Zlatana Nenova

Assistant Professor

EMAIL: nenovaz@wfu.edu

PHONE: (336) 758-5462

OFFICE: Farrell 347

CV: Curriculum Vitae

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Biography

Dr. Zlatana Nenova is a researcher and professor specializing in healthcare analytics, with a particular emphasis on how machine learning, artificial intelligence, and dynamic programming models can enhance care for patients with chronic conditions. Her research focuses on refining analytical methodologies to improve disease trajectory predictions, which can then be used to optimize treatment plans. Dr. Nenova also investigates how to schedule patients optimally under uncertainty and supply constraints, as well as how to better visualize patient data to support clinicians in making informed treatment decisions.

Her work has been published in leading academic journals, including Production and Operations Management, Journal of Operations Management, and Decision Sciences, and has been presented at premier conferences in the field.

At Wake Forest University's School of Business, Dr. Nenova teaches graduate courses in data analytics and visualization. Her teaching equips students with the knowledge and critical thinking skills needed to thrive in today's data-driven landscape. She emphasizes the responsible and strategic use of data in decision-making throughout her business analytics curriculum.

Honors

2020 - Faculty Research Fund Grant , University of Denver
2019 - Research Grant, Pittsburgh Supercomputing Center
2019 - Summer Research Grant: 2019 - 2024, University of Denver
2013 - ELG Fellowship, University of Pittsburgh

Research Interests

Healthcare Analytics & Decision Making
Data Mining & Statistics
Dynamic Programming

Teaching Interests

Data Mining & Statistics
Healthcare Analytics & Decision Making
Data Visualization
Optimization

Education

Ph D, University of Pittsburgh (Business Analytics and Operations) - 2017
MA, University of Pittsburgh (Applied Statistics ) - 2013
BS, Guilford College (Mathematics & Accounting ) - 2011

Publications

Elsevier

Chronic disease progression prediction in healthcare operations

Nenova, Z. , & Foster, K. (2025)

Decision Sciences

Identifying influential individuals and predicting future demand of chronic kidney disease patients

Nenova, Z. , & Bartelt, V. L. (2024)

Springer International Publishing

Machine Learning in Healthcare: Operational and Financial Impact

Anderson, D. , Bjarnadottir, M. V. , & Nenova, Z. (2022)

Production and Operations Management

Personalized Chronic Disease Follow?Up Appointments: Risk?Stratified Care Through Big Data

Nenova, Z. , & Shang, J. (2022)

Production and Operations Management

Chronic Disease Progression Prediction: Leveraging Case?Based Reasoning and Big Data Analytics

Nenova, Z. , & Shang, J. (2022)

Palliative Medicine

Appointment utilization as a trigger for palliative care introduction: A retrospective cohort study

Nenova, Z. , & Hotchkiss, J. (2019)

Journal of Operations Management

Determining an optimal hierarchical forecasting model based on the characteristics of the data set

Nenova, Z. , & May, J. (2016)