PhD Thesis Defense
Carnegie Mellon University
Designing Interactive Systems for Community Citizen Science
Abstract: Citizen science forges partnerships between experts and citizens through collaboration and has become a trend in public participation in scientific research over the past decade. Besides this trend, public participation can also contribute to participatory democracy, which empowers citizens to advocate for their local problems. This strategy supports citizens to form a community, increase [...]
Carnegie Mellon University
Visual Learning with Minimal Human Supervision
Abstract: Machine learning models have led to remarkable progress in visual recognition. A key factor driving this progress is the abundance of labeled data. Unfortunately, this reliance on lots of labeled data is also a key limitation in the rapid development and deployment of vision systems. These visual recognition systems show poor performance on concepts [...]
Carnegie Mellon University
Robot Design for Everyone: Computational Tools that Democratize the Design of Robots
Abstract: A grand vision in robotics is that of a future wherein robots are integrated in daily human life just as smart phones and computers are today. Such pervasive integration of robots would require faster design and manufacturing of robots that cater to individual needs. For instance, people would be able to obtain customized smart [...]
Carnegie Mellon University
Robust Soft-Matter Robotic Materials
Abstract: Emerging applications in wearable computing, human-machine interaction, and soft robotics will increasingly rely on new soft-matter technologies. These soft-matter technologies are considered inherently safe as they are primarily composed of intrinsically soft materials---elastomers, gels, and fluids. These materials provide a method for creating soft-matter counterparts to traditionally rigid devices that exhibit the mechanical compliance [...]
Carnegie Mellon University
Provably Optimal Design of a Brain-Computer Interface
Abstract: Brain-computer interfaces are in the process of moving from the laboratory to the clinic. These devices act by reading neural activity and using it to directly control a device, such as a cursor on a computer screen. Over the past two decades, much attention has been devoted to the decoding problem: how should recorded [...]
Carnegie Mellon University
Extensions of the Principal Fiber Bundle Model for Locomoting Robots
Abstract: Our goal is to establish a rigorous formulation for modeling the locomotion of a broad class of robotic systems. Recent research has identifi ed a number of systems with the structure of a principal fiber bundle. This framework has led to a number of tools for analysis and motion planning applicable to various robotic [...]
Carnegie Mellon University
Safe Data Gathering in Physical Spaces
Abstract: Reliable and efficient acquisition of data from physical spaces has widespread applications in industry, policy, defense, and humanitarian work. Unmanned Aerial Vehicles (UAVs) are an excellent choice for data gathering applications, due to their capability of gaining information at multiple scales. A robust data gathering system needs to reason about multi-resolution nature of information [...]
Carnegie Mellon University
Learning to learn from simulation: Using simulations to learn faster on robots
Abstract: Learning for control is capable of acquiring controllers in novel task scenarios, paving the path to autonomous robots. However, typical learning approaches can be prohibitively expensive in terms of robot experiments, and policies learned in simulation do not transfer directly due to modelling inaccuracies. This encourages learning information from simulation that has a higher [...]
Carnegie Mellon University
Learning with Clusters
Abstract: Clustering, the problem of grouping similar data, has been extensively studied since at least the 1950's. As machine learning becomes more prominent, clustering has evolved from primarily a data analysis tool into an integrated component of complex robotic and machine learning systems, including those involving dimensionality reduction, anomaly detection, network analysis, image segmentation and [...]
Carnegie Mellon University
Sensing, Measuring, and Modeling Social Signals in Nonverbal Communication
Abstract: Humans convey their thoughts, emotions, and intentions through a concert of social displays: voice, facial expressions, hand gestures, and body posture, collectively referred to as social signals. Despite advances in machine perception, machines are unable to discern the subtle and momentary nuances that carry so much of the information and context of human communication. [...]