The advent of metamaterials—hierarchical structures that manifest properties beyond those found in nature through geometry rather than material composition—inspired new possibilities and research in many fields. In mechanics, periodic metamaterials exhibit behaviors ranging from unprecedented compressibility to extreme stiffness. Numerous geometric classes of metamaterials with these properties have been discovered,...
Wearable visual systems, such as ego-centric wearable cameras, have failed to integrate into everyday life. We have witnessed the abandonment of wearable visual systems as consumer devices (e.g., Google Glass) and as research tools (e.g., SenseCam). While it is natural for some technologies to die out, visual wearable systems are...
In this dissertation, we aim to develop algorithms that achieve optimality with provable complexity guarantees under various settings in reinforcement learning (RL). Specifically, in Markov decision processes (MDPs), we study single-agent and multi-agent online RL, respectively, and offline RL under the presence of unobserved confounders. Single-agent online RL. We design...
In recent years, machine learning on graphs (or networks) has gone from a niche topic with only a few active researchers worldwide, to a heavily invested field with novel use cases for dealing with relationships and/or interactions within complex systems in the natural and social sciences. Traditionally, choosing the right...
X-ray imaging at nano and micro-scale is of great importance for the material science and defense industry. Large penetration depth and low wavelength of x-rays offer an important potential to image objects at high resolution and in a non-invasive process. While the ever-growing community is pursuing novel applications and looking...
Visual Question Answering (VQA) increasingly attracts industry and academia attention. It requires the model to provide a natural language answer by an image and a related natural language question. Meanwhile, it relates to multidisciplinary research such as natural language understanding, visual information retrieval, and multimodal reasoning. As a multimodality task,...
Imagine sitting in a room listening to some friends play a song. Perhaps one friend is playing guitar, another playing bass, and a third is playing drums. The musical content in this scene is extraordinarily complex, yet it contains many types of structure that is easy for us to comprehend....
Wearable-based human activity recognition is well-studied in the machine learning and pervasive computing community. A large corpus of studies focused on using wearable sensors to recognize health-related behaviors that involve high periodicity in the sensed signal, such as sitting, walking, and running. Other activities that occur less frequently throughout the...
Asymmetric relationships between creators and consumers in peer-produced knowledge repositories produce inequitable knowledge representation--or knowledge gaps. These gaps result in unequal access to information, and downstream technologies that leverage peer-produced data perpetuate these inequities. Effective knowledge gap identification represents a necessary first step towards equitable knowledge representation. However, while prior...
The past decade has seen the rapid progress of deep learning, which becomes a game-changing technique in different data-intensive domains, with the availability of large scale data, cost-effective computing hardware and more advanced learning theory and algorithms. Despite of the rapid progress of deep learning methods in daily-life applications, such...