Dissertation Defense Announcements

Emotional ambivalence – the experience of dual-valenced emotions – is becoming increasingly relevant to the process of leadership. Leaders are consistently faced with nuanced, complex situations that simultaneously elicit positive and negative emotions. Despite increased empirical investigations into leader emotional ambivalence at work (Rothman et al., 2017; Rothman & Melwani, 2017), leader emotion theorizing makes critical assumptions that limit understanding of the cognitive and social role of emotional ambivalence in the social process of leadership, including the leaders themselves and those that interact with leaders. I conduct a systematic literature review to show how past work conceptualizing emotional ambivalence as the experience of conflicting emotions and the default treatment of leader emotions as singular can be misleading. In this dissertation, I advance the definition of emotional ambivalence beyond emotional conflict and outline a new integrative process of leader emotions including the appraisal, experience, expression, and perception of complex emotions and their general outcomes.

Binary-phase diffraction gratings are optical components that distribute an incident light beam to diffraction-order directions, due to the periodic modulation of the refractive index within the grating volume. Gratings are essential components in fields like acousto-optics, holography, spectroscopy, and are typically fabricated using lithography. High-efficiency first-order gratings are particularly important in spectroscopy, since first-order spectral diffraction spatially separates the incident wavelengths to be measured. Designing a linear grating consists of iterations of numerical simulations for a given phase profile, to determine grating diffraction efficiencies. The inverse design process, specifying the efficiencies desired and obtaining the phase profile, is very challenging and can lead to unstable solutions. In this research effort, a two-step design process is used. The general parameter ranges are determined first based on design goals, and then more rigorous simulations are performed to “map-out” the diffraction efficiency as a function of a limited solution parameter-space search. The phase profile that matches the design goals is then chosen.
The first lithographic step in grating fabrication is to create a mask for the grating’s features on a photoresist and develop the device profile. Etching the features into the substrate with a reactive-ion plasma process results in a permanent optical component. The study addresses certain fabrication challenges in binary grating fabrication, associated with areal scaling from a 25×25 mm2 surface area to a much larger 101×101 mm2 desired component size. The greatest challenge is to achieve the proper etch depth for the device function, which is mitigated by multiple masking and etching steps.
The Littrow-mount configuration is commonly employed to enhance a grating’s first-order efficiency performance, but can cause ghost images due to light recombination, a problem often controlled with antireflective treatments. Part of the research effort presented here uses random antireflective surface structures (rARSS), which are randomly distributed conical nano-features, etched into dielectric surfaces to minimize their Fresnel reflectivity. These structures were fabricated and tested on cylindrical lenses and freeform elements, showing significant transmission enhancement in the visible spectrum, minimal wide-angle scattering losses, and no notable wavefront distortion. rARSS were then applied to proof-of-concept (POC) reactive-ion plasma-etched (RIPLE) gratings for the VIRUS2 spectrograph, which was designed for Littrow-mount configuration. The rARSS-treated gratings successfully suppressed the undesirable reflection from the zeroth-diffraction order, enhanced the transmitted first-order, and reduced Littrow ghost intensities to four orders of magnitude lower than the transmitted spectrum baseline.
In parallel, a grating beam splitting device composed of two alternating crossed-cell tile first-order diffraction gratings, oriented orthogonal to each-other, was fabricated to function as both a two-way and three-way beam splitter at oblique light incidence. The tiling spatially separates the first-diffraction orders of each grating cell group,
while it overlaps the undeflected zeroth-diffraction order, creating three light-splitting pathways in orthogonal directions in three-dimensions. Each grating type was optimized to separate light in the 1st− and 0th−diffraction order, in ratios 96:1 and 2:1 for the two-way and three-way beam splitter respectively. The result was the projection of three equal intensity spots in space for the three-way beam splitter, and two spots off the axial direction for the two-way a beam splitter.

Busyness, or how busy someone is, has increasingly become a topic of conversation in day-to-day life. Research has previously explored how people use their time and how people perceive their available time, or lack thereof, but there is no clear answer as to why people tell others that they are busy and what it is they are trying to accomplish by doing so. Drawing on impression management research, this paper proposes that people signal to others that they are busy so that the audience has a positive impression of them. The concept of the busyness facade is introduced, which includes behaviors and verbal statements that are intentionally enacted by individuals to signal to others that they have a lot to do or limited available time. Exactly how and why people engage in this busyness facade is explored in two studies using semi-structured interviews and an online, vignette survey. Overall, evidence is found for the existence of busyness facades and a better understanding of how people display busyness is gained, but the studies are unable to identify a clear motive for why busyness facades would be used as an impression management tactic. Additional findings and research directions are discussed.

Causal modeling provides us with powerful counterfactual reasoning and interventional mechanisms to generate predictions under various what-if scenarios. Nevertheless, uncovering causal relationships from observational data presents a considerable challenge, as unobserved confounders, limited sample sizes, and variations in distributions can give rise to misleading cause-effect associations. Models relying on these relationships may perform poorly when spurious correlations do not hold in test cases. To mitigate these challenges, researchers augment causal learning with known causal relations. This dissertation first investigates the incorporation of domain knowledge in structure learning by introducing additional constraints that convey qualitative knowledge about causal relationships. The experimental designs are specifically equipped to evaluate the role of domain knowledge. Secondly, a concept-driven approach is implemented to determine the advantages of incorporating concept-level prior knowledge. Given the invariant nature of causal relationships, the study then showcases the broader applicability of incorporating domain knowledge by employing a machine learning method for learning adsorption energies, illustrating the advantages of harnessing domain knowledge to obtain invariant molecular representations in catalyst screening. Finally, a novel approach is introduced to enhance robustness and out-of-distribution generalization by leveraging gradient agreement across different environments to identify reliable features. Collectively, these experimental designs advance causal discovery and robust machine learning by utilizing prior knowledge and relational invariances, paving the way for future research on integrating domain knowledge and invariance principles into the learning process.