Welcome
I am Piklu Mallick, a postdoctoral researcher working at the intersection of computational physics, Bayesian statistics, and public health. I hold a PhD in Physics from Georg-August-Universität Göttingen, completed in close collaboration with the Max Planck Institute for Dynamics and Self-Organization (MPIDS), where my thesis focused on the complex interactions of infectious disease and social dynamics.
My research combines mechanistic epidemic modeling with hierarchical Bayesian frameworks (using PyMC) to quantify how human behavior, interventions, and social feedback loops shape the course of an epidemic. This foundation is exemplified by my work on HIV PrEP dynamics, published in PNAS, and by my broader work on COVID-19 non-pharmaceutical interventions in Germany and India. I am currently expanding this line of work by exploring how Large Language Models and Generative AI can be used to model more realistic human decision-making within epidemiological simulations.
Currently, I am working as a postdoc in both the Max Planck Institute for Dynamics and Self-Organization in Göttingen and the Institute for Chemistry and Biology of the Marine Environment (ICBM) in Oldenburg. Across both roles, I focus on quantitative modeling, Bayesian inference, and building reproducible, interactive tools for scientific communication.
What I work on
- Bayesian inference and hierarchical modeling (PyMC) of behavioral and epidemiological feedback loops
- Compartmental and network-based epidemic models (SIR/SEIR, agent-based simulation)
- Integrating Generative AI and LLMs into epidemiological simulation of human behavior
- Interactive data visualization and scientific communication using Python, JavaScript, HTML, and CSS
Outside of research, I enjoy hiking, rock climbing, reading, and learning new programming languages, and I am an active member of the Effective Altruism community.