Soft materials such as colloids and polymers often exhibit a variety of mesoscopic structures that are governed merely by weak physical interactions. Due to these intermediate structures, they can be easily taken out of thermal equilibrium by introducing external stimuli such as a shear flow and electromagnetic fields. This thesis...
Connecting structure and function in nanoscale engineered materials and devices relies on the analysis of the fundamental arrangement of matter, frequently under dynamic conditions. The demand to image structures at fundamental length scales has touched inorganic materials, biology, and frequently hybrid hard/soft materials with unique phenomena driven by heterogeneous components....
The theory of how humans and machines control and communicate with each other is at the core of the scientific field known as Human-Robot Interaction (HRI). Researchers in this sub-discipline of robotics are therefore particularly interested in developing methods to chuppahreduce the inherent friction in this communication and control channel....
Connected and automated vehicle (CAV) technology is a disruptive transportation development with potentially transformative impacts on society and the economy. CAV systems promise to significantly reduce human-caused road crashes, improve traffic flow performance, and lower pollutant emissions. However, realizing those benefits requires strategic planning for the deployment of CAV systems...
Heterogeneous materials have been emerging and playing essential roles in various engineering and scientific fields. They usually include multiple phases of materials to create unique properties that are not accessible to their homogeneous counterparts. The traditional design approach in the material science community is to use trial-and-error iteratively, which is...
Machine learning and symbolic reasoning have been two main approaches to build intelligent systems. Symbolic reasoning has been used in many applications by making use of expressive symbolic representations to encode prior knowledge, conduct complex reasoning and provide explanations. Recently, machine learning has enabled various successful applications by learning from...
In this work, we explore the utility of the three main types of neural networks: feed forward, convolutional, and recurrent. While using these networks, we develop a new way to model multiagent trajectory data, explore the use of multiple activation functions for neurons at each layer of a neural network,...
A central question in neuroscience is how the brain plans movements. Here, I apply neural data analysis and machine learning methods to better understand both eye and arm movement planning, in particular focusing on naturalistic settings. First, I built encoding models to investigate the factors that led to neural activity...
Social media such as Twitter has risen as a powerful new communication medium for disseminating information on news, personal interests, experiences, and opinions. On social media, people talk about their lifestyle, health conditions and symptoms, search information on treatment options, and connect with people who have been through similar medical...