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Andrew Redd, PhD

Languages spoken: English

Academic Information

Departments: Internal Medicine - Research Assistant Professor, Family & Preventive Medicine - Adjunct Assistant Professor, Population Health Sciences - Adjunct Assistant Professor

Divisions: Epidemiology, Public Health

Academic Office Information

Research Interests

  • Biostatistics
  • Data Interpretation, Statistical
  • Clinical Natural Language Processing
  • Big Data Analytics
  • Data Mining in Biomedical Informatics
  • Data Analysis
  • Information Extraction
  • Models, Statistical
  • Parametric and Nonparametric Inferential Statistics
  • Statistics
Andrew Redd, Ph.D., is an Assistant Professor at the Division of Epidemiology. As a Statistician, his research interests include statistical data modeling for surveillance data, disease transmission models complex data models, network models, high performance computing, statistical programming, reproducible research methods and tool, and programming and analysis standardization.

Redd’s Dissertation work was on paired functional data analysis. His current research focuses on surveillance models and the statistical issues related to inference from data originating in information extraction and natural language process. He is an active contributor to the R statistical programming software through several add-on packages.

Redd received his Ph.D. from Texas A&M University.

Education History

Doctoral Training Texas A&M University
Internship KBSI, Inc.
Internship ATK Launch Systems
Graduate Training Texas A&M University
Undergraduate Weber State University
Applied Mathematics

Selected Publications

  1. Stewart IJ, Poltavskiy E, Howard JT, Janak JC, Pettey W, Zarzabal LA, Walker LE, Beyer CA, Sim A, Suo Y, Redd A, Chung KK, Gundlapalli A (2020). The Enduring Health Consequences of Combat Trauma: a Legacy of Chronic Disease. J Gen Intern Med, 36(3), 713-721.
  2. Jones AL, Pettey WBP, Carter ME, Brignone E, Redd A, Suo Y, Divita G, Blais RK, Fargo JD, Gundlapalli AV (2020). Regional Variations in Documentation of Sexual Trauma Concepts in Electronic Medical Records in the United States Veterans Health Administration. AMIA Annu Symp Proc, 2019, 514-522.
  3. Gundlapalli AV, Redd AM, Suo Y, Pettey WBP, Brignone E, Chin DL, Walker LE, Poltavskiy EA, Janak JC, Howard JT, Sosnov JA, Stewart IJ (2020). Predicting and Planning for Musculoskeletal Service-Connected Disabilities in VA Using Disability for Active Duty OEF/OIF Military Service Members. Mil Med, 185(Suppl 1), 413-419.
  4. Redd AM, Gundlapalli AV, Suo Y, Pettey WBP, Brignone E, Chin DL, Walker LE, Poltavskiy EA, Janak JC, Howard JT, Sosnov JA, Stewart IJ (2020). Exploring Disparities in Awarding VA Service-Connected Disability for Post-Traumatic Stress Disorder for Active Duty Military Service Members from Recent Conflicts in Iraq and Afghanistan. Mil Med, 185(Suppl 1), 296-302.
  5. Beyer CA, Poltavskiy E, Walker LE, Pettey W, Suo Y, Redd A, Rittel AG, Kazanis WH, Dunham JR, Zarzabal LA, Rutter WC, Sim A, Watrous JR, Howard JT, Janak JC, Stewart IJ, Gundlapalli A (2019). Persistent Opioid Use After Combat Injury and Subsequent Long-term Risk of Abuse: A Retrospective Cohort Study. Ann Surg, 274, e957-e965.
  6. Gundlapalli AV, Jones AL, Redd A, Divita G, Brignone E, Pettey WBP, Carter ME, Samore MH, Blais RK, Fargo JD (2019). Combining Natural Language Processing of Electronic Medical Notes With Administrative Data to Determine Racial/Ethnic Differences in the Disclosure and Documentation of Military Sexual Trauma in Veterans. Med Care, 57 Suppl 6 Suppl 2, S149-S156.
  7. Gawron LM, Pettey WBP, Redd AM, Suo Y, Turok DK, Gundlapalli AV (2019). Distance Matters: Geographic barriers to long acting reversible and permanent contraception for homeless women Veterans. J Soc Distress Homeless, 28(2), 139-148.
  8. Thomas A, Khader K, Redd A, Leecaster M, Zhang Y, Jones M, Greene T, Samore M (2015). Extended models for nosocomial infection: parameter estimation and model selection. Math Med Biol, 35(suppl_1), 29-49.
  9. Redd AM, Gundlapalli AV, Divita G, Tran LT, Pettey WBP, Samore MH (2017). Comparison of Grouping Methods for Template Extraction from VA Medical Record Text. Stud Health Technol Inform, 238, 136-139.
  10. Gundlapalli AV, Redd A, Carter ME, Palmer M, Peterson R, Samore MH (2014). Exploring patterns in resource utilization prior to the formal identification of homelessness in recently returned veterans. Stud Health Technol Inform, 202, 265-8.
  11. Redd A, Carter M, Divita G, Shen S, Palmer M, Samore M, Gundlapalli AV (2014). Detecting earlier indicators of homelessness in the free text of medical records. Stud Health Technol Inform, 202, 153-6.
  12. Divita G, Shen S, Carter ME, Redd A, Forbush T, Palmer M, Samore MH, Gundlapalli AV (2014). Recognizing Questions and Answers in EMR Templates Using Natural Language Processing. Stud Health Technol Inform, 202, 149-52.
  13. Gundlapalli AV, Redd A, Carter M, Divita G, Shen S, Palmer M, Samore MH (2013). Validating a strategy for psychosocial phenotyping using a large corpus of clinical text. J Am Med Inform Assoc, 20(e2), e355-64.
  14. Gundlapalli AV, Carter ME, Palmer M, Ginter T, Redd A, Pickard S, Shen S, South B, Divita G, Duvall S, Nguyen TM, DAvolio LW, Samore M (2013). Using natural language processing on the free text of clinical documents to screen for evidence of homelessness among US veterans. AMIA Annu Symp Proc, 2013, 537-46.
  15. Gundlapalli A, Divita G, Carter M, Shen S, Palmer M, Forbush T, South B, Redd A, Sauer B, Samore M (3/2013). Extracting Surveillance Data from Templated Sections of an Electronic Medical Note: Challenges and Opportunities. Online J Public Health Inform, 5(1).
  16. Forbush TB, Gundlapalli AV, Palmer MN, Shen S, South BR, Divita G, Carter M, Redd A, Butler JM, Samore M (2013). "Sitting on pins and needles": characterization of symptom descriptions in clinical notes". AMIA Jt Summits Transl Sci Proc, 2013, 67-71.