The recognition of individuals as sufficiently "Darwinian" entities for natural selection has led to the exploration of clades as alternative units of selection to species in the field of philosophy of biology. Previous research has demonstrated that clades meet the criteria of "Darwinian" individuals, intriguing philosophers to explain natural selection at the clade level. This research employs an Abstract Data Type (ADT) approach from computer science, constructing a data structure (DS), and attempts to implement the clades ADT both with and without species. The objective is to scrutinize the inner structure of clade and unearth the interplay between clades and species, a relationship not explicitly implied in their definitions. Preliminary findings affirm the technical feasibility of implementing clades ADT as a clade-tree data structure with species, while the feature of each level of clades remains unclear: (1) Issues of trait identification emerge when assigning properties to organisms within clades; (2) The empirical nature of the data used to construct the data structure representing clades limits holistic demonstration of evolution. On the other hand, a clade-tree data structure without species encounters challenges: (1) Historical organisms within inner stages cannot be distinctly separated without defined species-like boundaries (2) If properties are specified to species-level, the species-free intention of the data structure becomes questionable. The emergence of a dependency on species introduces a compelling reason for reconsidering the ability of clades in explaining natural selection, particularly for those philosophers who oppose species as a unit of selection.

The measurement problem is the challenge of reconciling the probabilistic and deterministic aspects of Quantum Mechanics. In this study, our primary aim is to unravel the measurement problem by investigating the possibility that quantum collapse occurs according to the probabilities presented by Born's Rule due to a perturbation on the system, appearing during the measurement process. Our group employs a multifaceted approach, where we examine the interplay between time dynamics and classical limits, alongside the influence of time-(in)dependent perturbations. Computational simulations serve as our primary tool in this exploration. One part of our group worked with a 3-well system with a time-independent perturbation, another part looked at a 2-well system with a time-dependent perturbation, and the last part saw what a time-independent perturbation does to a 2D-well system. We anticipate that our investigations will uncover critical parameters that are expected to yield probabilities consistent with Born's Rule, a foundational principle of Quantum Mechancis. This research points towards a potential reconsideration of quantum collapse as a dynamical, affected by the perturbation introduced by measurement. While preliminary, these findings contribute to the ongoing discourse in Quantum Mechanics and may offer insights for future theoretical developments and applications.

Deep brain stimulation (DBS) is currently being studied as a potential treatment for Alzheimer’s Disease (AD). At this time, little is known about how prospective users of such devices view this kind of surgical intervention. User-centered design recommends early input from potential users of devices to ensure that their needs and values are recognized in the design process. From February 2021 to January 2022, 34 qualitative interviews were conducted with individuals who are at risk for dementia due to factors including family history, genetic biomarkers, or mild cognitive impairment. Subjects were asked for their perspectives on the hypothetical use of DBS devices to assist individuals living with dementia. One focus for such a hypothetical device is the improvement of short-term memory. My research examines interviewees’ perspectives on the value of improved memory as well as the value of forgetting, and how their stance informs their perspective on and personal interests in the hypothetical use of DBS to treat AD. Using Atlas.ti for coding and qualitative analysis, I found that a small number of interviewees expressed complete enthusiasm for, or complete rejection of, the device. The majority of participants were intrigued while concerned. I show how these interviewees answered questions such as, “Do you think there are any downsides to having a better memory?” and/or, “Do you think there is value in forgetting” in ways that suggest nuanced perspectives on the value of memory and forgetting. They voice concerns regarding potential drawbacks of the hypothetical memory device in relation to risk, trauma, and caring relations. As clinical trials for DBS in AD continue, understanding the values and concerns of prospective users will be vital information in both the design process and successful clinical trials.

On June 29, 2023, the United States Supreme Court ruled that using affirmative action in college admissions is unconstitutional in the case, Students for Fair Admissions, Inc. v. President and Fellows of Harvard College. This research analyzes arguments presented by both parties to reveal the effects of this policy removal on the future of underrepresented minority students applying to college. I analyze Harvard’s admission statistics through regression models cultivated by each party’s expert witness to identify the lack of true diversity in Harvard’s admission process. The statistical findings the experts present highlight the use of the Asian American experience to justify the removal of affirmative action measures in higher education. Additionally, I conduct a complex legal analysis of prior Supreme Court cases through the lens of reparation jurisprudence to expose the lucrative, and performative, system of affirmative action in higher education. The Court’s decision to remove affirmative action requires universities to develop a new form of admission criteria that aids underrepresented minority students in the college admission process. Statistical evidence provided by the Department of Education and economist, Richard D. Kahlenberg, points to a new form of affirmative action that considers varying intersectional factors to develop a complex method of class-based affirmative action. Such studies identify the benefits of looking at various demographic factors contributing to an applicant’s experience to cultivate a diverse class of students that goes deeper than race.