Xiaohui Chen

Conducted advanced research in the robustness and explainability of medical artificial intelligence. Developed a lightweight and explainable AI framework to analyze adversarial attacks in medical imaging by quantifying spatial shifts in critical feature regions with interpretable metrics.

Performed Assisted Daily Livings for nursing home residents including daily dress change, output measurement, vital sign measurement, mechanical lift, sit-to-stand lift, wheel-bed transfer, personal/oral/toilet hygiene, feeding and documentation. Floated across different floor/units as requested.

Conducted advanced research in the robustness of medical artificial intelligence, with a focus on developing adversarial defense strategies for medical imaging applications. Investigated domain discrepancies between natural and medical images to optimize transfer learning in medical diagnostics.

Instructor for COMP SCI 1500: Computational Problem Solving, responsible for lectures and lab sessions for a class of 60 undergraduate students. Taught foundational Python programming concepts, including variables and expressions, data types, control flow, functions, object-oriented programming, and modular development.

Conducted in-depth analysis of SHA and IQVIA claims data to generate strategic business insights into product market trends, healthcare provider targeting, and dialysis center mapping. Led end-to-end claims data pipeline operations, including weekly data ingestion and delivery workflows using Snowflake and Amazon S3.

Served as a key contributor on a client-focused team developing a Proof-of-Concept for the Claim Edits project. Designed and delivered interactive Power BI dashboards with dynamic filtering capabilities, enabling comparative analysis across multiple key performance indicators to support data-driven decision-making.

Shadowed under an orthopedic surgeon to observe both surgical and clinical sessions. Wrote reports on observations, findings and personal research of each session.

Activities and societies: Graduate Research Assistant, conducting advanced research in the robustness and explainability of medical artificial intelligence. Developed a lightweight and explainable AI framework to analyze adversarial attacks in medical imaging and a novel adversarial defense framework scalable for real-world deployment.

Currently pursuing a Ph.D. in Computer Science, focusing on advanced research in the robustness and explainability of medical artificial intelligence. Developing a lightweight and explainable AI framework to analyze adversarial attacks in medical imaging.

Activities and societies: Graduate Research Assistant, conducting advanced research in the robustness of medical artificial intelligence. Graduate Teaching Assistant for COMP SCI 1500: Computational Problem Solving, responsible for lectures and lab sessions.

Pursued a Ph.D. in Computer Science, with a focus on developing adversarial defense strategies for medical imaging applications. Investigated domain discrepancies between natural and medical images to optimize transfer learning in medical diagnostics.

Activities and societies: Designer and Developer for '3D Imaging for Tumor Resection' project, evaluating unmet clinical requirements and reconstructing medical imaging datasets into 3D test models. Programmer for 'Automatic Segmentation of Blood Pool in Cardiac MRI'.

Completed a Master of Engineering in Biomedical Engineering. Involved in a cross-functional industrial project team for 3D Imaging for Tumor Resection.

Obtained a Master of Science in Computer Science. This program enhanced skills in various programming languages and software.

Activities and societies: Selected student on the Dean’s List in Spring 2014, Fall 2014, and Fall 2015.

Earned a Bachelor of Science in Computer Science. Recognized on the Dean's List multiple times during the program.