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Lorena Martin

  • Assistant Professor of Clinical Data Sciences and Operations

PhD, BS, University of Miami; MS, Nova Southeastern University; Postdoctoral Fellowships, UC San Diego

As an Assistant Professor of Clinical Data Sciences and Operations at the University of Southern California, Lorena Martin stands out for her insightful approach to research, often illustrated through her focus on "both sides of the bell curve." This phrase encapsulates her dual research interests: on one side, she is dedicated to reducing health disparities in underprivileged populations, particularly within the Hispanic/Latino community, by examining physical activity levels and promoting healthy lifestyle behaviors. On the other side, her work extends into the realm of sports science, where she concentrates on enhancing sports performance and injury prevention for professional athletes.

Martin's unique perspective is deeply influenced by her background as a former elite tennis player. Her transition from athlete to academic has been marked by significant roles in the professional sports industry, including serving as the Director of High Performance for a Major League Baseball team and as the Director of Sports Performance Analytics for the Los Angeles Lakers. These experiences have provided her with invaluable insights into the practical applications of her research.

In addition to her professional roles, Martin is an accomplished author, contributing to renowned books like "Sports Injury Prevention and Rehabilitation, 2nd edition" and "Improving Exercise Adherence." She is also the sole author of "Sports Performance Measurement and Analytics," a testament to her expertise in the field. Her academic credentials are equally impressive: she earned her bachelor’s degree in Psychology and her master's degree in Mental Health Counseling from Nova Southeastern University, then she returned to the University of Miami where she obtained her doctorate in Exercise Physiology. She also completed a three-year postdoctoral fellowship in analytics, GIS spatial analysis, biostatistics, and epidemiology at the University of California, San Diego.

Lorena Martin's career, characterized by her passion for research and data science and her unique application of the bell curve concept, positions her as a leader in leveraging data science for reducing health disparities and improving sports performance.

Lorena Martin
Press Inquiries: COMMUNICATIONS@MARSHALL.USC.EDU

Areas of Expertise

Analytics
Business of Sports
Sports Performance

Departments

Data Sciences + Operations

INSIGHT + ANALYSIS

The latest interviews, quotes, citations, and research in the media.

NEWS + EVENTS

COURSES

Spring 2025
  • BUAD-425
    Introduction to Business Analytics
    Leveraging large corporate datasets; slice and dice data; dash boards; data mining and statistical tools; neural network; multiple and logistic regression; decision tree; gain inference and decision making; clustering.
  • DSO-499
    Sports Data Science and Management
    Sports Data Science principles, wearable technology, statistical analysis, machine learning, AI, data interpretation, leadership, and management within the sports industry.
  • DSO-445
    Statistical Computing and Data Viz: R, Python, Tableau
    Develop skills in statistical computing, data visualization and programming using R, Python and Tableau. Hands-on projects, coding exercises and collaborative teamwork for business insights.
  • DSO-578
    Fundamentals of Sports Performance Analytics
    Statistical models for pro sports industry business application. Effectively communicate findings for practical actionable results. Sports science data protocol.
  • DSO-579
    Advanced Sports Performance Analytics
    Implement supervised and unsupervised machine learning models to a specific sports performance analytics scenario. Help assess and predict performance.
Fall 2024
  • BUAD-425
    Introduction to Business Analytics
    Leveraging large corporate datasets; slice and dice data; dash boards; data mining and statistical tools; neural network; multiple and logistic regression; decision tree; gain inference and decision making; clustering.
  • DSO-424
    Business Forecasting
    A variety of forecasting techniques used by a variety of businesses. Emphasis on learning to apply these techniques to real data.
  • DSO-578
    Fundamentals of Sports Performance Analytics
    Statistical models for pro sports industry business application. Effectively communicate findings for practical actionable results. Sports science data protocol.
  • DSO-579
    Advanced Sports Performance Analytics
    Implement supervised and unsupervised machine learning models to a specific sports performance analytics scenario. Help assess and predict performance.
Spring 2024
  • DSO-499
    Special Topics
    Selected topics reflecting current trends and recent developments in data sciences, information systems, operations management, and statistics. May be repeated only if topic is different.
  • DSO-560
    Text Analytics and Natural Language Processing
    Acquire, analyze, visualize and perform natural language processing (NLP) on text data. Apply Python, machine learning packages, statistical methodology and computer code to business decision-making.
  • DSO-579
    Advanced Sports Performance Analytics
    Implement supervised and unsupervised machine learning models to a specific sports performance analytics scenario. Help assess and predict performance.
Fall 2023
  • DSO-545
    Statistical Computing and Data Visualization
    Data cleaning and reshaping; good vs. bad graphics; univariate, bivariate, trivariate, hypervariate and time series graphics; interactive graphics; web-related computing.
  • DSO-560
    Text Analytics and Natural Language Processing
    Acquire, analyze, visualize and perform natural language processing (NLP) on text data. Apply Python, machine learning packages, statistical methodology and computer code to business decision-making.
  • DSO-578
    Fundamentals of Sports Performance Analytics
    Statistical models for pro sports industry business application. Effectively communicate findings for practical actionable results. Sports science data protocol.