Events

Upcoming events at Western Sydney University are listed below.

• Suggest a new event

• Oct 20
  Research Hour

  Informal session for researchers to connect with research support staff from ITDS/Library/Research Services/Intersect; share ideas and ask questions.

  Information sessions; Online Events
  Western Sydney University researchers
  Informal session for researchers to connect with research support staff from ITDS/Library/Research Services/Intersect; share ideas and ask questions.

  Researchers from across Western are invited to join us for ‘Research Hour’; hosted by ITDS, Research Services, Intersect and the Library - an informal, drop-in, Q&A session. If you have any questions about any aspect of your research project, plans, or implementation then Research Hour is the place for you. We have a range of experts on hand from across the University to discuss any queries you might have, help you problem solve, or point you to resources and services that could be of benefit to you as you carry out your research. Incorporating ‘Hacky Hour’: swap notes, get help, learn techniques in programming and data science, code, digital tools, HPC etc. Providing assistance across a range of research related topics (e.g.: managing your online researcher profile, strategic publishing, Open Access, metrics and impact, data management plan, research data storage, equipment and facilities). No question is too big or too small – we want to hear from you, and to make sure you have all the support you need to carry out your research successfully. Research Hour is open to Researchers from any discipline and at any level of their career… everyone is welcome. This is a participatory discussion session, not a presentation – come along prepared to engage!

  Wed, 20 Oct 2021 12:00:00 +1100
• Oct 21
  Things that Matter: Strengths, Struggles and Settlement Strategies of Culturally and Linguistically Diverse (CALD) and Vulnerable groups -The what, why and how?

  The School of Psychology invites you to attend our Research Forum - Things that Matter.

  academic events; Conferences and seminars; Information sessions; Social events; Online Events
  All Welcome
  The School of Psychology invites you to attend our Research Forum - Things that Matter.

  Dear Colleagues, The School of Psychology would like to invite you to attend the Research Forum - Things that Matter: Strengths, Struggles and Settlement Strategies of Culturally and Linguistically Diverse (CALD) and Vulnerable groups -The what, why and how? We have some exciting international and local guest speakers attending. See attached Flyer, program and bios of speakers for more information. A summary of the details are: Date: Friday 21 October 2021 Time: 16:00-18:00pm Location: zoom link on flyer attached Please feel free to distribute amongst your friends, colleagues and students. Join Zoom Meeting https://uws.zoom.us/j/89111647408?pwd=M0h3MUNkS2JPTllXRzBtS3dqTnlRUT09 Meeting ID: 891 1164 7408 Password: 921784

  Thu, 21 Oct 2021 16:00:00 +1100
• Oct 22
  Intersect Online Training: Introduction to Research Data Management at Western Sydney: Online

  This workshop is ideal for researchers who want to know how research data management can support project success.

  Training and skill upgrade; Online Events
  This workshop is ideal for researchers who want to know how research data management can support project success.

  Why do this course? It is increasingly acknowledged that publication and re-usability of research data brings great benefits to researchers, institutions, and the scientific community at large. Therefore the management of your valuable research data becomes an important task. In fact, WSU’s Research Data Management Policy requires all researchers to have a data management plan (DMP) in place at the beginning of their research project. This workshop is ideal for researchers who want to know how research data management can support project success and are interested in research data management services and support available at their institution. We will step you through the process of creating a comprehensive DMP within our Researcher Dashboard, and along the way we will discuss: - How to manage research data according to legal, statutory, ethical, funding body and university requirements. - Approaches to planning, collecting, organising, managing, storing, backing up, preserving, and sharing your data. - Services supporting research data at your institution. Co-presented by: Library, Intersect, ITDS.

  Fri, 22 Oct 2021 09:30:00 +1100
• Oct 27
  Intersect Online Training: Surveying with Qualtrics

  This course introduces the technical components of Qualtrics from building a survey to analysing the results.

  Training and skill upgrade; Online Events
  This course introduces the technical components of Qualtrics from building a survey to analysing the results.

  Why do this course? Needing to collect data from people in a structured and intuitive way? Have you thought about using Qualtrics? Qualtrics in a powerful cloud-based survey tool, ideal for social scientists from all disciplines. This course will introduce the technical components of the whole research workflow from building a survey to analysing the results using Qualtrics. We will discover the numerous design elements available in order to get the most useful results and make life as easy as can be for your respondents. You’ll learn to: - Format a sample survey using the Qualtrics online platform - Configure the survey using a range of design features to improve user experience - Decide which distribution channel is right for your needs - Understand the available data analysis and export options in Qualtrics.

  Wed, 27 Oct 2021 09:30:00 +1100
• Oct 27
  School of Law Research Seminar

  The seminar will consider decolonising the curriculum, and the understanding and narration of race, text, and identity in education.

  Conferences and seminars; Online Events
  The seminar will consider decolonising the curriculum, and the understanding and narration of race, text, and identity in education.

  The School of Law Seminar presented by our guest speaker, Dr Lindiwe Maqutu, Academic Leader in the School of Law, University of Kwazulu-Natal, South Africa. Dr Maqutu will be joined by her colleague, Dr Freddy Mnyongani for the discussion. This seminar will consider decolonising curriculum – with a focus on the ways in which “whitely attitudes” distort both the understanding and the narration of race, text, and identity in education. Attached is a journal article by our speaker Dr Maqutu, on which the seminar will be based. The seminar will no doubt provide interesting insights for to consider and reflect upon as we continue our initiatives to Indigenise and diversify the curriculum at Western Sydney University. Zoom Meeting ID: 869 7157 5610 Password: 597255

  Wed, 27 Oct 2021 14:45:00 +1100
• Oct 28
  Sojourners or Settlers? Early Chinese Migrants to Australia: A Case Study of Tasmania

  This talk is a case study of Tasmania based on an ARC research project that attempts to research into several questions concerning early Chinese migra.

  Conferences and seminars; Online Events
  Staff, students, public
  This talk is a case study of Tasmania based on an ARC research project that attempts to research into several questions concerning early Chinese migra.

  This talk is a case study of Tasmania based on an ARC research project that attempts to research into several questions concerning early Chinese migrants to Australia. The overriding research problem is why early Chinese migrants are either assumed or argued as sojourners, in contrast to British migrant who were considered settlers. I argue in this talk that early Chinese migration to Australia might come as sojourners, but willing to be settlers, and ended up as a mixture of both. The talk ends with one theoretical postulation that early Chinese migrants to the little island Tasmania were transnationals, hybrids and ‘global citizens” more than a hundred years ago. Once migrated early Chinese migrants were less “Chinese” but could not be like “white Australians” either.

  Thu, 28 Oct 2021 16:00:00 +1100
• Oct 29
  Research Week Event: Research Creation Showcase 2021

  Welcome to the HCA Research Creation Showcase as part of Research Week 2021.

  Online Events
  Welcome to the HCA Research Creation Showcase as part of Research Week 2021.

  The Research Creation Showcase 2021 is in its 7th year of coinciding with the University’s Research Week celebration of all things research. The School of Humanities and Communication Arts is proud to participate in activities that are featured across the research landscape of the University. 2021 is the second year in which we have moved online for our event, featuring research outcomes from School staff and postgraduate students across Design, Music, Media Arts, and Humanities. As a showcase of creative practice and research, we feature an online exhibition of creative works including posters, films, photography, writing and music curated by a team drawn from the School of Humanities and Communication Arts. This event highlights our prolific maker/scholars and establishes the intrinsic link between making and knowing. A suite of artists talks, curators’ presentations, panels, performances and keynotes are drawn from both academics and our partners in the creative industries. Additionally, the top researchers in the School will be recognised at our School researcher awards presentation. Over much of 2021 our working lives have again been transformed. COVID 19 and climate change means living with a global health emergency, an environmental crisis and permanent uncertainty. Our collective patience has been sorely tested. As in 2020, in response to the need for greater physical isolation, many of us have found ways to retain and even re-make social connections. The creative and communication arts have been indispensable to mobilising a response to these most impactful events in the human narrative. These making and knowledge practices assist us in learning how to inhabit this troubled world and how to heal it in the building of safe places. Creative arts can inspire us to understand and to act in a timely fashion—with urgency and across our gendered, racial and bodily diversities. While the Research Creation Showcase 2021 offers compelling examples of creative practice, we can also learn from the presenters of the kinds of knowledges that are embedded in these works as an emphatic indication of the importance of the creative arts and research in a time of crisis. Registration and full program can be accessed at https://bit.ly/3licXWL

  Fri, 29 Oct 2021 10:00:00 +1100
• Nov 2
  Intersect Online Training: Intro to Machine Learning using R: Introduction & Linear Regression

  Explore the fundamentals of Machine Learning and get a comprehensive introduction to linear regression and model training in R.

  Training and skill upgrade; Online Events
  Explore the fundamentals of Machine Learning and get a comprehensive introduction to linear regression and model training in R.

  Please register your interest by joining the waitlist using your University email*. Tickets will be allocated to registrants two weeks prior to the course.

  * People who register without a University email will not be considered when allocating the tickets. Please make sure that you use a valid email address.

  Schedule:

  Tue, 2 Nov: 9:30 am - 12:30 pm AEDT

  Wed, 3 Nov: 9:30 am - 12:30 pm AEDT

  About this course

  Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the R programming language and its scientific computing packages. We will provide a comprehensive introduction to Linear Regression and Model Training, and apply the knowledge on real-world datasets. We hope after this hands-on workshop, you will have a better understanding of these Machine Learning models and techniques and appreciate its capability, as well as make better informed decisions on how to leverage Machine Learning in your research.

  Learning Outcomes:

  • Understand the difference between supervised and unsupervised Machine Learning.
  • Understand the fundamentals of Machine Learning.
  • Comprehensive introduction to Machine Learning models and techniques such as Linear Regression and Model Training.
  • Understand the Machine Learning modelling workflows.
  • Use R and its relevant packages to process real datasets, train and apply Machine Learning models.

  Prerequisites:

  • Either Learn to Program: R and Data Manipulation in R or Learn to Program: R and Data Manipulation and Visualisation in R needed to attend this course. If you already have experience with programming, please check the topics covered in the Learn to Program: R, Data Manipulation in R and Data Manipulation and Visualisation in R courses to ensure that you are familiar with the knowledge needed for this course, such as good understanding of R syntax and basic programming concepts and familiarity with dplyr, tidyr and ggplot2 packages.
  • Maths knowledge is not required. There are only a few Math formula that you are going to see in this course, however references to Mathematics required for learning about Machine Learning will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them.
  • For more information about prerequisites and programming pathways for this course, please visit the course page on our website.

  Why do this course?

  • Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources.
  • It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning.
  • We do have applications on real datasets!
  • Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects.
  • Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning.

  For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using R workshops:

  • Introduction to Machine Learning using R: Introduction & Linear Regression
  • Introduction to Machine Learning using R: Classification
  • Introduction to Machine Learning using R: SVM & Unsupervised Learning
  Tue, 02 Nov 2021 09:30:00 +1100
• Nov 2
  Intersect Online Training: Exploring chi-square and correlation in R

  This course focuses on the realm of inferential statistics, beginning with correlation and reliability using R.

  Training and skill upgrade
  This course focuses on the realm of inferential statistics, beginning with correlation and reliability using R. Please register your interest by joining the waitlist using your University email*. Tickets will be allocated to registrants two weeks prior to the course. * People who register without a University email will not be considered when allocating the tickets. Please make sure that you use a valid email address. About this course This hands-on training is designed to familiarise you with the data analysis environment of the R programming. In this session, we will traverse into the realm of inferential statistics, beginning with correlation and reliability. We will present a brief conceptual overview and the R procedures for computing reliability and correlation (Pearson’s r, Spearman’s Rho and Kendall’s tau) in real world datasets. Learning Outcomes: Obtain inferential statistics and assess data normality Manipulate data and create graphs Perform Chi-Square tests (Goodness of Fit test and Test of Independence) Perform correlations on continuous and categorical data (Pearson’s r, Spearman’s Rho and Kendall’s tau) Prerequisites This course assumes familiarity with R and RStudio. You should have a good understanding of R syntax and basic programming concepts, as well as familiarity with data manipulation (dplyr) and visualisation (ggplot2 package). Please consider attending Intersect’s following courses to get up to speed: Learn to Program: R Data Manipulation and Visualisation in R For more information about prerequisites and this course, please visit the course page on our website. Target Audience and Expectation This Introductory training is designed for researchers and students who have had little to no formal training in statistics. The session focuses on the practical implementation; basic conceptual understanding and interpretation of the relevant methods and their corresponding outputs, with little emphasis on theory.
  Tue, 02 Nov 2021 09:30:00 +1100
• Nov 4
  Intersect Online Training: Excel for Researchers

  Intersect Online Training: Excel for Researchers

  Training and skill upgrade; Online Events
  Intersect Online Training: Excel for Researchers

  This course runs over two days. You must attend both days to complete the course. Zoom link will be sent to you closer to the training day.

  Part 1: Thursday, 4 November 2021, 9:30 AM – 12:30 PM

  Part 2: Friday, 5 November 2021, 9:30 AM – 12:30 PM

  In order to participate in this course, you must have Excel installed on your computer. For Western Sydney University researchers, you can contact Jeff Wang (jeff.wang@westernsydney.edu.au) for help on installing Excel.

  Why do this course?

  Data rarely comes in the form you require. Often it is messy. Sometimes it is incomplete. And sometimes there's too much of it. Frequently, it has errors. We'll use one of the most widespread data wrangling tools, Microsoft Excel, to import, sort, filter, copy, protect, transform, summarise, merge, and visualise research data. While aimed at novice Excel users, most attendees will walk away with new tricks to work more efficiently with their research data.

  You’ll learn to:

  - ‘Clean up’ messy research data

  - Organise, format and name your data

  - Interpret your data (SORTING, FILTERING, CONDITIONAL FORMATTING)

  - Perform calculations on your data using functions (MAX, MIN, AVERAGE) - Extract significant findings from your data (PIVOT TABLE, VLOOKUP)

  - Manipulate your data (convert data format, work with DATES and TIMES) - Create graphs and charts to visualise your data (CHARTS)

  - Handy tips to speed up your work

  Thu, 04 Nov 2021 09:30:00 +1100
• Nov 11
  Intersect Online Training: Intro to Machine Learning using R: Classification

  A comprehensive introduction to the Classification models in Machine Learning and their application on real-world datasets using R.

  Training and skill upgrade; Online Events
  A comprehensive introduction to the Classification models in Machine Learning and their application on real-world datasets using R.

  Please register your interest by joining the waitlist using your University email*. Tickets will be allocated to registrants two weeks prior to the course.

  * People who register without a University email will not be considered when allocating the tickets. Please make sure that you use a valid email address.

  Schedule:

  Thur, 11 Nov: 9:30 am - 12:30 pm AEDT

  Fri, 12 Nov: 9:30 am - 12:30 pm AEDT

  About this course:

  Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the R programming language and its scientific computing packages. We provide a comprehensive introduction to the Classification models in Machine Learning and use R to apply the knowledge on real-world datasets. We hope after this hands-on workshop, you will have a better understanding of these Machine Learning models and techniques and appreciate its capability, as well as make better informed decisions on how to leverage Machine Learning in your research.

  Learning Outcomes:

  • Comprehensive introduction to Machine Learning models and techniques such as Logistic Regression, Decision Trees and Ensemble Learning.
  • Know the differences between various core Machine Learning models.
  • Understand the Machine Learning modelling workflows.
  • Use R and its relevant packages to process real datasets, train and apply Machine Learning models.

  Prerequisites:

  • Either Learn to Program: R and Data Manipulation in R or Learn to Program: R and Data Manipulation and Visualisation in R needed to attend this course. If you already have experience with programming, please check the topics covered in the Learn to Program: R, Data Manipulation in R and Data Manipulation and Visualisation in R and Introduction to ML using R: Introduction & Linear Regression courses to ensure that you are familiar with the knowledge needed for this course, such as good understanding of R syntax and basic programming concepts, familiarity with dplyr, tidyr and ggplot2 packages, and basic understanding of Machine Learning and Model Training.
  • Maths knowledge is not required. There are only a few Math formula that you are going to see in this course, however references to Mathematics required for learning about Machine Learning will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them.
  • For more information about prerequisites and programming pathways for this course, please visit the course page on our website.

  Why do this course?

  • Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources.
  • It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning.
  • We do have applications on real datasets!
  • Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects.
  • Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning.

  For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using R workshops:

  • Introduction to Machine Learning using R: Introduction & Linear Regression
  • Introduction to Machine Learning using R: Classification
  • Introduction to Machine Learning using R: SVM & Unsupervised Learning
  Thu, 11 Nov 2021 09:30:00 +1100
• Nov 16
  Intersect Online Training: Introduction to Machine Learning using R: SVM & Unsupervised Learning

  A comprehensive introduction to Support Vector Machine and Unsupervised models in Machine Learning using R.

  Training and skill upgrade; Online Events
  A comprehensive introduction to Support Vector Machine and Unsupervised models in Machine Learning using R.

  Please register your interest by joining the waitlist using your University email*. Tickets will be allocated to registrants two weeks prior to the course.

  * People who register without a University email will not be considered when allocating the tickets. Please make sure that you use a valid email address.

  About this course:

  Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the R programming language and its scientific computing packages. We provide a comprehensive introduction to Support Vector Machine and Unsupervised models in Machine Learning and use R to apply the knowledge on real-world datasets. We hope after this hands-on workshop, you will have a better understanding of these Machine Learning models and techniques and appreciate its capability, as well as make better informed decisions on how to leverage Machine Learning in your research.

  Learning Outcomes:

  • Comprehensive introduction to Machine Learning models and techniques such as Logistic Comprehensive introduction to Machine Learning models and techniques such as Support Vector Machine, K-Nearest Neighbor and Dimensionality Reduction.
  • Know the differences between various core Machine Learning models.
  • Understand the Machine Learning modelling workflows.
  • Use R and its relevant packages to process real datasets, train and apply Machine Learning models.

  Prerequisites:

  • Either Learn to Program: R and Data Manipulation in R or Learn to Program: R and Data Manipulation and Visualisation in R needed to attend this course. If you already have experience with programming, please check the topics covered in the Learn to Program: R, Data Manipulation in R and Data Manipulation and Visualisation in R and Introduction to ML using R: Introduction & Linear Regression courses to ensure that you are familiar with the knowledge needed for this course, such as good understanding of R syntax and basic programming concepts, familiarity with dplyr, tidyr and ggplot2 packages, and basic understanding of Machine Learning and Model Training.
  • Maths knowledge is not required. There are only a few Math formula that you are going to see in this course, however references to Mathematics required for learning about Machine Learning will be provided. Having an understanding of the Mathematics behind each Machine Learning algorithms is going to make you appreciate the behaviour of the model and know its pros/cons when using them.
  • For more information about prerequisites and programming pathways for this course, please visit the course page on our website.

  Why do this course?

  • Useful for anyone who wants to learn about Machine Learning but are overwhelmed with the tremendous amount of resources.
  • It does not go in depth into mathematical concepts and formula, however formal intuitions and references are provided to guide the participants for further learning.
  • We do have applications on real datasets!
  • Machine Learning models are introduced in this course together with important feature engineering techniques that are guaranteed to be useful in your own projects.
  • Give you enough background to kickstart your own Machine Learning journey, or transition yourself into Deep Learning.

  For a better and more complete understanding of the most popular Machine Learning models and techniques please consider attending all three Introduction to Machine Learning using R workshops:

  • Introduction to Machine Learning using R: Introduction & Linear Regression
  • Introduction to Machine Learning using R: Classification
  • Introduction to Machine Learning using R: SVM & Unsupervised Learning
  Tue, 16 Nov 2021 09:30:00 +1100
• Nov 17
  Research Hour

  Informal session for researchers to connect with research support staff from ITDS/Library/Research Services/Intersect; share ideas and ask questions.

  academic events; Information sessions; Online Events
  Western Sydney University researchers
  Informal session for researchers to connect with research support staff from ITDS/Library/Research Services/Intersect; share ideas and ask questions.

  Researchers from across Western are invited to join us for ‘Research Hour’; hosted by ITDS, Research Services, Intersect and the Library - an informal, drop-in, Q&A session. If you have any questions about any aspect of your research project, plans, or implementation then Research Hour is the place for you. We have a range of experts on hand from across the University to discuss any queries you might have, help you problem solve, or point you to resources and services that could be of benefit to you as you carry out your research. Incorporating ‘Hacky Hour’: swap notes, get help, learn techniques in programming and data science, code, digital tools, HPC etc. Providing assistance across a range of research related topics (e.g.: managing your online researcher profile, strategic publishing, Open Access, metrics and impact, data management plan, research data storage, equipment and facilities). No question is too big or too small – we want to hear from you, and to make sure you have all the support you need to carry out your research successfully. Research Hour is open to Researchers from any discipline and at any level of their career… everyone is welcome. This is a participatory discussion session, not a presentation – come along prepared to engage!

  Wed, 17 Nov 2021 12:00:00 +1100
• Nov 23
  2021 National Students as Partners Roundtable

  The 21C Project at Western Sydney University is hosting the 2021 National Students as Partners Roundtable.

  academic events; Conferences and seminars; Meetings; Online Events
  The 21C Project at Western Sydney University is hosting the 2021 National Students as Partners Roundtable.

  The 21C Student Curriculum Partners at Western Sydney University are excited to be hosting the 2021 National Students as Partners Roundtable. Supported by the University's 21C Project, the theme this year is: THE PARTNERSHIP PARADOX Click on the video announcement to learn how you can be part of it. https://www.youtube.com/watch?v=AGxqjUfOIIA When: Tuesday 23rd – Thursday 25th November 2021 Where: Online on MS Teams and Zoom Cost: It’s free

  The invitation is now open for students and staff to submit a Partnership Case Study, and to share their partnership practice with a national and international student-staff partnership community. It’s open to students, academics, researchers, professional and technical staff in tertiary and university settings to submit their initiative. We’re interested in student-staff partnership initiatives that focus on:

  1. learning, teaching, curriculum and assessment

  2. engaging students in research, or as researchers

  3. co-curriculum activities and programs for student engagement

  4. students’ participation in academic governance

  5. academic and educational development

  6. conceptual and theoretical challenges to student-staff partnership

  We are delighted to confirm Professor Peter Felten, Elon University – one of the leading scholars in student-staff partnership – as the first of three keynote speakers.

  Partnership case studies close Friday 1st October, and registration for the Roundtable opens mid-September.

  Visit the National SAP Roundtable website www.saproundtable21.com to learn more, and follow on twitter #SAPRtable21 for updates to the program.

  Tue, 23 Nov 2021 00:00:00 +1100
• Nov 23
  Designing a Dementia-Friendly South West Sydney

  Building Partnerships to Transform South Western Sydney into a Dementia-Friendly Region.

  Conferences and seminars; Information sessions; Training and skill upgrade; Online Events
  Representatives from South West Sydney councils and the local health district, and state government planners
  Building Partnerships to Transform South Western Sydney into a Dementia-Friendly Region.

  Did you know? South West Sydney is expected to have the highest increase in dementia cases in all of NSW by 2050. Dementia is a disability that can affect mobility, vision, and cognition; it is not a normal part of ageing. What are we doing about it? Western Sydney University Researcher, Dr Diana Karamacoska, is hosting an online interactive workshop for council staff, state planning representatives, and South West Sydney local health district officers to raise awareness for dementia-enabling environments. Together, we will identify strategies to transform South West Sydney into a dementia-friendly region. Participants will receive a certificate acknowledging their involvement through Dementia Australia, the national peak body for dementia. When? 10:00am to 12:00pm on 23rd November 2021 How? The event will be hosted online through Zoom: https://uws.zoom.us/j/86022689900 Participants must register via EventBrite to receive their certificate from Dementia Australia. Want to know more? Contact Dr Diana Karamacoska on mobile 0479 150 816 or email d.karamacoska@westernsydney.edu.au Acknowledgements This event is supported by Western Sydney University and Maridulu Budyari Gumal SPHERE.

  Tue, 23 Nov 2021 10:00:00 +1100
• Dec 2
  NICM HRI Webinar: The art and science of Lifestyle Medicine

  Join NICM HRI and guest speaker Dr Sam Manger as he discusses Lifestyle Medicine - key research, benefits and clinical use in optimising healthcare.

  academic events; Conferences and seminars; Information sessions; Online Events
  Researchers, academics, clinicians, staff, students, and anyone interested in Lifestyle Medicine
  Join NICM HRI and guest speaker Dr Sam Manger as he discusses Lifestyle Medicine - key research, benefits and clinical use in optimising healthcare.

  NICM Health Research Institute presents Dr Sam Manger, General Practitioner; Senior Lecturer and Medical Educator, College of Medicine and Dentistry, James Cook University; and President of the Australasian Society of Lifestyle Medicine (ASLM). Join guest seminar speaker Dr Manger as he discusses key research in Lifestyle Medicine, and its benefits and clinical use in optimising healthcare. ABSTRACT Lifestyle Medicine is growing in popularity amongst clinicians, public health professionals, healthcare executives, researchers, scientists and educators. In this presentation, Dr Manger will address why there is a need for this growing approach, explain what Lifestyle Medicine is, and highlight key studies in Lifestyle Medicine covering a broad range of physical and mental illness from depression to diabetes. He will also discuss its economic benefits, application in practice including health coaching, and the new models of health care delivery utilising Lifestyle Medicine.

  Thu, 02 Dec 2021 12:00:00 +1100