Kai Zhu is interested in global change biology, ecological modeling, and environmental data science, where he enjoys integrating ecological theory with advanced tools in statistics and computer science. His current research focuses on plant and soil responses to environmental change in the coupled natural and human systems, spanning from meter-scale experiments to global-scale analyses. Recent … Read more
One branch of my research considers how to use data and models to improve manufacturing productivity. We look at how to capture streaming data from the factory floor, put it together with models encapsulated in “digital twins”, and use the predictions to better schedule production, plan maintenance, detect anomalies (including cyber-attacks), reconfigure the manufacturing system … Read more
Use deep learning for sub wavelength imaging, data analysis and nanophotonics design.
The Computational Materials Physics group under the direction of Vikram Gavini focuses on developing computational frameworks and algorithms to enable large-scale ab-initio calculations for predictive materials simulations. The two main present thrusts of the group since 2020 are: (i) Developing fast and accurate large-scale density functional theory (DFT) calculations; (ii) Development of a computational framework … Read more
Much of our work focuses on host-parasite coevolution both computationally using populations of self-replicating computer programs (sort of like computer viruses), and experimentally in the lab with bacteria and their viruses (bacteriophage). But that’s not all! We’re deeply interdisciplinary, and broadly interested in ecology and evolution. While I often approach questions from an experimentalist’s perspective, … Read more
Comprehensive investigations of solar, interplanetary, and Earth’s Magnetospheric systems utilizing state-of-the-art in-situ observations and global simulations. The research topics of interest involve critical open science questions, including solar coronal heating, solar wind acceleration and heating processes, magnetospheric dynamics, and space weather predictions. The research tools include statistical data analyses to generate physics-based models. Accomplishments and … Read more
My research interests include the analysis, modeling, design and optimization of transportation systems towards achieving sustainability and economic efficiency. My ongoing research involves investigating the implications of emerging technologies on mobility services and systems. I closely follow the development of new technologies, such as smart mobile devices and apps, sensoring technologies, electric vehicles, drones, and … Read more
My research utilizes computational social science and artificial intelligence to derive contextually informed algorithmic frameworks for understanding individuals and the social systems which influence their behavior, and for supporting positive behavior change within these systems. In particular, I analyze policy and behavior, and apply interactive behavior support and predictive algorithms, within the areas of higher … Read more
The Rabosky lab seeks to understand how and why life on Earth became so diverse. We focus primarily on large-scale patterns of species diversification (speciation and extinction) and on the tempo and mode of phenotypic evolution, to better understand what regulates the “amount” of biodiversity through Deep Time. To this end, we develop theoretical frameworks … Read more