students (non-degree, up to 12 months).
I am interested in hiring Co-op students for research placements.
I am interested in supervising students to conduct interdisciplinary research.

Complete these steps before you reach out to a faculty member!

Check requirements
  • Familiarize yourself with program requirements. You want to learn as much as possible from the information available to you before you reach out to a faculty member. Be sure to visit the graduate degree program listing and program-specific websites.
  • Check whether the program requires you to seek commitment from a supervisor prior to submitting an application. For some programs this is an essential step while others match successful applicants with faculty members within the first year of study. This is either indicated in the program profile under "Admission Information & Requirements" - "Prepare Application" - "Supervision" or on the program website.
Focus your search
  • Identify specific faculty members who are conducting research in your specific area of interest.
  • Establish that your research interests align with the faculty member’s research interests.
    • Read up on the faculty members in the program and the research being conducted in the department.
    • Familiarize yourself with their work, read their recent publications and past theses/dissertations that they supervised. Be certain that their research is indeed what you are hoping to study.
Make a good impression
  • Compose an error-free and grammatically correct email addressed to your specifically targeted faculty member, and remember to use their correct titles.
    • Do not send non-specific, mass emails to everyone in the department hoping for a match.
    • Address the faculty members by name. Your contact should be genuine rather than generic.
  • Include a brief outline of your academic background, why you are interested in working with the faculty member, and what experience you could bring to the department. The supervision enquiry form guides you with targeted questions. Ensure to craft compelling answers to these questions.
  • Highlight your achievements and why you are a top student. Faculty members receive dozens of requests from prospective students and you may have less than 30 seconds to pique someone’s interest.
  • Demonstrate that you are familiar with their research:
    • Convey the specific ways you are a good fit for the program.
    • Convey the specific ways the program/lab/faculty member is a good fit for the research you are interested in/already conducting.
  • Be enthusiastic, but don’t overdo it.
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