Current Activities
Overview: This campus-wide program provides outstanding early-career researchers with intensive training and research experience as they ready themselves for independent research in academia and other sectors. As one of the sites in a new global network of postdoc programs focusing on AI in Science and Engineering, we support postdocs who apply AI methodology to address significant research questions. AI is defined broadly to include machine learning, robotics, Bayesian inference, and simulation. Science and engineering includes mathematical sciences, physical sciences, earth and environmental sciences, basic biological sciences, and engineering.
Who Will Benefit: Postdocs, their faculty mentors, and research collaborators.
Coordinators: H.V. Jagadish (Director, MIDAS | Professor, Computer Science and Engineering), Jing Liu (Executive Director, MIDAS), and William Currie (Professor and Associate Dean for Research and Engagement, SEAS)
Overview: Generative AI, such as ChatGPT and Bard, generates novel texts, images and other contents by learning from extensive datasets using machine learning algorithms. By leveraging their ability to learn patterns from existing data, generative AI models can be a valuable component in various research domains, aiding researchers in tasks such as forming hypotheses, building databases, providing experimental design and carrying out analysis, and even writing scientific papers. MIDAS coordinates research discussions, training activities and builds collaboration to enable the use of generative AI to accelerate research and enable new research. The first faculty workshop is offered in July, 2023.
Who Will Benefit: All researchers on campus who would like to explore generative AI methods in research.
Coordinator: Jing Liu (Executive Director, MIDAS)
Overview: Using the postdoc training program as the core, we are developing research and training activities for campus researchers and trainees, to connect AI methodologists and domain researchers, to enable AI skills training for researchers, to build an AI in Science and Engineering research community. The first AI in Science and Engineering summer academy is offered in 2023.
Who Will Benefit: All researchers on campus who would like to apply AI methods to science and engineering research.
Coordinators: Jing Liu (Executive Director, MIDAS) and Ken Reid (Data Scientist, MIDAS)
Overview: Significant advancements in scientific computing, AI, and the hardware and software research environment are enabling researchers to develop AI-driven research workflows (ARWs): AI, including Generative AI, as components for data processing and analytics, and as tools to design and monitor experiments. Institutions and researchers are capitalizing on this opportunity to significantly accelerate research. MIDAS has organized a mini-symposium and faculty discussions around this theme, and is now building collaboration among campus researchers to enable ARW development and adoption.
Who Will Benefit: All researchers on campus who would like to explore how ARWs could facilitate their research and researchers who are interested in developing ARWs.
Coordinator: Jing Liu (Executive Director, MIDAS)