Conference: Workshop on Predictive Modeling in Biology and Medicine
- Institution
- University of California-Riverside, CA
- Principal investigator
- Mark Alber
- Funding
- $30K
- Duration
- 2023–2024
Moonbase score
Still being scored
Abstract
The conference on "Predictive Modeling in Biology and Medicine" is to be held on November 17-19 (Friday-Sunday), 2023, at the University of California, Riverside (UCR) (https://icqmb.ucr.edu/predictive-modeling-biology-and-medicine-conference). The conference will bring together researchers at different stages of their career and with diverse backgrounds to exchange ideas and novel approaches as well as to promote interdisciplinary collaborations on predictive modeling in biology and medicine. By bringing together researchers from different disciplines and at different career stages, the aim of the conference is to promote communication and collaboration among researchers with diverse backgrounds, as well as to help the new generation of researchers, especially those from underrepresented groups, to establish their own research programs. The conference includes a workshop with a special focus on promoting Diversity, Equity, and Inclusion (DEI) in mathematical and computational biology and, more broadly, in the mathematical and scientific community. The first day of the conference will include a workshop consisting of two plenary talks and two panel discussions. The first is concerned with promoting DEI in education and research, and the second panel will focus on career paths in mathematical and computational biology so that the participants can discuss and plan concrete actions to cultivate an inclusive and welcoming research community environment. In the last two decades, a variety of multi-scale mathematical and computational models have been developed and widely applied to better understand biological systems. Recently, large amounts of data generated from biological experiments as well as clinical data provided new opportunities for developing novel data-driven modeling approaches combined with machine learning algorithms to gain novel insights into biology and medicine. The conference will focus on three main research topics: 1. Multi-scale modeling in biology and medicine, 2. Data driven and machine learning methodologies in biology and medicine, 3. Predictive modeling in biology and medicine. A broad spectrum of speakers, some of the leading experts in the field, with diverse backgrounds will share their experiences and encourage the next generation of researchers. Two poster sessions with more than 50 posters will promote research of graduate students and postdoctoral associates. A large number of graduate students and postdoctoral associates from underrepresented groups, including those from UCR, will participate in the conference, which will allow them to learn the most recent research approaches in the field, and provide them with advice and resources to successfully pursue Ph.D. degrees and seek career opportunities in STEM fields working in academia, industry, health care or for the government. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Research team
- Mark AlberPI
- Uduak Z George
- Weitao Chen
- Heyrim Cho
- Yiwei Wang
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