Books for Baghdad is a nonprofit organization dedicated to enhancing educational opportunities for students in Baghdad by providing them with essential books and school supplies. Our mission is to empower young minds through access to quality educational resources, fostering a love for learning and contributing to the development of a prosperous community.

I play a crucial role in delivering high-quality care to patients with cardiovascular conditions. My responsibilities include monitoring vital signs, assisting with daily activities, performing routine tests, and supporting the nursing staff in various procedures. I work closely with patients to provide comfort, gather medical histories, and ensure that their needs are met promptly and compassionately. My role helps maintain the smooth operation of the cardiovascular unit and contributes to positive patient outcomes and experiences.

I delve into the intricate biology of TDP-43 and m6A RNA modifications, with the goal of developing therapies for frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS). My work involves a variety of advanced techniques: I culture neurons and other cell lines to explore the effects of TDP-43 mutations and mislocalization, employing immunofluorescence and immunohistochemistry to visualize TDP-43 protein localization and aggregation. Western blotting and mass spectrometry are used to analyze protein expression levels and post-translational modifications. For studying m6A RNA modifications, I extract and quantify RNA, utilizing MeRIP-Seq to profile m6A-modified RNA and RT-qPCR to validate these findings. I also engage in pathological analysis through electron microscopy to examine TDP-43 inclusions in neural tissue and work with animal models to understand disease progression and test potential therapies. Additionally, I screen and test drugs, including small molecules and RNA-based therapies, to modulate TDP-43 and m6A pathways, using bioinformatics to integrate data from RNA-seq and other technologies with clinical and pathological insights. The ultimate aim of my research is to translate these molecular discoveries into effective clinical treatments for FTD and ALS.

I work directly with the new members of the Residential College at the University of Michigan to provide academic, social, and personal support.

To determine the Relative Citation Ratio (RCR) of clinical researchers in the field of cornea and ocular surgery, measuring the significance of their research and its implications on practices in the field, data was collected and analyzed via ICite. The RCR data of every Cornea researcher from every Medical School in America was sorted by mean and median scores, as well as overall impact scores (among each researcher's general publications, as well as their scholarly research). This data was sorted into two separate categories. These findings would help to further understand the significance of RCR scores and how new research is being implemented into clinical practice.

The Medical Arabic team consists of a group of students interested in eradicating the language barrier often faced by Arab-Americans patients. Our aim is to teach medical students at the university of Michigan, Ann Arbor, Arabic phrases and basic anatomy, all of which could be applied in a clinical setting. This will ultimately better the patient-care experience and contribute to crafting the next generation of physicians.

We are examining how individuals in certain professions (typically those that increase exposure to metals) are at greater risk of ALS. In conjunction, we are studying how brain function is impeded by ALS.

Being a first-generation American means I was the first in my family to experience academic and professional opportunity without the many burdens immigrants often face. The RISE tutoring program seeks to eradicate the academic disparity between immigrant students and their peers. Offering tutoring in science, mathematics, and english - in addition to citizenship and SAT test-prep-, the RISE program is an excellent way to develop the fundamentals of common-core subjects and learning. This sets out students up for success in both their academic and personal lives.

A smaller community within the University of Michigan, focused on kinship and promoting academic excellence. In the DEI sector of the fraternity, a diverse and talented student body is fostered, providing and promoting equal opportunity for all, and ultimately developing a more inclusive and equitable community. This is done through charitable events, donations, etc.

As a volunteer in the music-therapy lounge of Michigan Mott’s Children’s Hospital, my responsibilities are extensive. From playing piano for infants and adolescents, to giving tours of the music-therapy lounge, I get the opportunity to provide these services to families in a time of great need.

To expand my understanding of what is means to be a healthcare provider, I accepted this position as a medical assistant at Xpress Urgent Care. My position consists of collecting background information on patients, checking patients into the clinic, taking vitals, photographing and recording X-rays, administering tests for COVID, STREP Throat, HIV, and STI, and giving injections.

Working alongside Oculofacial Plastic Surgeon Dr. Zhenyang Zhao, we have two main objectives for our project:i. AI Training Based on Generative Adversarial NetworkA generative adversarial network (GAN) is used to conduct an unsupervised deep learning process. In brief, two deep learning models have trained under the same “training set” images. The generator model is trained to generate new images (simulated results) based on pre-operative photos. The discriminator model is trained with post-surgical photos to tell if the simulated results are real (from the original photos) or fake (newly generated by AI). The two models are trained together in a zero-sum game, adversarial, until the discriminator model is fooled about half the time, meaning the generator model is generating plausible examples (Fig 1).An open-source “pix2pix” framework7 will serve as the base model for the DL algorithm. The training will be monitored by validation loss and terminated until no improvement is achieved for a consecutive 10 epochs or repetitions. After each repetition, the model predictions will be compared with the real post-operative images to illustrate the model’s improvement throughout the training process. Unseen images from the “test set” will be used to assess the model performance. The trained generator will be the final product used to predict postoperative images in new patients.ii. Publication of Final Product as ASOPRS Sponsored Free ServiceThe final product will be deployed as a web-based application. A REST API will be created using Flask. The model will be hosted in a cloud server. The final product will first be tested by ASOPRS members on an account access basis. The application may also provide individualized service that can generate surgeon-specific simulation if sufficient data are collected from the same surgeon. Periodic big-data reports will be generated for further research purposes.

I have acquired over 90 clinical shadowing hours in multiple departments at the Michigan medical hospital -And UofM affiliates-. This includes radiology, anesthesiology, gastroenterology, Emergency Medicine, psychiatry, geriatrics, pediatrics, plastic surgery, sports medicine, neurology, neurosurgery, and palliative care.

My responsibilities at Sam Michaels Tailor Shop included selling clothing daily, ensuring store efficiency and customer satisfaction, stocking shelves and keeping item count, and working at the register.