2021 RESEARCH SEED AWARDS

Physical SciencesLife and Medical Sciences | Life, Medical and Physical Sciences | Public Health | Humanities and Social Sciences 

Physical Sciences

Teaching High School Students about Autonomous Aerial Robots
The aim of this proposal is to test the hypothesis that we can prepare high school teachers to teach students about autonomous aerial robots on their own, at scale by 1) providing a project-based curriculum targeted at the high school level on an open-source low-cost autonomous robot with few infrastructure requirements; 2) providing remote professional development workshops for teachers; and 3) pairing teachers with Brown students familiar with the curriculum who will provide help and technical support. We will study the interactions between teachers and curriculum materials, tools, and Brown students who facilitate the learners' conceptual development, and what characteristics our online PD and remote support give rise to these interactions. Our work will assess each of these three interventions by assessing teacher content knowledge as well as self-efficacy. We will also assess the effectiveness with which we can engage students in both urban and suburban districts through hands-on remote learning curricula that emphasize physical hardware, in the hands of the students as well as via remote laboratories. This work has the potential to directly benefit students in Rhode Island, consistent with President Paxson's commitment to Providence public schools. Moreover this funding will provide critical preliminary work enabling us to apply for follow-on funding for larger expansions from NSF and industry resources to grow our project to a nationwide and international effort to teach students about autonomous robotics.
PI: Stefanie Tellex, Associate Professor of Computer Science
Co-PI: Diane Silva Pimentel, Senior Lecturer in Education

Finding the Physics that Matters in Astrophysical and Astro-Particle Analyses with Interpretable Machine Learning
As more and more analyses depend on machine learning, physicists need to understand the biases induced in their models by the training data they use. In many situations they face a tradeoff between two types of data: (1) abundant but low-resolution, synthetic, or otherwise approximate data, and (2) scarce but high-resolution, high-fidelity, or otherwise more realistic data. The ideal would be to correct the biases in the abundant data so that it is more like the scarce data in the ways that affect the predictions of the machine learning models trained on that data. If done, then scientists would have access to higher quality, abundant data. The problem is that, even though it is easy to tell that models trained on each type of data disagree in their predictions, it is hard to tell which aspects of the input are leading to that disagreement. Our proposal is to create a software framework for identifying these key causes of differences.
PI: Stephon Alexander, Professor of Physics
Co-PIs: Stephen Bach, Assistant Professor of Computer Science; Ian Dell’Antonio, Professor of Physics; Richard Gaitskell, Hazard Professor of Physics; Jonathan Pober, Assistant Professor of Physics

Reverse Engineering the Synaptic Cleft - the Search for Quantum Information Processing in the Brain
The interdisciplinary team proposes to test the idea that the fundamental principle of a complex brain operation is quantum processing involving nuclear spins of phosphorus as a neural qubit. This idea originates from a reputable theoretical physicist M. Fisher, UCSB. He identified the hypothetical Posner molecule as one that can protect neural qubits very long times and thereby serve as a working quantum-memory. Our novel approach involves harnessing the properties of nuclear spins to study quantum information processing (QIS) in the brain by reverse engineering specific polymers and biomolecules to provide sufficiently long coherence times required for quantum processing. This is orthogonal to the UCSB’s approach that focuses on the search of Posner molecule. The team members are highly complementary and have a well-established prior record of collaborations. Palmore will synthesize  polymer based biomaterials with appropriate nuclear spin species, while Mitrovic and Walsh will use the nuclear magnetic resonance (NMR) technique to test possible coherence propagation and test whether such bio-materials can be used as a quantum register to process information. The team has identified the appropriate synthesis and patterning of phosphates into specific isotopically labeled and DNA nanostructure. They have also designed the NMR experiment to test the quantum nature of neural signal transmission, and NMR experiments to test nuclear spin coherence. Our long-term goal is to identify essential biomaterial properties required for QIS and quantum signal transmission using nuclear spins of phosphorus. The ultimate goal is synthesis of artificial neural synapses and memory registers.
PI: Vesna Mitrovic, Professor of Physics 
Co-PIs: Tayhas Palmore, Elaine I. Savage Professor of Engineering, Professor of Chemistry; Edward Walsh, Assistant Professor of Neuroscience (Research)

Using Artificial Intelligence to Search for New Physics Underground, on the Ground, and in the Sky
In the past few years, significant developments in high-power, massively parallel computing, made in part possible by the advancement of fast GPUs, FPGAs, and specialized processors, took artificial intelligence (AI) to a qualitatively new level, making it a valuable tool for scientific research. Some of the AI methods, such as supervised and unsupervised machine learning (ML) using deep neural networks, are now being widely deployed in large scientific experiments in particle and astroparticle physics, both for data reconstruction and for unraveling subtle signals over otherwise overwhelming backgrounds. Typical data from these large detectors, organized in a series of “events,” i.e., snapshots of the detector triggered by a certain, interesting activity, naturally allow for massive parallel processing of the data and for identifying characteristic patterns within. We propose to utilize advanced AI methods and a combination of supervised and unsupervised ML algorithms to look for unusual patterns in the data of experiments underground, on the surface of the Earth, and in the sky. More specifically, we will focus on unconventional experimental signatures of new physics in the Brown-led LUX/LZ detectors at the Sanford Underground Research Facility by exploring new methods for identifying heterogenous particle recoil signatures involving both nuclear and electron recoil components, at the CMS experiment at the Large Hadron Collider at CERN by looking for jets with unconventional structure or patterns, and in the sky using forecasting weak gravitational lensing data from the Square Kilometer Array to discern the presence of dark matter substructure using time dependent spatial correlations.
PI: Greg Landsberg, Thomas J. Watson, Sr. Professor of Physics
Co-PIs: Richard Gaitskell, Hazard Professor of Physics; Savvas M Koushiappas, Associate Professor of Physics

Responsive Hydrogel Based pH Regulation of Cancer Tumor Microenvironment to Reduce Metastasis
Cancer cells are known to create acidic extracellular environments through the excretion of acid byproducts due to irregular metabolic pathways. This unusually acidic extracellular tumor microenvironment compared to healthy tissues may be targeted through cancer therapies. Counteracting the pH of the tumor microenvironment in in vivo mouse models by ubiquitous bicarbonate delivery has shown promise. Currently, an effective method of locally regulating the pH of the tumor microenvironment to reduce cancer progression due to acidosis does is lacking and our research aims to fill this important need by developing a responsive hydrogel pH regulating system by demonstrating its efficacy in cancer treatment. We aim to develop a novel biocompatible pH regulating hydrogel that reduces cancer metastasis and invasion by continuously counteracting the acidosis of the extracellular space.  We will conduct in vitro experiments to test proliferation, motility, and invasion of MDA-MB-231 breast cancer cells when exposed to our novel hydrogel. Completion of our study will allow further research into targeted delivery of pH regulating hydrogels in vivo as well as new studies of subcellular cancer cell mechanisms that can be regulated through pH control.
PI: Vikas Srivistava, Assistant Professor of Engineering

Syntheses of Atom-Precise Gold Nanoclusters with In Situ Catalytic Active Sites for Hydrogen Activation and Electrocatalysis
Nanoparticles display properties that are different from bulk materials and in particular can be excellent catalysts for important chemical reactions. However, because of the size and surface inhomogeneity, the mechanisms of catalytic reactions by nanoparticles are often challenging to be deciphered. This project aims at advancing nanochemistry through the syntheses of novel ligand-protected and atom-precise gold nanoclusters with uncoordinated sites, which can serve as well-defined in situ activation centers for catalysis. While there have been major advances in the syntheses of atom-precise nanoclusters, information about the active sites of these nanoparticles in catalytic applications are still challenging to obtain because often times the ligands need to be removed to create active sites that can introduce uncontrolled structural changes. The motivation of this project is to address this challenge by synthesizing ligand-protected nanoclusters with uncoordinated atoms, that can be used as in-situ active sites. The first goal of the project is to find new ligands that allow the syntheses of gold or bimetallic gold nanocluster with precisely-defined size and structure. The second goal is to explore their catalytic properties and obtain preliminary data about hydrogenation reactions and electrocatalysis.
PI: Lai-Sheng Wang, Jesse H. and Louisa D. Sharp Metcalf Professor of Chemistry

Life and Medical Sciences

Defining Neuron-glial Synaptic Interactions in Health and Alzheimer's Disease
If current prevention and intervention strategies remain the same, one in three of us will be diagnosed with Alzheimer’s disease (AD) in our lifetime. Therefore, it is critically important to discover new, effective treatments, and the key to doing so is to fully understand how AD develops. Unfortunately, this understanding is limited by the absence of an appropriate humanized model system and the deficiency in general knowledge to guide an experimental path forward are the major reasons for this gap. To tackle such a challenge, our two research teams have combined our distinct expertise and devised original techniques based on stem cell technology and computational genomics, to study the neuron-glial communications that become disrupted in AD and aged brains. Specifically, the objective of this pilot project is to develop an integrated platform to discover the nature of direct synaptic interactions between neurons and oligodendroglia in both healthy and diseased individuals. The work proposed here represents a novel research horizon for the field, ultimately aimed at inspiring a new therapeutic logic for AD and relevant brain aging disorders. We will leverage our multidisciplinary expertise uniquely established at Brown to couple cellular reprogramming methods with modern genome scanning and editing techniques. Our preliminary data have provided the very first evidence supporting the neuron-OPC synaptic mechanism as an emerging therapeutic target for further translation. Our approaches are amenable to contemporary studies of neurodegeneration and aging beyond AD and we hope to extend our collaboration with Brown’s vibrant faculty to further synergize our discoveries.
PI: Yu-Wen Alvin Huang, GLF Translational Assistant Professor of Molecular Biology, Cell Biology and Biochemistry
Co-PI: Ashley E. Webb, Richard and Edna Salomon Assistant Professor of Molecular Biology, Cell Biology and Biochemistry

Structure and Post-Translational Modifications of Candida Transcription Factors and their Impact on Phase Separation
The ability of macromolecules to undergo liquid-liquid phase separation (LLPS) is now recognized as underlying a number of key biological phenomena. Our studies have revealed that transcriptional regulation in the pathogenic fungus Candida albicans is controlled via LLPS, as multiple transcription factors can come together to form phase-separated condensates that are critical to the regulation of transcription networks in this species. This mechanism has been directly linked to the presence of prion-like domains (PrLDs) in transcription factors (TFs) that promote their propensity to undergo LLPS and thereby form transcriptional hubs. In this proposal, we seek to determine how structural features and post-translational modifications (PTMs) alter the ability of TFs to undergo LLPS. A number of recent studies have shown that LLPS processes can be exquisitely sensitive to both PTMs and transient secondary structures that can impact phase separation. This is particularly relevant to fungal transcription networks where domains of unknown structure contribute to function and PTMs may enable cells to rapidly respond to external stimuli and activate an appropriate transcriptional response. We will therefore seek to define the structures and PTMs associated with the master TFs in C. albicans networks, and also examine how these features impact LLPS and transcriptional output by these factors. These findings are expected to have broad significance to the regulation of TF networks, and will provide fundamental insights as to how these features can regulate the properties of LLPS condensates.
PI: Richard Bennett, Professor of Biology
Co-PI: Nicolas Fawzi, Associate Professor of Molecular Pharmacology, Physiology and Biotechnology

Engineering Genetic Models for Translational Research in Autism and Schizophrenia
Schizophrenia is among the most devastating and enigmatic conditions affecting the human brain. It has a strong genetic component, and it shares neurodevelopmental components with other neuropsychiatric illnesses, such as autism. The project proposed here relates to study of 17q12 deletion syndrome, a highly-penetrant genetic mutation that confers susceptibility to both autism and schizophrenia. Using CRISPR/Cas9 genome editing and human stem cell methods, we will establish experimental models (mice and patient-derived stem cells) for 17q12 deletion syndrome. In validating our mouse model, we have identified a prominent and high-impact phenotype involving perturbation of forebrain development. Here, we will define the molecular mechanisms underlying these abnormalities in forebrain development. We will also establish a human iPSC resource with 17q12 deletion mutations. These 17q12 deletion studies will put us in a unique position to capitalize on human genetics and discover pathways critical to human forebrain development and neuropsychiatric disorders. The impact of this work will be to define new pathophysiologic mechanisms in schizophrenia (and other neuropsychiatric disorders), stemming from genetically-inspired, neurodevelopmental studies in patients and animal models. The research group involves a multi-disciplinary team that spans psychiatry, computational biology and molecular and cellular biology, and clinical and basic research, and includes two junior faculty (Moreno De Luca and Uzun) and a senior faculty (Morrow). Together, our efforts will provide important insights into the genetic underpinnings and the underlying mechanisms of 17q12 deletion syndrome as well as related developmental neuropsychiatric illness more broadly.
PI: Eric Morrow, Mencoff Family Associate Professor of Biology, Associate Professor of Neuroscience, Associate Professor of Psychiatry and Human Behavior
Co-PIs: Daniel Moreno De Luca, Assistant Professor of Psychiatry and Human Behavior; Ece Uzun, Assistant Professor of Pathology and Laboratory Medicine

Pulmonary Artery Endothelial Cell Phenotypes During Pulmonary Hypertension
Pulmonary hypertension (PH) is a devastating disease marked by endothelial cell (EC) dysfunction and vascular stiffness. While EC dysfunction is at the core of PH pathobiology, the PH EC phenotype is incompletely characterized and remains controversial. Current methods to study this gap source cells from end-stage patients, non-diseased cell lines, or outside of the pulmonary vasculature. Right heart catheterization is the fundamental diagnostic procedure in PH and is repeated throughout the disease course. We have shown that ECs from the balloons of pulmonary artery catheters can be harvested, propagated ex vivo and characterized and that the behavior and function of these cells is influenced by clinical traits and PH severity. We contend that ECs in severe PH display abnormal programmed cell death triggered by cell detachment, known as anoikis resistance. We will leverage this source of pulmonary artery ECs from living patients to define patient-, time- and substrate-based factors that influence EC phenotype. We will characterize the behavior and function of cultured ECs over the course of disease with established assays. We will measure and compare the response of these ECs on a biomimetic synthetic pulmonary vessel platform with variable stiffness and topography. We will identify the gene expression signature of cultured ECs and compare across samples and against that from primary cells. Our experiments will include ECs from patients with different forms of PH, diseased controls, and biological replicates from the same patients over time. Data derived will be used to further develop the project for a Multi-PI grant.
PI: Elizabeth Harrington, Professor of Medicine
Co-PIs: Corey Ventetuolo, Associate Professor of Medicine, Associate Professor of Health Services, Policy and Practice; Diane Hoffman-Kim, Associate Professor of Medical Science, Associate Professor of Engineering

Role of Senescence Associated Extracellular Vesicles in Radiation-Induced Pulmonary Fibrosis
Pulmonary fibrosis is a common side effect of thoracic radiotherapy; it limits treatment options for cancer patients and increases the risk for cancer metastasis to the lungs. This treatment modality is highly effective in killing mitotic cancer cells by damaging their DNA and inducing apoptosis. However, even low dose radiotherapy is capable of inducing cellular senescence in normal cells, and the accumulation of these senescent cells and their secretory phenotype described as key mediators of pulmonary fibrosis. Ionizing radiation also results in rapid activation and persistent expression of transforming growth factor-b (TGFb), a pleiotropic cytokine involved in extracellular matrix (ECM) remodeling. Yet, there remains a gap in our understanding of how radiation-induced senescence drives pulmonary fibrosis through TGFb-mediated ECM remodeling. Our recent study demonstrated that senescent cells deposit and crosslink ECM proteins altering the architecture and mechanics of the surrounding collagen-rich environment. Although senescent cells are relatively scarce in vivo, it is possible that their ECM modifications are transferred throughout the lung via senescence-associated exosomes (SA-EVs). Previous studies have shown SA-EVs can activate nearby fibroblasts promoting collagen matrix remodeling through TGFb. The proposed studies will investigate the role of SA-EVs in transferring TGFb-mediated ECM remodeling in the lung to promote radiation-induced fibrosis and malignancy.
PI: Michelle Dawson, Assistant Professor of Molecular Pharmacology, Physiology and Biotechnology

Life, Medical and Physical Sciences 

Immunomodulatory Biomaterials for Treating Ischemia in Diabetic Models
Ischemic wounds occur when blood flow is reduced in a specific body area, leading to cell death and tissue damage. In diabetes, microvascular complications and unbalanced activation of the immune cells markedly compromise the repair from ischemic wounds, causing slower healing, development of chronic wounds and increased risk for infections.The overall objective of this proposal is to explore the mechanisms of wound healing in diabetes, by signaling of anti-inflammatory cytokines (CSF-1, IL4 and IL-13) via the JAK-STAT pathway, and to develop a novel treatment using preclinical models of non-healing diabetic ulcers. My preliminary data show that CSF-1, IL-4, and IL-13 regulate immune cells polarization and ischemic wound healing in monocyte cultures and non-diabetic animal models. With this proposal, we will elucidate the cytokines-driven regulation of the JAK-STAT signaling cascade in diabetes (Aim 1), we will deliver CSF-1, IL-4 and IL-13 from biomaterials to modulate the plasticity of monocytes isolated from the blood of diabetic rats and humans (Aim 2), and we will examine the healing of ischemic wounds in diabetic rats (Aim 3). This work will advance Brown’s position in the fields of immune engineering and wound healing therapy, will allow the PI to lay a solid foundation for expanding her research program in diabetes, and will be instrumental for attracting external funds. If successful, this project will identify suitable therapeutic targets for treating chronic wounds in diabetic patients, and will accelerate the translation to the clinic of novel immunomodulatory treatments for a patient population in great need.
PI: Fabiola Munarin, Assistant Professor of Engineering (Research)

Deep Learning Based on CT Angiography in Patient Selection for Endovascular Treatment of Large Vessel Ischemic Stroke
Stroke is a leading cause of long-term disability, and outcome in regaining functionality in areas supplied by anterior circulation large vessel is directly related to timely endovascular therapy (EVT). However, not all patients benefit from rapid intervention. CT perfusion is widely recognized as the selection tool to identify patients who will most likely benefit from reperfusion based on stroke core and penumbra size estimation as well as mismatch quantification. However, it is not routinely performed at many institutions in the United States and around the world. In this proposal, we propose to develop a fully automated artificial intelligence (AI) pipeline that identifies the images/series of interest, detect emergent large vessel occlusion and predicts immediate (e.g. the Thrombolysis in Cerebral Infarction [TICI[ score) and functional (e.g., modified Rankin score [mRS[) outcomes from EVT based on pre-procedure CT angiography. We will establish an end-to-end AI platform that interfaces with the Rhode Island Hospital (RIH) Picture Archiving and Communications Systems for real-time clinical use. The ability to predict immediate outcomes of EVT will affect management because proceduralists will be able to anticipate different reperfusion based on these predictions and adjust their treatment approach accordingly, while prediction of functional outcome assists in patient selection, resulting in improved outcome. We anticipate that the proposed project will further collaboration between the Department of Computer Science and the Department of Diagnostic Imaging, which is crucial in advancing Brown University's position in research on AI, machine learning and computer vision applied to the healthcare system and medical imaging.
PI: Ugur Cetintemel, Professor of Computer Science
Co-PIs: Harrison Bai, Assistant Professor of Diagnostic Imaging; Arko Barman, Assistant Teaching Professor, Rice University


Public Health

Using ENDS to Reduce Harm for Low SES Cigarette Smokers
Smoking is the leading cause of preventable morbidity and mortality in the US, contributing to 480,000 deaths this year. Despite increasingly strong tobacco control, annual deaths are no different than 30 years ago and tobacco-related diseases continue to disproportionately burden individuals from lower socioeconomic populations. Prevention of use and cessation remain the primary goals. However, for those unwilling or unable to quit, substituting combustible tobacco smoking with electronic nicotine delivery systems (ENDS) can significantly reduce tobacco-related harms. We propose to randomize 50 socioeconomically disadvantaged smokers who are not planning to quit to three conditions: one of two ENDS conditions (4th generation nicotine salt pod e-cigarette [EC] or heat-not-burn tobacco [HNB]) or assessment only control. We will provide participants in the ENDS conditions with devices and 8 weeks of complimentary nicotine supplies and investigate the impact on cigarette use, dependence, full substitution (quitting cigarettes), and biomarkers of exposure, toxicity, disease, and inflammation. The results of this pilot project will elucidate the magnitude and clinical meaningfulness of these effects and inform the design of a fully-powered NIH R01 application comparing ENDS to gold-standard treatments. The multidisciplinary research team established by this Category 2 OVPR Research Seed Fund proposal spans the areas of clinical psychology, medicine, public health, and social epidemiology. This project will be one of the first to compare HNB to EC and investigate their harm reduction potential. Further, the study will fill a critical gap in the literature on the feasibility and acceptability of these procedures in socioeconomically disadvantaged populations.
PI: Alexander W. Sokolovsky, Assistant Professor of Behavioral and Social Sciences
Co-PI: Jasjit S. Ahluwalia, Professor of Behavioral and Social Sciences, Professor of Medicine, and Director, Population Sciences for the Brown Cancer Center

Humanities and Social Sciences

Informal Transit Networks in Emerging Cities
African cities will double in population by 2050, and will require thoughtful solutions to get around. In many emerging cities, transit is private: operated by many small bus companies, some so small they only own a single bus. This system is flexible, but can be disorganized and dangerous. In recent years, many cities have invested in formal public transit to replace private transit. But mass rapid transit is costly. And it may not be necessary: new technologies like dynamic routing may make it possible to increase the efficiency of decentralized transit, without the need for costly investment. This project will develop a new data partnership to study transport in Africa’s largest city. It will use that partnership to study how informal transit systems respond when the city of Lagos, Nigeria, introduces 820 new formal, government-owned and regulated buses across 50 routes. The study will assess how the introduction of this new travel option affects riders and operators, in collaboration with the Lagos Metropolitan Area Transport Authority (LAMATA).
PI: Daniel Bjorkegren, Assistant Professor of Economics

Unmasking COVID-19: Pacific Islanders, Health Equity, and Survival in New Zealand and the United States
“Unmasking COVID-19” examines the disproportionate effects of the coronavirus pandemic on Pacific Islander communities in New Zealand and the United States. While both countries have adopted different approaches to managing the pandemic at a national level, Pacific Islanders in both nations have been diagnosed with and suffered the impact of COVID-19 in numbers disproportionate to their representation within the overall population. Thus, a closer investigation of the historical and structural factors shaping Pacific Islanders' health outcomes, the pandemic’s role in exacerbating those factors, and local level organizations’ role in mitigating the impact of these circumstances is needed. Our team will conduct interviews with leaders and members of Pacific Islander serving organizations in New Zealand and the United States that have actively sought to provide much-needed community assistance during the pandemic. These interviews will then be supplemented by interviews with physicians and local government officials. Drawing on this data we will: (1) co-author and publish a series of Op-Ed pieces in New Zealand and U.S. news outlets on COVID-19’s disproportionate impact on Pacific Islander communities; (2) develop and publish a co-authored research paper on the importance of reconciling national and community-based narratives during the coronavirus pandemic; (3) build a website using the StoryMaps platform to showcase the virus’s impact on individuals’ everyday lives and highlighting the diverse array of community-based responses to managing the pandemic’s effects; and (4) apply for external grant funding to include additional nations/overseas territories across the Pacific region.
PI: Kevin Escudero, Assistant Professor of American Studies
Co-PIs: Keith Camacho, Associate Professor of Asian American Studies, University of California, Los Angeles; Maryann Nanette Anesi Heather, Senior Lecturer, School of Population Health, Faculty of Health and Medical Sciences, University of Auckland and General Practitioner, South Seas Healthcare

Disrupted Dreams: Understanding the Impact of Covid-19 on the Life Projects of First-Generation College Students and their Parents
This project makes use of the Pandemic Journaling Project (PJP) – an online journaling platform that Mason and Willen created and launched in May 2020 to chronicle and preserve first-hand experiences of the pandemic. We will examine the impact of the Covid-19 pandemic on the entwined life projects of first-generation college students and their parents. We ask: Has the Covid-19 pandemic impacted the content or trajectory of the life projects of first-generation college students and their parents, and if so, how? We will use a mixture of online journaling, semi-structured interviews, focus groups and the curation of an online photo exhibition to answer this question. Seed funds from Brown would allow Mason, Willen, Flores and Baines to build a long and lasting collaboration, would ensure the viability of the PJP platform through 2021, and would position our group well to procure extramural funds for this project. PJP currently has about 750 users and more than 6700 journal entries have already been submitted. By assisting our group in demonstrating that this platform can successfully be utilized to conduct virtual ethnographic research on a timely topic of importance during the pandemic, Brown can establish itself as a leader in virtual research methods in anthropology and education.
PI: Katherine Mason, Vartan Gregorian Assistant Professor of Anthropology
Co-PIs: Andrea Flores, Assistant Professor of Education; Sarah Willen, Associate Professor of Anthropology, University of Connecticut

Re-constructing Reza Abdoh's Father Was a Peculiar Man
Queer Iranian American director Reza Abdoh’s Father was a Peculiar Man is an important work of US avant garde theatre history. Based on Fyodor Dostoyevsky’s Brothers Karamazov, the play, combined aspects of the novel with other texts that explored the relationship between patriarchy, violence and the AIDS crisis. Father was staged in New York City’s meatpacking district—near sites of queer sex commerce and celebration in 1990. Unlike Abdoh’s other works, Father was never edited into a production video because it was a highly moveable site-specific performance which was nearly impossible to “capture” in a linear format. This project attempts to creatively reconstruct this performance through a multimodal digital archive of the performance including video footage, artist testimony, an annotated production “script,” critical essays and an urban spatial representation of the play. This project has two major contributions: 1) Providing scholars with access to a performance that radically shaped this history of avant-garde performance, and queer performance 2) modeling a new way of recreating performance works that are left out of traditional archives. A seed grant will fund the work of a research assistant (who has begun work as an UTRA recipient) and team of artists involved in the production to curate and organize the content to be made into the annotated reconstruction of the performance and to provide basic technical support for this project. This award will advance Brown's reputation for innovative arts scholarship in the digital humanities.
PI: Patricia Ybarra, Professor of Theatre Arts and Performance Studies