Foreigner

This written thesis serves as supporting documentation for Foreigner, my MFA Thesis Exhibition. This exhibition reflects my experience as a foreigner, a solitary Chinese man living in the United States. Through embodying my personal experience, my paintings question the relationship between individuals and society. The exhibition is composed of a series of paintings that visualize my personal story as a foreigner living in an incompatible and unacquainted culture. By displaying imagery of myself and my family in frozen moments, the paintings draw viewers into a discussion about personal identity, life philosophy, and culture collision. The exhibition and this thesis expand on topics concerning creative processes, personal motivations, inspirations, and painting techniques

Multi-omics approaches to understand respiratory disease

The main scope of this thesis is to improve our understanding of the biological mechanisms of allergic disease, in particular asthma and rhinitis, by applying multi-omics approaches. We collected multi-omics data from the genome, epigenome, bulk and single-cell transcriptome, and the exposome. By applying association and machine learning approaches, we investigated epigenetic mechanisms of the development of allergic disease, revealed cell-type specific molecular regulation of asthma risk variants, identified biomarkers of allergy, and provided a prediction tool for allergic disease

An Ensemble of 2.5D ResUnet Based Models for Segmentation for Kidney and Masses

The automatic segmentation of kidney, kidney tumor and kidney cyst on Computed Tomography (CT) scans is a challenging task due to the indistinct lesion boundaries and fuzzy texture. Considering the large range and unbalanced distribution of CT scans' thickness, 2.5D ResUnet are adopted to build an efficient coarse-to-fine semantic segmentation framework in this work. A set of 489 CT scans are used for training and validation, and an independent never-before-used CT scans for testing. Finally, we demonstrate the effectiveness of our proposed method. The dice values on test set are 0.954, 0.792, 0.691, the surface dice values are 0.897, 0.591, 0.541 for kidney, tumor and cyst, respectively. The average inference time of each CT scan is 20.65s and the max GPU memory is 3525MB. The results suggest that a better trade-off between model performance and efficiency.Comment: 7 pages, 2 figure

Hello, Twitter Bot!:Towards a Bot Ethics of Response and Responsibility

In this paper, we explore the troubles and potentials at stake in the developments and deployments of lively technologies like Twitter bots, and how they challenge traditional ideas of ethical responsibility. We suggest that there is a tendency for bot ethics to revolve around the desire to differentiate between bot and human, which does not address what we understand to be the cultural anxieties at stake in the blurring boundaries between human and technology. Here we take some tentative steps towards rethinking and reimagining bot-human relationships through a feminist ethics of responsibility as response by taking as our starting point our own experience with bot creation, the Twitter bot “Hello30762308.” The bot was designed to respond with a “hello” to other Twitter users’ #hello, but quickly went in directions not intended by its creators.

DECOUPLING ACCOUNTABILITY AND LIABILITY:CASE STUDY ON THE INTERIM MEASURES FOR THE OPENING OF PUBLIC DATA IN SHANGHAI

As open public data initiatives have become prevalent among local and national governments across the globe with promises of benefits such as increased accountability, challenges, especially the governments’ lack of willingness to open public data, have also begun to emerge. Existing governance research on open public data primarily focuses on how open public data can increase the accountability of public bodies. The important steps in achieving accountability are, however, ignored. In this paper, we view the perceived risk of liability as a barrier for the public bodies to disclose their data in the first place, and hence to achieve accountability as a desired outcome. We explore the link between perceived risk of liability and accountability by looking into the recently announced Interim Measures for the Opening of Public Data in Shanghai as an example of a local regulatory initiative of open public data. Our findings show that by identifying the specific data entities and outlining their corresponding duties, the interim measures clarify the roles of different public bodies and under what conditions they can incur liability. By introducing an exemption clause, they also provide public bodies with legal flexibility to cope with uncertain consequences of data utilization. In this way, we argue that the interim measures, outlining duties for specific entities in data opening in accounting for the consequences of data utilization while remaining flexible due to their temporality, constitute a novel regulatory approach towards reducing the legal uncertainty around perceived risks of liability in the area of open public data, hence potentially contributing to increased accountability