Missouri Data Science & Informatics Symposium 2024

Title: Modeling the spatiotemporal distributions of ticks and tick-borne diseases.

Abstract:
Ticks and tick-borne diseases as well as other arthropods and arthropod-borne diseases are to a large extent regulated by ambient conditions to which these vectors are exposed. This renders the study of their spatial and population dynamics, and to a lesser extent also the prevalence of diseases transmitted by them possible through geospatial and computational methods. Tick-borne diseases have increased in intensity (i.e., number of cases seen) as well as in the spatial distribution over the past couple of decades. The spatiotemporal distribution and exact nature of the driving factors behind such surge are not clearly understood. Fine-resolution vector and disease data at patient-level, and matching remote sensing and demographic/socio-economic data are useful. Additionally, novel geospatial models need to be developed to find meaningful associations and actionable information.

Bio:

Dr. Raghavan is broadly interested in spatially-enabled computational epidemiology of vector-borne and infectious diseases and applications of geospatial approaches for enhancing animal/public health. He extensively uses Geographic Information Science (GIS) and remote-sensing concepts in his research alongside geo-statistical, correlative modeling, and Bayesian modeling approaches for understanding spatio-temporal dynamics of non-stationary epidemiological processes. His current and prior research have identified important spatio-temporal patterns and spatial determinants for vector/water-borne zoonotic diseases from climatic, environmental, and socio-economic themes. Increasingly, his research strives to identify consistencies in complex meteorological variable associations (i.e. climate-change) with vector-borne diseases through the utilization of high-resolution ground-based and NASA Earth Observing System (EOS) datasets.

Title: Achieving AI for Good

Abstract
AI systems are developing by leaps and bounds to the point that we will arrive at Artificial General Intelligence (i.e., human-level AI) sooner or later. Along the way, collective effort is needed now to ensure that this technology is designed, developed, and deployed for good. However, a fundamental question remains: how do we achieve AI for good and how do we contribute towards its realization? Through the lens of Responsible Research Innovation, this talk will present theoretical and practical insights on how individuals and society at large can achieve AI for good.

Bio
Dr. Bautista is an Assistant Professor at the Sinclair School of Nursing, University of Missouri-Columbia (MU). He also holds other MU appointments, such as MizzouForward Faculty, MUIDSI Core Faculty in Health Informatics, and MU Provost’s AI Teaching Fellow. He has an interdisciplinary background in health (nursing and public health), informatics (health, social, and social justice informatics), and communication science (health and organizational communication), with specific training and expertise in both qualitative (interviews, observations, and document analysis) and quantitative (primary and secondary survey data) research. As an early career researcher, he has received fellowships and internal grants to conduct socio-technical research to identify the benefits and risks of using smartphones, social media, blockchain, and artificial intelligence (AI) for health-related purposes. Since 2022, he has gained valuable insights and knowledge on the ethical and responsible use of AI by attending competitive workshops (e.g., Global Sandpit on Trustworthy Autonomous Systems and Work in the Age of Intelligent Machines Workshop) and facilitating workshops (e.g., at UT Austin, Johns Hopkins, and Yale).

Title. Potential applications of AI in clinical medicine

Abstract: This brief talk will explore potential applications of AI in clinical medicine. Areas to be covered include large language models, imaging, and clinical decision algorithms. In addition, barriers to implementation will be discussed.

Bio
Dr. Richard Hammer is highly trained hematopathologist/surgical pathologist with extensive experience and a focus on providing state-of-the-art diagnosis and evaluation using the latest evidence-based medicine. His lab provides high-level service in hematopathology, flow cytometry, coagulation, and molecular diagnostics in hematology. He also is involved in bioinformatics and developing tools to apply digital solutions to clinical practice and clinical decision support.