Community sense and response systems

The proliferation of smartphones and other internet-enabled, sensor-equipped consumer devices enables us to sense and act upon the physical environment in unprecedented ways. This thesis considers Community Sense-and-Response (CSR) systems, a new class of web application for acting on sensory data gathered from participants' personal smart devices. The thesis describes how rare events can be reliably detected using a decentralized anomaly detection architecture that performs client-side anomaly detection and server-side event detection. After analyzing this decentralized anomaly detection approach, the thesis describes how weak but spatially structured events can be detected, despite significant noise, when the events have a sparse representation in an alternative basis. Finally, the thesis describes how the statistical models needed for client-side anomaly detection may be learned efficiently, using limited space, via coresets.

The Caltech Community Seismic Network (CSN) is a prototypical example of a CSR system that harnesses accelerometers in volunteers' smartphones and consumer electronics. Using CSN, this thesis presents the systems and algorithmic techniques to design, build and evaluate a scalable network for real-time awareness of spatial phenomena such as dangerous earthquakes.

An in vitro biomolecular breadboard for prototyping synthetic biological circuits

Biomolecular circuit engineering is critical for implementing complex functions in vivo, and is a baseline method in the synthetic biology space. However, current methods for conducting biomolecular circuit engineering are time-consuming and tedious. A complete design-build-test cycle typically takes weeks' to months' time due to the lack of an intermediary between design ex vivo and testing in vivo. In this work, we explore the development and application of a "biomolecular breadboard" composed of an in-vitro transcription-translation (TX-TL) lysate to rapidly speed up the engineering design-build-test cycle. We first developed protocols for creating and using lysates for conducting biological circuit design. By doing so we simplified the existing technology to an affordable ($0.03/uL) and easy to use three-tube reagent system. We then developed tools to accelerate circuit design by allowing for linear DNA use in lieu of plasmid DNA, and by utilizing principles of modular assembly. This allowed the design-build-test cycle to be reduced to under a business day. We then characterized protein degradation dynamics in the breadboard to aid to implementing complex circuits. Finally, we demonstrated that the breadboard could be applied to engineer complex synthetic circuits in vitro and in vivo. Specifically, we utilized our understanding of linear DNA prototyping, modular assembly, and protein degradation dynamics to characterize the repressilator oscillator and to prototype novel three- and five-node negative feedback oscillators both in vitro and in vivo. We therefore believe the biomolecular breadboard has wide application for acting as an intermediary for biological circuit engineering.

Cryogenic Silicon Optical Reference Cavities

Thermodynamical fluctuations in temperature and position exist in every physical system, and show up as a fundamental noise limit whenever we choose to measure some quantity in a laboratory environment. Thermodynamical fluctuations in the position of the atoms in the dielectric coatings on the mirrors for optical cavities at the forefront of precision metrology (e.g., LIGO, the cavities which probe atomic transitions to define the second) are a current limiting noise source for these experiments, and anything which involves locking a laser to an optical cavity. These thermodynamic noise sources scale physical geometry of experiment, material properties (such as mechanical loss in our dielectric coatings), and temperature. The temperature scaling provides a natural motivation to move to lower temperatures, with a potential huge benefit for redesigning a room temperature experiment which is limited by thermal noise for cryogenic operation.

We design, build, and characterize a pair of linear Fabry-Perot cavities to explore limitations to ultra low noise laser stabilization experiments at cryogenic temperatures. We use silicon as the primary material for the cavity and mirrors, due to a zero crossing in its linear coefficient of thermal expansion (CTE) at 123 K, and other desirable material properties. We use silica tantala coatings, which are currently the best for making high finesse low noise cavities at room temperature. The material properties of these coating materials (which set the thermal noise levels) are relatively unknown at cryogenic temperatures, which motivates us to study them at these temperatures. We were not able to measure any thermal noise source with our experiment due to excess noise. In this work we analyze the design and performance of the cavities, and recommend a design shift from mid length cavities to short cavities in order to facilitate a direct measurement of cryogenic coating noise.

In addition, we measure the cavities (frequency dependent) photo-thermal response. This can help characterize thermooptic noise in the coatings, which is poorly understood at cryogenic temperatures. We also explore the feasibility of using the cavity to do macroscopic quantum optomechanics such as ground state cooling.

Neural network design for switching network control

A neural network is a highly interconnected set of simple processors. The many connections allow information to travel rapidly through the network, and due to their simplicity, many processors in one network are feasible. Together these properties imply that we can build efficient massively parallel machines using neural networks. The primary problem is how do we specify the interconnections in a neural network. The various approaches developed so far such as outer product, learning algorithm, or energy function suffer from the following deficiencies: long training/ specification times; not guaranteed to work on all inputs; requires full connectivity.

Alternatively we discuss methods of using the topology and constraints of the problems themselves to design the topology and connections of the neural solution. We define several useful circuits-generalizations of the Winner-Take-All circuitthat allows us to incorporate constraints using feedback in a controlled manner. These circuits are proven to be stable, and to only converge on valid states. We use the Hopfield electronic model since this is close to an actual implementation. We also discuss methods for incorporating these circuits into larger systems, neural and nonneural. By exploiting regularities in our definition, we can construct efficient networks. To demonstrate the methods, we look to three problems from communications. We first discuss two applications to problems from circuit switching; finding routes in large multistage switches, and the call rearrangement problem. These show both, how we can use many neurons to build massively parallel machines, and how the Winner-Take-All circuits can simplify our designs.

Next we develop a solution to the contention arbitration problem of high-speed packet switches. We define a useful class of switching networks and then design a neural network to solve the contention arbitration problem for this class. Various aspects of the neural network/switch system are analyzed to measure the queueing performance of this method. Using the basic design, a feasible architecture for a large (1024-input) ATM packet switch is presented. Using the massive parallelism of neural networks, we can consider algorithms that were previously computationally unattainable. These now viable algorithms lead us to new perspectives on switch design.

An integrated design approach to power systems : from power flows to electricity markets

Power system is at the brink of change. Engineering needs, economic forces and environmental factors are the main drivers of this change. The vision is to build a smart electrical grid and a smarter market mechanism around it to fulfill mandates on clean energy. Looking at engineering and economic issues in isolation is no longer an option today; it needs an integrated design approach. In this thesis, I shall revisit some of the classical questions on the engineering operation of power systems that deals with the nonconvexity of power flow equations. Then I shall explore some issues of the interaction of these power flow equations on the electricity markets to address the fundamental issue of market power in a deregulated market environment. Finally, motivated by the emergence of new storage technologies, I present an interesting result on the investment decision problem of placing storage over a power network. The goal of this study is to demonstrate that modern optimization and game theory can provide unique insights into this complex system. Some of the ideas carry over to applications beyond power systems.

Structure-Guided Design and Biophysical Characterization of Novel Anti-HIV Reagents

Despite over 30 years of effort, an HIV-1 vaccine that elicits protective antibodies still does not exist. Recent clinical studies have identified that during natural infection about 20% of the population is capable of mounting a potent and protective antibody response. Closer inspection of these individuals reveal that a subset of these antibodies, recently termed potent VRC01-like (PVL), derive exclusively from a single human germline heavy chain gene. Induced clonal expansion of the B cell encoding this gene is the first step through which PVL antibodies may be elicited. Unfortunately, naturally occurring HIV gp120s fail to bind to this germline, and as a result cannot be used as the initial prime for a vaccine regimen. We have determined the crystal structure of an important germline antibody that is a promising target for vaccine design efforts, and have set out to engineer a more likely candidate using computationally-guided rational design.

In addition to prevention efforts on the side of vaccine design, recently characterized broadly neutralizing anti-HIV antibodies have excellent potential for use in gene therapy and passive immunotherapy. The separation distance between functional Fabs on an antibody is important due to the sparse distribution of envelop spikes on HIV compared to other viruses. We set out to build and characterize novel antibody architectures by incorporating structured linkers into the hinge region of an anti-HIV antibody b12. The goal was to observe whether these linkers increased the arm-span of the IgG dimer. When incorporated, flexible Gly4Ser repeats did not result in detectable extensions of the IgG antigen binding domains, by contrast to linkers including more rigid domains such as β2-microglobulin, Zn-α2-glycoprotein, and tetratricopeptide repeats (TPRs). This study adds an additional set of linkers with varying lengths and rigidities to the available linker repertoire, which may be useful for the modification and construction of antibodies and other fusion proteins.