Jing Chen

About

Jing Chen is an Associate Professor of Biological Sciences at Virginia Tech, located in Derring Hall. Her research focuses on theoretical and computational modeling of cell biology, systems biology, spatiotemporal regulation, and mechano-biochemistry. Her current research interests include coordinated motility in bacterial colonies and mitotic signaling, with an emphasis on understanding the coupling between biological signaling and spatiotemporal regulation and mechanical interactions. She investigates how biological systems self-assemble into highly heterogeneous and dynamic structures, exploring the roles of spatiotemporal regulation and mechanical interactions within biological signaling mechanisms. Chen's work involves integrating experimental data into physically viable models to gain insights into the functional roles of spatiotemporal regulation and mechanical interactions, often working in close collaboration with experimental groups to ensure effective feedback between theory and experiments. Her educational background includes a Ph.D. in Biophysics from the University of California, Berkeley, a M.S. in Mathematics in Bioscience from the Technical University of Munich, and a B.S. in Biology from Fudan University. She completed a postdoctoral fellowship at the National Heart, Lung, and Blood Institute, NIH. Her research aims to deepen understanding of the complex interactions that govern cellular behavior and biological signaling processes.

Research topics

• Virology
• Medicine
• Computer Science
• Computer Security
• International trade
• Business
• Engineering
• Marketing
• Internal medicine
• Environmental health

Selected publications

• Pandemics In Silico: Scaling an Agent-Based Simulation on Realistic Social Contact Networks

  arXiv (Cornell University) · 2024-01-16 · 1 citations

  preprintOpen access

  Preventing the spread of infectious diseases requires implementing interventions at various levels of government and evaluating the potential impact and efficacy of those preemptive measures. Agent-based modeling can be used for detailed studies of epidemic diffusion and possible interventions. Modeling of epidemic diffusion in large social contact networks requires the use of parallel algorithms and resources. In this work, we present Loimos, a scalable parallel framework for simulating epidemi…

  PublisherOA PDFDOI

• Scenario Projections of COVID-19 Burden in the US, 2024-2025

  UNC Libraries · 2025-09-25

  articleOpen access

  Importance: COVID-19 remains a disease with high burden in the US, prompting continued debate about optimal targets for annual vaccination. Objective: To project COVID-19 burden in the US for April 2024 to April 2025 under 6 scenarios of immune escape (20% and 50% per year) and levels of vaccine recommendation (no recommendation, vaccination for individuals at high risk only, vaccination for all eligible groups) and to assess the potential benefit of vaccine recommendations in reducing disease b…

  PublisherDOI

Frequent coauthors

• Madhav Marathe

  200 shared

• Bryan Lewis

  Biocom

  140 shared

• Srinivasan Venkatramanan

  Biocom

  119 shared

• Anil Vullikanti

  University of Virginia

  110 shared

• Henning Mortveit

  University of Virginia

  95 shared

• Stefan Hoops

  University of Virginia

  59 shared

• Aniruddha Adiga

  54 shared

• Achla Marathe

  51 shared

Similar researchers at Virginia Tech

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• Cayelan Careyh-44
• Julie Allenh-43