Role: Healthcare Data Analyst, Department of Medicine
Tenure: October, 2024 - Present

Responsibilities:

• Lead and manage multi-domain research initiatives, including critical care, pulmonary, and sleep medicine, integrating clinical expertise with advanced data analytics using Python, R, SQL, EPIC, and REDCap.

• Design and implement predictive and geospatial models for CDC and NIH funded projects, including machine learning frameworks to assess vaccine uptake and rural health disparities.

• Conduct comprehensive EHR-based analyses to uncover key clinical patterns, disease predictors, and outcome disparities, supporting peer-reviewed abstracts, posters, and national conference presentations.

• Collaborate across disciplines with clinicians, data scientists, and IT specialists to optimize clinical workflows, quality improvement (QI) initiatives, and research study protocols.

• Mentor fellows, residents, and research staff in data analytics, study design, and reproducible workflows, fostering a collaborative, data-driven research environment.

Current Projects:

• Title: Machine Learning Decision Support Tool for Differentiating Malignant vs. Benign Soft Tissue Masses on MRI

Department of Radiology, WVU Medicine; Collaboration with MD Anderson Cancer Center 

Duration: Feb 2026 - Present

• Built a decision tree classifier (scikit-learn) on 295 retrospectively reviewed musculoskeletal MRI cases to help non-expert clinicians distinguish malignant from benign soft tissue masses, achieving 86% accuracy and an AUC of 0.84.

• Identified lesion size (> 4.2 cm), T1 heterogeneity, and perilesional edema as the strongest predictors of malignancy, with odds ratios up to 46.6x for perilesional edema (95% CI: 21.6–100.3, p < 0.001).

• Title: Comparative Outcomes of Mechanical Thrombectomy and Anticoagulation Therapy in Pulmonary Embolism Patients 

Duration: Sep 2025 - Present

• Conducted a retrospective data analysis of 191 patients diagnosed with acute Pulmonary Embolism (PE), comparing outcomes between mechanical thrombectomy (MT) and anticoagulation (AC) treatment groups.

• Performed statistical tests on clinical, demographic, and biomarker data (e.g., Troponin, B-type natriuretic peptide, Charlson Comorbidity Index), identifying a significant difference in Troponin levels (p = 0.0003) between groups.

• Title: Geospatial and Temporal Analysis of Pediatric Physical Abuse Encounters in Rural Appalachia

Division of Pediatrics, WVU Medicine Golisano Children's Hospital 

Duration: Jan 2026 - Present

• Analyzed 14 years of EHR data (2010–2024) covering around 509 pediatric physical abuse encounters, identifying a greater than 7-fold increase in monthly cases from pre- to post-COVID-19 periods (1.18 to 8.77/month, p<0.0001).

• Conducted geospatial analysis (Python, GeoPandas, Matplotlib) integrating Census TIGER/Line shapefiles with the Distressed Communities Index, revealing a highly significant association between community economic distress and abuse prevalence.

• Applied chi-square, ANOVA, and Kruskal-Wallis testing to detect significant shifts in patient age and insurance status across the pandemic timeline, supporting targeted public health intervention design.

• Title: Group-Based Trajectory Modeling of Longitudinal Inflammatory Biomarker Patterns   

Duration: July 2026 - Present

• Applied Group-Based Trajectory Modeling (R, package: lcmm) to identify distinct longitudinal patterns in a clinical inflammatory biomarker, testing 2- through 5-class solutions using quadratic mixed-effects modeling.

• Selected the optimal 3-class trajectory solution by balancing BIC improvement, posterior classification probability (> 80% average across classes), and clinical interpretability, identifying increasing, decreasing, and stable trajectory subgroups.

• Produced a structured model comparison report (BIC trends, posterior probability diagnostics, trajectory visualizations) to support a data-driven model selection decision.

• Title: Impact of Comprehensive Geriatric Assessment on Polypharmacy, Delirium, and Outcomes in Older Trauma Patients

Section of Geriatric & Palliative Medicine, WVU Medicine

Duration: May 2026 - Present

• Conducted a retrospective case-control analysis of 250 trauma patients (≥ 65 years) to evaluate the effect of inpatient Comprehensive Geriatric Assessment (CGA) on polypharmacy, delirium, readmissions, and mortality.

• Identified that CGA consultation was associated with a meaningful reduction in in-hospital delirium (11.7% vs. 20.5%) and lower 1-year mortality (13% vs. 21%), despite no significant difference in readmission rates.

• Analyzed medication burden trends using REDCap-extracted data, revealing severe polypharmacy rose from 47.9% at admission to 70% at discharge, surfacing a critical, modifiable target for future intervention design.

• Title: Machine Learning–Driven Predictive Modeling for Vaccine Receptivity: Optimizing Resource Allocation in Rural Appalachia (CDC Project) 

Duration: Oct 2024 - Present

• Developed and implemented advanced machine learning and deep learning models using Python, TensorFlow, and Scikit-learn to predict vaccine uptake across rural Appalachian populations, leveraging demographic, socioeconomic, and health behavior data.

• Collaborated with CDC and WVU Medicine researchers to analyze vaccine receptivity trends, identify high-risk geographic clusters, and support data-driven resource allocation and public health outreach strategies.

• Enhanced model performance through iterative validation, achieving over 89% prediction accuracy, and provided actionable insights to inform policy-level vaccination strategies and community health interventions.

• Title: Longitudinal ICU Biomarker Data: Neutrophil to Lymphocyte Ratio (NLR) Analysis   

Duration: April 2026 - Present

• Built an end-to-end Python data pipeline to clean, validate, and derive a longitudinal clinical biomarker (neutrophil to lymphocyte ratio) from raw laboratory records, including deduplication and multi-step data validation logic.

• Conducted exploratory data analysis and visualization (distribution analysis, missingness assessment, longitudinal trajectory plots) to support downstream statistical modeling of clinical biomarker patterns.

• Title: Right Heart Catheterization Data Analysis in Group 1 Pulmonary Hypertension Patients 

Duration: Oct 2025 - Present

• Conducted a comprehensive analysis of Right Heart Catheterization (RHC) data from 61 Group 1 Pulmonary Hypertension patients, evaluating demographic, comorbidity, and hemodynamic parameters.

• Performed Kaplan-Meier survival analysis and Cox proportional hazards model based on functional class (I–IV), identifying a statistically significant association with patient survival (p = 0.0016).

• Title: Patient Predictive Modeling of PAP Therapy Adherence Using Patient Perception Survey Data    

Duration: June 2026 - Present

• Analyzed survey and clinical data from 209 hospitalized OSA patients using multivariable logistic regression to determine whether PAP therapy perception predicted post-discharge diagnostic follow-through.

• Found that patients with a good perception of PAP therapy were significantly more likely to complete post-discharge testing and receive home CPAP prescription (adjusted OR=2.75, 95% CI: 1.34–5.61, p=0.006), even after adjusting for age, BMI, CHF, and COPD/Asthma.

• Title: Randomized Controlled Trial for Early Detection of Sleep Apnea in Acute Stroke Patients

Duration: Oct 2024 - Present

• Designed a randomized controlled trial comparing an intervention group (in-hospital sleep consultation and structured follow-up) versus standard care to improve timely completion of sleep studies post-stroke.

• Aimed to set a new standard in stroke care by enabling early diagnosis and treatment of obstructive sleep apnea, thereby enhancing recovery and reducing long-term health impacts.

Completed Projects:

• Title: SAHARA Study: Five-Year Analysis of Sleep Apnea in Rural Hospitalized Patients  (NIH Project)

 Duration: Oct 2024 - May 2025

• Retrospectively analyzed a REDCap database of 2,728 patients using level III unattended polysomnography, identifying that 40% of screened patients had moderate to severe sleep apnea.

• Analyzed associations between sleep apnea severity and key comorbidities such as hypertension, COPD, diabetes, and congestive heart failure to uncover population-level health disparities.

• Findings contributed to a published abstract at the SLEEP 2024 Conference, supporting data-driven initiatives to enhance inpatient sleep medicine programs in rural hospitals.

• Title: OSA & Pulmonary Hypertension in Appalachia: Prognostic Impacts on Re-admission and Survival (NIH Project)

Duration:  Oct 2024 - Nov 2025 

• Conducted a retrospective cohort study of 573 (rural Appalachian population) patients using Kaplan–Meier curves and Cox regression, to evaluate long-term survival and hospital readmission outcomes, adjusting for age, gender, BMI, and comorbidities.

• Identified a “survival paradox”: patients with both OSA and PH demonstrated better long-term survival compared to those with PH alone (HR=1.3, p=0.002).

• Discovered that BMI was inversely associated with hospital readmission rates, suggesting an “obesity paradox” protective effect.

• Supported development of hospital-level sleep medicine quality improvement initiatives and contributed to a peer-reviewed abstract publication and national poster presentation (APSS).

• Title: Pulmonary Embolism (PE) Outcomes and Geospatial Analysis

Duration:  Jan 2025 - June 2026

• Conducted comprehensive statistical and geospatial analyses of pulmonary embolism patients to assess mortality, readmission, and demographic disparities using Python (Pandas, Seaborn, GeoPandas, Matplotlib, Contextily).

• Integrated geospatial mapping to visualize regional healthcare patterns and rural–urban disparities, highlighting variations in ICU mortality and readmission rates across West Virginia.

• Designed reproducible analysis workflows and advanced visualizations to communicate findings effectively to clinical teams and support evidence-based decision-making.

• Merged electronic health record (EHR) data with geographical indicators (RUCA codes) to identify underserved areas and inform public health resource allocation.

• Title: Geographic and Clinical Determinants of Interstitial Lung Disease Severity and Referral Patterns in Rural Appalachia

Duration:  Dec 2024 - April 2026

• Analyzed 312 ILD clinic patients (2021–2024) to evaluate referral patterns, geographic access, and pulmonary function outcomes in rural Appalachia.

• Found that greater travel distance (>60 miles) correlated with worse lung function (FEV1, TLC, DLCO) and longer delays from symptom onset to specialty care.

• Conducted geospatial and statistical analysis using Python and Excel, identifying key access barriers and trends in disease severity and referral behavior.

• Title: Implementation Science–Driven Quality Improvement to Increase Vaccine Uptake in Pulmonary Medicine Clinics

Duration:  Dec 2024 - Aug 2025

• Participated in a multi-institutional American Thoracic Society (ATS) Vaccine Initiative aimed at improving adult vaccination rates (COVID-19, influenza, pneumococcal) in subspecialty pulmonary medicine settings.

• Applied implementation science frameworks - including the Consolidated Framework for Implementation Research (CFIR) and Expert Recommendations for Implementing Change (ERIC) - to identify barriers, facilitators, and context-specific strategies for program deployment.

• Conducted a clinic process workflow analysis using stakeholder focus groups and LucidChart-based mapping to identify intervention touchpoints across patient and provider engagement steps.

• Collaborated with a multidisciplinary team (physicians, IT developers, administrators, public health researchers) to align QI design with implementation science methods for long-term sustainability.

• Title: INSPIRE Study: Data Analysis of Upper Airway Stimulation Therapy Outcomes in Obstructive Sleep Apnea 

Duration: Aug 2025 - Present

• Performed statistical analysis of pre and post-operative sleep study data from the INSPIRE Upper Airway Stimulation project to evaluate treatment outcomes for Obstructive Sleep Apnea (OSA) patients.

• Identified correlations between facial structure and body position and how these influence therapeutic response, contributing to improved patient selection criteria and postoperative evaluation strategies.

Role: Senior Supply Chain Analyst
Tenure: April, 2018 - November, 2021

Responsibilities:

• Achieved a 10% reduction in supply chain costs by implementing data-driven solutions for inventory management, resulting in the optimization of stock levels and a decrease in both stockouts and overstock situations.

• Improved supply chain efficiency by 15% through regression analysis, ANOVA, multilevel models, and root cause analysis. This involved streamlining processes and reducing lead times to address supply chain inefficiencies.

• Led cross-functional collaboration with production teams to gather and structure extensive manufacturing data. Proficiently utilized tools like R, SAS, SQL, Python, MS Excel, Tableau, and Power BI to create comprehensive reports and visually compelling presentations, showcasing advanced data management, organization, and visualization skills.