Class of 2025

- Created SQL-based pricing models to identify systematic payment discrepancies in the hospital revenue cycle by manipulating large sets of financial data using SQL Server Management Studio- Conducting detailed financial audits of hospital clients’ patient account records on a mass scale to identify major trends within revenue cycle processes- Negotiating payments with health insurance representatives over contract language interpretation for underpaid provider claims

-Conducted a research investigation into the effect of coping strategies on different experiences of depression, stress, and anxiety within premedical students

-Investigating the mechanisms by which c-myc is a regulator in Pol I transcription-Determining therapeutic strategies to combat cancers with myc related pathways

-Designed interface and hardware to monitor brainwave activity in real time to help detect learning disabilities like ADHD-Engaged physicians, psychiatrists, and industry leaders to improve and market the platform and device

Shadowed in the Cardiothoracic and Vascular Surgery Departments at Methodist Hospital, observed numerous surgeries including Coronary Artery Bypass Grafts and transplants, gained a better understanding of a physician's lifestyle.

-Investigated the role of Cdk7 in the smooth muscle response in the cardiovascular system-Analyzed epigenetic regulators and chromatin-associated proteins to evaluate potential as novel therapeutic targets

-Conducted an in-depth research assessment on big data technologies in the healthcare realm to better determine how Cisco can obtain a competitive advantage and direct innovative efforts in the future-Presented findings at the IEEE International Conference on Medical Computing (COMPSAC2017) in Turin, Italy

-Analyzed the molecular basis of Entamoeba Histolytica to help devise a solution to amoebiasis-Researched the expression and purification of the GST-fusion protein

-Focused on increasing the efficiency of transactions between healthcare providers and consumers-Developed taxonomy system for patient appointment classification