This dissertation presents three independent research projects. The first chapter of this thesis studies the impact of a large-scale adult learning program on child health. The study exploits the exogenous variation created by the program implementation in a regression discontinuity framework using a nationally representative household survey. The study finds that children whose mothers are eligible for the program are less undernourished, with improved health outcomes measured by height-for-age and weight-for-age z-scores. The results are likely driven by increased diversity in children’s diets and higher labor force participation of mothers. There is no evidence for changes in fertility behavior and utilization of healthcare services. The results translate to a large social gain induced by favorable child health outcomes, suggesting additional scope for well-designed adult learning programs in developing countries to raise overall welfare.

The second chapter investigates the impact of a teacher’s effectiveness on her students’ future peers. Good teachers affect both the short- and long-term achievements of their students. However, teachers might also be able to influence short- and long-term outcomes of future peers of their students. Using administrative data from a Southern state, this study quantifies teacher effects on such spillovers. The identification comes from the natural transitions of students from multiple elementary schools into a single middle school. The study finds that the positive impact of teachers on their students spills over to affect their students’ future peers with improved cognitive outcomes in middle school and long-run outcomes in high school. The findings indicate that such unaccounted spillovers underestimate the actual effectiveness of a teacher.

The third chapter measures the impact of two main signals of tertiary-level human capital accumulation, college quality, and certification, on the first stage of the hiring process in India. This experimental study involved sending fake resumes to job postings for recent engineering graduates across major cities. The study finds no impact on callbacks of having graduated from a mid-tier college ranked in the top 300 relative to one outside of the top 1000. There is also no impact of scoring in the highest as opposed to the lowest quartile of a widely-used certification test. The study does not find evidence of gender discrimination or heterogeneity by company characteristics.

Energy consumption of the modern wireless communication systems is rapidly growing due to the ever-increasing data demand and the advanced solutions employed in order to address this demand, such as multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) techniques. These MIMO systems are power hungry, however, they are capable of changing the transmission parameters, such as number of spatial streams, number of transmitter/receiver antennas, modulation, code rate, and transmit power. They can thus choose the best mode out of possibly thousands of modes in order to optimize an objective function. This problem is referred to as the link adaptation problem.

In this work, we focus on the link adaptation for energy efficiency maximization problem, which is defined as choosing the optimal transmission mode to maximize the number of successfully transmitted bits per unit energy consumed by the link. We model the energy consumption and throughput performances of a MIMO-OFDM link and develop a practical link adaptation protocol, which senses the channel conditions and changes its transmission mode in real-time. It turns out that the brute force search, which is usually assumed in previous works, is prohibitively complex, especially when there are large numbers of transmit power levels to choose from. We analyze the relationship between the energy efficiency and transmit power, and prove that energy efficiency of a link is a single-peaked quasiconcave function of transmit power. This leads us to develop a low-complexity algorithm that finds a near-optimal transmit power and take this dimension out of the search space. We further prune the search space by analyzing the singular value decomposition of the channel and excluding the modes that use higher number of spatial streams than the channel can support. These algorithms and our novel formulations provide simpler computations and limit the search space into a much smaller set; hence reducing the computational complexity by orders of magnitude without sacrificing the performance.

The result of this work is a highly practical link adaptation protocol for maximizing the energy efficiency of modern wireless communication systems. Simulation results show orders of magnitude gain in the energy efficiency of the link. We also implemented the link adaptation protocol on real-time MIMO-OFDM radios and we report on the experimental results. To the best of our knowledge, this is the first reported testbed that is capable of performing energy-efficient fast link adaptation using PHY layer information.

The topological transitions of the grain boundary network during grain growth under uniform grain boundary energies are believed to be known. However, this is not true for more realistic materials with varying grain boundary energies that, in principle, allow many different grain boundary configurations. A grain growth simulation for such a material therefore requires a procedure to enumerate all possible topological transitions and select the most energetically favorable one. Such a procedure is developed and implemented here for a microstructure represented by a volumetric finite element mesh. The method is implemented as a C++ library called VDlib based on SCOREC, an open source massively parallelizable library for finite element simulations with adaptive meshing. To test the implementation, a Voronoi tessellated microstructure composed of one hundred grains is generated and evolved under constant grain boundary properties until half of the grains remained. The evolution of the individual grains is compared to what is expected from the MacPherson-Srolovitz relation and is found to be in good match.

As with all numerical techniques, it is important to identify systematic sources of error. Such studies for grain growth simulations are either missing from or not uniform across the literature. To address this issue and enable comparison across grain growth simulations, a set of benchmark cases, one for each boundary type of surfaces, lines, and points with analytical solutions are identified. These are used to compare a recently developed discrete-interface method for microstructure evolution to a state of the art diffuse interface (multiphase field method). In each case, the discrete method is found to meet or outperform the multiphase field method in terms of accuracy for comparable levels of refinement, demonstrating its potential efficacy as a numerical approach for microstructure evolution.

Last, a novel invariant of ideal grain growth process is defined that ideally can be used to calculate the number of topological entities in a microstructure and only changes as the topology changes. VDlib is used to test the invariant on a simulated microstructure composed of a periodic arrangement of Kelvin cells. A convergence study reveals that the invariant converges to the ideal case with increasing levels of refinement, however predicting the number of entities without bounds on number of entities proves unpractical. Two error measures based on this novel invariant are proposed which can potentially be used to quantitavely measure how much simulations deviate from ideal grain growth process and experimental microstructures.