Keywords
Fields of Research (FoR)
Cardiology (incl. cardiovascular diseases), Biomedical engineering, Bio-fluids, Machine learningSEO tags
Biography
Dr. Susann Beier is a renowned researcher in the field of biomedical engineering, specialising in cardiovascular health and machine learning. Her outstanding contributions to the area are evidenced by her prestigious awards, including the International Cardiovascular Innovations Award and the National Heart Foundation Research Fellowship in New Zealand. As a Fellow of the Cardiovascular Society of Australia and New Zealand, Dr. Beier has been...view more
Dr. Susann Beier is a renowned researcher in the field of biomedical engineering, specialising in cardiovascular health and machine learning. Her outstanding contributions to the area are evidenced by her prestigious awards, including the International Cardiovascular Innovations Award and the National Heart Foundation Research Fellowship in New Zealand. As a Fellow of the Cardiovascular Society of Australia and New Zealand, Dr. Beier has been recognised as a leading expert in cardiovascular health and has made significant strides in advancing the field.
Dr. Beier's research focuses on risk assessment and prevention in cardiovascular health through medical image analysis and advanced computational biofluids modelling using high-performance computing. Her work is fundamental and applied, strongly emphasising developing innovative solutions that address cardiovascular health challenges.
Through her leadership as the head of the Sydney Vascular Modelling Group (SVMG), Dr Beier has spearheaded groundbreaking research projects that leverage the latest advances in machine learning and AI to improve cardiovascular health outcomes. The group's cutting-edge research can revolutionise the biomedical and bioengineering field.
With over 50 peer-reviewed research outputs, Dr. Beier's work has been widely recognised and has significantly impacted the field. As the Associate Editor of Biomedical Engineering Online, she continues contributing to the scientific community by publishing new research and mentoring the next generation of researchers.
As a result, Dr Beier's research presents exciting opportunities for PhD projects that will allow students to contribute to the cutting-edge work of the Sydney Vascular Modelling Group and advance the field of biomedical and bioengineering. By combining expertise in machine learning, AI, and biomedical engineering, students can make a meaningful impact on preventing and treating heart attacks and other cardiovascular conditions.
PHD PROJECTS AVAILABLE.
My Grants
- NHF Vanguard $150,000, 2023
- NHMRC Ideas, $490,000, 2022
- NSW Capacity Building, $485,000, 2022
- NHMRC Idea $593,000, 2021
- NHF Vanguard $150,000, 2020
- RIS 3D soft printing $250,000, 2019
- Auckland Medical Research Foundation (AMRF) NZD $153,000, 2017
- Auckland Academic Health Alliance (AAHA) NZD $100,000, 2016
- Cardiovascular Research Innovations Grant by the Cardiovascular Society of Australia and New Zealand $35,000, 2016
My Qualifications
- BE (Hon) Mechanical Engineering
- ME Chemical and Materials Engineering
- PhD Biomedical Sciences
My Awards
- Eng Future Women Leaders Conference Award (Monash University, University of Melbourne and UNSW), 2019
- The Australian Academy of Sciences Travel Award for ECR, 2018
- Heart Foundation Fellowship, 2017
- Visiting Fellow, Stanford University, 2017
- Cardiovascular Research Innovations Award by the Cardiovascular Society of Australia and New Zealand, 2016
- Auckland Charitable Heart Trust, Research Fellowship, 2015
- Emerging Research of the Year Award, 2015
- Emerging Research of the Year Award, 2013
- Laval University Travel Award, 2010
My Research Activities
Susann heads the Sydney Vascular Modelling Group SVMG, which drives important engineering innovations in cardiovascular medicine (see outputs).
See the Coronary Atlas website and the Sydney Vascular Modelling Group's page for more info.
Speaking
- Australian Bifurcation Club ABC, Sydney, Keynote 2020, 2021, 2023
- European Bifurcation Club EBC, Sydney, Keynote annually since 2017
- IEEE Engineering Medicine and Biology Society EMBS 2019
- Invited Chair, European Bifurcation Club EBC, Brussel, 2018
- European Bifurcation Club EBC, Porto, Portugal, 2017
- European Bifurcation Club EBC, Rotterdam, Netherlands, Keynote, 2016
- Research Bazaar ResBaz, Auckland, New Zealand, Keynote, 2016
- Annual Meeting of the Cardiovascular Society CSANZ, Auckland, New Zealand, Keynote, 2015
- MICCAI CVII-STENT, presentation, 2015
- European Bifurcation Club EBC, presentation, 2015
My Research Supervision
Supervision keywords
Areas of supervision
-
Machine learning and AI in cardiovascular health
-
Immersive technologies applied to cardiovascular health
-
Stent design optimisation
-
Big data image analysis for personalised preventive cardiovascular medicine
-
Super-computing for automated vascular simulations assisting clinical surgery
-
Real-life surgery with virtual reality
-
Imaging of cell behaviour under flow conditions in artery replicas
-
Fabrication of realistic artery replicas using advanced 3D printing
-
CFD study of diseased arteries to assist patient treatment
-
Micro- and Biofluidics
My Teaching
MECH9650 Micro- and Biofluidics - see this link for our student-co-developed electronic and interactive textbook
GSOE8920 Project Management
Location
Level 4, Room 401D
UNSW, Kensington Campus
Sydney NSW 2052
AUSTRALIA
Map reference (Google map)
Publications
ORCID as entered in ROS
https://orcid.org/0000-0002-9815-108X
Research Activities
Enhance the next generation of immersive technologies for medical surgeries. Learn how imaging, visualisation and personalised simulations can be used to assist with difficult surgeries, ranging from the spine to heart atrial fibrillation intervention, all with 3D visualisation in real time, so 4D.
Research project seeking students: Stents are meshed wired scaffolds implanted into narrowed arteries to prevent heart attacks and strokes. They still fail in 1 in 10 patients besides being the most common treatment for the largest cause of death world-wide.
The aim of this work is to generate CAD models from micro-CT images of stented patient replicas. The replicas represent the anatomical/geometric distribution found within a large population. The CAD models will be used to generate CFD simulation of the blood flow, revealing their effectiveness for that patient…
Stents are meshed wired scaffolds implanted into narrowed arteries to prevent heart attacks and strokes. They still fail in 1 in 10 patients besides being the most common treatment for the largest cause of death world-wide.
The aim of our work is to expand a number of numerical CFD simulations to generate input for a developed multi-object algorithm. The optimum design trade offs for modern stents can then be determined through several iterations of solutions.
The specific outcome are new guidelines for clinicians to be implemented in practice,…
Research Project seeking students: Cardiovascular disease is the single largest killer in the world, causing heart attacks and strokes. Experimental investigation of underlying principals are key in combating this epidemic, however individual considerations are still completely missing.
We are continuously expanding the Coronary Atlas, which is a virtual map of arterial shape and blood flow. Using in-house build tools to run bash programmed batch processes on the National Computing Infrastructure we can fast process hundreds of medical CT images at the time. These are then…
Cardiovascular disease is the single largest killer in the world, causing heart attacks and strokes. Experimental investigation of underlying principals are key in combating this epidemic, however individual considerations are still completely missing.
The aim of this work is to develop accurate machine learning neural networks to identify links between a large set of demographic, arterial shape and flow data with clinical risk. This will help to identify biomarkers which can be deployed in clinical practice for early risk detection.
Available data will be…
Videos
