Every complex challenge has a story.
Voices of Biocomplexity (VoBI) is a conversation series from the University of Virginia's Biocomplexity Institute. Through podcasts, videos, blogs, and panel discussions, VoBI brings together researchers and practitioners to explore the ideas, data, and science behind today's most pressing challenges.
From infectious diseases and food systems to artificial intelligence, resilient infrastructure, workforce transformation, and beyond, our conversations examine how seemingly separate systems are deeply interconnected. By combining expertise in modeling, simulation, artificial intelligence, network science, high-performance computing, and data science, our researchers help decision makers better understand complexity, anticipate change, and evaluate possible solutions.
Whether you're a scientist, policymaker, student, or simply curious about the science behind complex systems, we invite you to join the conversation.
Ep 1: The Supercomputer I Didn't Understand
What makes China's new CPU-powered supercomputer so remarkable? Erin Raymond talks with Parantapa Bhattacharya about CPUs, GPUs, and why this headline matters far beyond the world of computing.
Ep. 2: The Pest I'd Never Heard Of
What if one of the biggest threats to our food supply was something you'd never even heard of? Join Abhijin Adiga, Kristy Hall, Vidya Mani, and Samarth Swarup as they discuss the New World screwworm and how this tiny parasite could have far-reaching impacts on cattle, food systems, supply chains, and the economy.
Ep. 3: The Outbreak I Didn't Understand
Measles is reappearing in communities across the US. Ebola continues to emerge in parts of Africa. Although these disease are very different, they raise many of the same questions: How do outbreaks spread? When should we be concerned? How do public health officials decide where to focus resources? And how can modeling help communities prepare before an outbreak becomes a crisis? Join Bryan Lewis, Srini Venkatramanan, and Erin Raymond for a conversation about how network science, computational modeling, and digital twins help researchers understand disease transmission, evaluate response strategies, and support better decision-making before, during, and after an outbreak.
Ep. 4: The Forecast I Didn't Trust
How do we know what flu season will look like before it happens? BI researcher Aniruddha Adiga takes us inside the CDC’s FluSight forecasting network to explore how dozens of models, changing data, and plenty of uncertainty come together to help anticipate what may happen next.
