The 11th international conference on Computational Visual Media (CVM 2023) will be held on April 6th to April 8th, 2023, at Shenzhen, China. The Computational Visual Media Conference series is intended to provide a major international forum for exchanging novel research ideas and significant practical results both underpinning and applying Visual Media. With the rapid progress of Internet technology, large-scale visual data can be found on the Internet, bringing significant opportunities for novel processing of visual information, as well as commercial applications. The primary rationale for this new conference series is to target cross disciplinary research which amalgamates aspects of computer graphics, computer vision, machine learning, image processing, video processing, visualization and geometric computing. Original research is sought in areas concerning the classification, composition, retrieval, synthesis, and understanding of visual media.

The 9th IEEE International Conference on Data Science and Advanced Analytics (DSAA) features its strong interdisciplinary synergy between statistics (via ASA), computing and information/intelligence sciences (via IEEE and ACM), and cross-domain interactions between academia and business for data science and analytics. DSAA sets up a high standard for its organizing committee, keynote speeches, submissions to main conference and special sessions, and a competitive rate for paper acceptance. DSAA has been widely recognized as a dedicated flagship annual meeting in data science and analytics such as by the Google Metrics and China Computer Foundation. DSAA'2022 provides a premier forum that brings together researchers, industry and government practitioners, as well as developers and users of big data solutions for the exchange of the latest theoretical developments in Data Science and the best practice for a wide range of applications. DSAA'2022 invites submissions of papers describing innovative research on all aspects of data science and advanced analytics as well as application-oriented papers that make significant, original, and reproducible contributions to improving the practice of data science and analytics in real-world scenarios.

As a technology which can assist precise treatment, remote patient monitoring, edlerly health monitoring and so on, so as to reduce the medical burden and benefit long-term care, smart health care through mobile sensing has always drawn enormous attention. Such a trend will increase dramatically, since the number of people aged 65 or older becomes more and more in the near future in many coutries. The evolution of smart health care through mobile sensing has also experienced a number of challenges including, users’ security and privacy problem, applicability in real scenario, communication among various devices, hertergenous data management and accurate pridiction, poor scalability, and etc. Various theories, prediction models and sophisticated mechanisms have been proposed to deal with the problems of the smart health care. The recent advances in mobile sensing technoliges, Internet of Things (IoT), and Artificial Intelligence (AI) have brought new opportunities in overcoming the challenges of health care. However, towards mobile sensing with more secure, more real-time, more scalable, more applicable and more accurate smart health care, we still have a long way to go.

We believe that future mobile sensing will closely fuse with 5th Generation (5G) and Beyond-5G technologies, comprehensive fusion between crowd sourcing, AI, and thrustworty mobile sensing. Thus, the future mobile sensing also need to solve a lot of emerging research issues, such as the privacy and security of user data, behavior monitoring based on hertergenous data, precise prediction, real-time mechanisms, and etc. Once the smart health care technology becomes more intelligent, more secure, more real-time, more scalable, more applicable and more accurate in the future, it will spark more blue-sky thinking, and innovative ideas that can improve the future mobile sensing technologies to another level with strong application guarantee.

Thereby, the goal of this workshop is to bring together researchers and experts from academia and industry to discuss and promote the research and development needed to overcome the major challenges that pertain to this research direction with strong application potential. The scope of this workshop includes but not limited to the following topics.

1. AI-powered Smart Health Care
2. Data Collection and Fusion on Hertergenous Mobile Sensing Data
3. Health Care Models for Future Wireless Sensing
4. Scalable and Secure Mechanisms Health Care Systems
5. Data Analytics to Human Behaviours for Future Wireless Sensing
6. Security and Privacy Issues in Health Care Intelligence
7. Healthcare System Design and Deployment
8. Privacy/Security/Access Control Protocols
9. Design and Implenentation of Portable Healthcare Devices
10. Proof-of-Concept Smart Health Care for Future Mobile Sensing: Experimental Prototyping and Testbeds
11. COVID-19-related Data Analysis in Smart City

The workshop will feature two keynote speeches given by world leading researchers in the field. The workshop accepts only original and previously unpublished papers. All submissions must be formatted in standard ACM conference proceedings format (two-column, 10pt format). The maximum number of printed pages is six including figures. Papers must include the author names and affiliations for single-blind peer reviewing by the program committee. Authors of accepted papers are expected to present their papers at the workshop. Accepted papers will be published in the ACM mmNets proceedings and will be archived in the ACM Digital Library.