LIMPID/BisQue + IDEAS Joint Workshop Feb 3-5, 2020
Following up on the 2018 workshop, we will be hosting a second LIMPID/BisQue workshop on Scalable Image Informatics. This is a joint meeting with the workshop on Applications of Machine Learning and Scalable Image Informatics to Materials Discovery, held as part of the NSF-sponsored IDEAS program on Data-Driven Approaches to Materials Discovery, at the University of California at Santa Barbara. Participation is by invitation only and we are expecting over 80 registered participants.
The three day joint workshop will take place at UCSB from February 3-5, 2020. The workshop will start at 8:00 AM on Monday, February 3rd and adjourn by 5:00 PM on Wednesday, February 5th.
This workshop will bring together researchers from Academia and National Laboratories who are developing or have adopted new experimental methods and measurement tools that provide very large and rich data sets, with early adopters of machine learning as well as leaders in the machine learning community. The main objective of the LIMPID/BisQue workshop is to identify key requirements for scalability and sustainability of software infrastructures to support multimodal data analysis and machine learning in diverse application areas such as life sciences, marine science, materials and health sciences. A key objective of the IDEAS workshop is to connect researchers in the data sciences field with domain researchers to foster a dialogue and establish the state-of-the-art in the application of machine learning to materials discovery related disciplines, and identify (i) the potential impact of, and opportunities for, data sciences in materials, with an emphasis on integrating experimental and computational materials; and (ii) the grand challenges at the intersection of materials discovery and machine learning.
Monday will focus on sustainable software infrastructure for multimodal informatics and machine learning for image applications. Tuesday will address data-driven approaches for advanced materials applications, effectively educating a workforce of data-driven innovators, and high-throughput approaches in computational mechanics. Wednesday will focus on accelerating data-intensive research with a range of applications, and AI and ML for high-dimensional and multi-scale datasets.
Samantha Daly, Mechanical Engineering, UCSB
B.S. Manjunath, ECE, UCSB
Tresa Pollock, Materials, UCSB