Eric Wespi is the founder and leader of a Data Science team in the Process Development group at Boston Scientific. This team develops tools using AI-based computer vision, graph analytics, natural language processing, and various predictive analytics methods. Eric has been with Boston Scientific for 7 years, prior to which he was a Staff Engineer and analytics expert at Intel Corp. He has spent over 15 years applying advanced analytics and data visualization methods to improve automated manufacturing. Eric has a degree in Chemical Engineering from the University of Minnesota and an MBA from the W.P. Carey School of Business at Arizona State University.
Over the past 10 years we have seen the emergence of impressive AI capabilities via the open source community. Pretrained models and transfer learning, a growing ecosystem of software tools, and decreasing compute costs allow for the development of highly accurate and custom models. So why aren’t we seeing widespread adoption in manufacturing? We will discuss the process and lessons learned by the AI Vision team at Boston Scientific, which has been developing and deploying models for automated visual inspections in manufacturing.
Professor at the School of Mechanical and Aerospace Engineering (MAE), Nanyang Technological
University (NTU) and Executive Director of Singapore Centre for 3D Printing (SC3DP),Singapore.
2001 Doctor of Philosophy (Ph.D.), University of Reading, UK
1996 Master of Science (MSc), Technical University of Lisbon, Portugal
1993 Licenciatura degree (5 years degree) in Mechanical Engineer, Technical University of Lisbon, Portugal
Inspiring Leaders programme, University of Manchester in partnership with CIRRUS (2019-2020)
Paulo Bartolo is author and co-author of more than 600 publications as journal papers, book chapters and conference proceeding papers. He also edited 22 books and has 16 Patents. His research has been published in high impact factor journals.
3D bioprinting, the combined use of additive manufacturing, biocompatible and biodegradable materials, cells and biomolecular signals is an emerging topic of research, with significant social and economic relevance. This lecture will introduce the concept of 3D bioprinting, discussing key printing strategies including in-situ bioprinting, fabrication techniques including robotic-assisted bioprinting and multi-modal systems, and main materials. Recent advances related to the use of smart materials and the concept of 4D bioprinting is also discussed. Successful cases and commercial opportunities demonstrating the relevance of 3D bioprinting are also presented. Finally, the presentation will address the main research challenges and future perspectives in the field of 3D bioprinting.