Dynamic Research Enterprise for Multidisciplinary Engineering Sciences
Zhejiang University (ZJU) and the University of Illinois Urbana-Champaign (Illinois) have formed a joint research enterprise, the Dynamic Research Enterprise for Multidisciplinary Engineering Sciences (DREMES). DREMES is a unique umbrella for active collaborations among ZJU, Illinois, and the existing joint ZJU-UIUC Institute for Engineering in Haining, China. The enterprise explores fundamental global issues in human health, energy and environment, and sustainable manufacturing. Three center-scale theme proposals have been initiated to start the operation of DREMES.
Directors
Philip T. Krein, PhD, PE
Grainger Emeritus Chair Professor in Electric Machinery and Electromechanics
Director, ZJU-UIUC Joint Research Center
University of Illinois Urbana-Champaign
Email: krein@illinois.edu
Er-Ping Li, IEEE Fellow
Vice Dean, Zhejiang UniversityQiushi Chair Professor in Information and Electronic Engineering
Director, ZJU-UIUC Joint Research Center
Zhejiang University International Institute(Haining)
Email: erpingli@intl.zju.edu.cn
Center for Pathogen Diagnostics (CPD)
As highlighted by the ongoing COVID-19 pandemic, the technologies and commercial products available for disease diagnosis and immunity determination include important limitations that drive cost, detection limits, time-to-result, sensitivity/selectivity against false results, and availability at the point of care. The shortcomings of COVID-19 diagnostics are representative of those used in the contexts of bacterial pathogens, fungal pathogens, vector-borne illness, food safety, and monitoring of environmental resources. The vision for the CPD is to establish a multi-disciplinary and multi-institutional research and development team to address significant technological and scientific gaps in the field of pathogen detection. Our goal is to establish a pipeline of innovation that includes identification of biological and structural characteristics of pathogens that can serve as a basis for next-generation detection techniques, sample preparation technologies that effectively separate target materials from complex media, ultra-selective molecular biology methods, ultra-sensitive biosensor signal transduction, mobile detection instruments, and machine learning tools that convert detection data into clinically relevant knowledge.
Co-Directors:
Brian T. Cunningham, Professor, UIUC, bcunning@illinois.edu
Huan Hu, Professor, Zhejiang University - UIUC Institute, huanhu@intl.zju.edu.cn
Adaptive, Resilient Cyber-Physical Manufacturing Networks
Industry 4.0 seeks to evoke new capabilities, efficiencies, and flexibility in manufacturing. This revolution is powered the connectivity, data analytics, and automation made possible by modern cyber-infrastructure to make and execute timely, perceptive, and data-supported manufacturing decisions. The next generation of manufacturing infrastructure can be viewed as a cyber-physical system (CPS) integrating manufacturing resources (physical equipment and processes) with high-bandwidth communications and high-performance edge and endpoint computing (cyber infrastructure). The overall goal of this project is to define the science and technology for creating smart and highly flexible manufacturing networks emphasizing: (1) the interaction of autonomous hardware (processing, transportation, storage) and software (planning, modeling, scheduling, learning) agents to produce verifiably correct and safe behavior to achieve a common manufacturing goal; (2) the collection, curation, storage and use of data on the current and past states and performance of the network/agents in evoking optimized behavior with respect to stated objectives; (3) the continuous analysis of the data to learn and train decision-making (concerning, system faults, safety and security, etc.); and (4) on-the-fly adaptation to changing needs and detected errors or risks in order to ensure resilience. Based on a solid design methodology developed in the project, we will conduct case studies on industrially relevant application problems ranging from flexible assembly cells consisting of production collaborative robots and autonomous e-vehicles to distributed supply networks configured for the production of an entire product.
Leads:
Katherine Driggs-Campbell, Professor, UIUC, krdc@illinois.edu
Placid Ferreira, Professor, UIUC; pferreir@illinois.edu
Klaus-Dieter Schewe, Professor, Zhejiang University-UIUC Institute (ZJUI); KD.Schewe@intl.zju.edu.cn
Hongwei Wang, Associate Professor and Assistant Dean, ZJUI
CIRCLE: Center for Infrastructure Resilience in Cities as Livable Environments
Over 80% of the U.S. population and 60% of China’s population live in cities and rely on urban infrastructure systems, such as those for energy, water, environment, and transportation, to provide essential services to the residents. These infrastructure systems are key to cities providing livable environments. Moreover, resilience of this interconnected infrastructure against natural and human-made disasters is crucial for effective protection of people and their livelihoods. We assert that without resilient infrastructure that can withstand and recover from extreme events, cities are not livable. However, climate change and human activities have exacerbated the frequency, duration, and intensity of climate-driven extreme events such as typhoons, floods, droughts, and heat waves,4 as well as the risks associated with pandemics, terrorist attacks, and earthquakes. Despite advances in distributed sensing, risk assessment, and urban design, large cities remain vulnerable. For example, failures of both physical and social infrastructure clearly worsened the impact of massive weather disasters in New Orleans (Katrina), New York (Sandy), San Juan (Maria), and Houston (Harvey) – the four costliest storms in the U.S. history.5 Global climate change has aggravated the co-called compounding extreme events6 (e.g., a drought event followed by a flooding event, co-occurrence of a heat wave with a flood or drought, etc.), which hinders the understanding and solution development toward holistic city-level infrastructure resilience. Moreover, the continued rapid growth of our cities has profoundly changed urban infrastructure systems, yielding unprecedented and time sensitive opportunities and challenges for city planners and managers. The convergence of data science and engineering, as described herein, is needed to assess current vulnerabilities and design strategies to develop resilient interdependent infrastructure in response to these extreme events, and to enhance overall resilience in cities as livable environments.
Leads:
Billie F. Spencer, Jr., Professor and Newmark Endowed Chair, UIUC bfs@illinois.edu
Yan Xiao, Distinguished Professor, Zhejiang University- UIUC Institute, yanxiao@intl.zju.edu.cn