Each of these projects are designed to deliver real-world social benefits and highlight the Institute鈥檚 focus on advanced manufacturing and creative interdisciplinary collaboration across the university.
Welcome to July鈥檚 eNews for the UNSW Materials and Manufacturing Futures Institute (MMFI). As we go into the second half of the year, we have continued to engage our industry partners and different schools and faculties of UNSW, and are excited to announce some new collaborative projects that will deliver tangible products to assist our front-line health workers in the current, as well as any future, scenarios. We have also been busy continuing to support the university in 鈥淭he Second Stage of Return to Campus鈥 and are glad to announce several successful MMFI seed grants for 2020. Each of these projects are designed to deliver real-world social benefits and highlight the Institute鈥檚 focus on advanced manufacturing and creative interdisciplinary collaboration across the university.
Congratulations to the following successful proposals for MMFI seed grant funding for 2020 and thank you to all applicants. The continuing situation across the globe has shown that having protective equipment and technologies are crucial in fighting any disease, and that key manufacturing industries and supply chains are at the ground level of any useful product or solution. The proposals were made in response to these circumstances and so the MMFI is keen to support the successful applicants through to the delivery of their finished products.
To continue the series, Dr. Jack Yang will be holding a third Python virtual townhall in late August. An announcement with the time and a link to access the workshop will be provided shortly.
Understanding High-Dimensional Data with Unsupervised Machine Learning 鈥撀燚r. Jack Yang
In the previous townhall, we looked at an example of how supervised machine learning works in practice to uncover the trends in data, which can be helpful for predictions. In this workshop, we will look at unsupervised machine learning. This is a powerful tool to reduce the dimensionalities in complex datasets, which will help you to better visualize the data in order to uncover hidden trends.
We have initiated a collaboration between the School of Electrical Engineering and Telecommunication, UNSW for rapid innovation of聽an advanced personal protection equipment (PPE) to聽provide an opportunity to manufacture a cost-effective PPE for front-line health workers using our manufacturing facilities at MMFI.
We have continued discussions with UNSW鈥檚 legal office and Knowledge Exchange to explore the next steps in the planning of our new initiative - MMFI Factory Lab.聽 Watch this space as we continue to develop our long-term plan for this exciting innovation in production and manufacturing.
The second Python virtual workshop, 鈥楳achine Learning 101 Using Python鈥, by Dr. Jack Yang was held on the 23rd July 2020. We had 180 registrations, with a total of 69 people attending the live event, so we will now try a change of media platform for the third workshop to try and increase the attendance vs registration ratio by transferring the media platform from Zoom to Microsoft Teams.
Have you had a recent success?聽 Do you have something you want to share with the MMFI team?聽 We want to hear from you!聽 Please contact us directly with any feedback or news items at聽mmfutures@unsw.edu.au