HELLO! I’M ÇAĞLAR ÇAĞLAYAN
I'm a researcher, working on the topics of clinical decision-making under uncertainty. My research mainly focuses on disease management and health service operations.
About Me
Data Analyst; Decision-Making Scientist; Math. Modeling & Simulation Expert; Healthcare Systems Engineer; Analytics & Operations Research Scientist
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I am a health systems data and decision-making scientist at Johns Hopkins University Applied Physics Laboratory. My research interests include mathematical modeling, optimization under uncertainty, and data- and decision-centric healthcare analytics. I utilize a broad range of analytical methods and collaborate with healthcare researchers to conduct data-driven research with methodological contributions and clinically impactful findings. I plan to continue my career by tackling pressing and important healthcare problems and conducting research on medical decision-making for disease management (control, prevention, detection and treatment) and health service operations.
Please contact me at caglar.caglayan@jhuapl.edu
My Experience
BACKGROUND & EXPERTISE
HEALTH SYSTEMS DATA & DECISION-MAKING SCIENTIST, NATIONAL HEALTH
Johns Hopkins University Applied Physics Laboratory, Laurel, MD
AUGUST 2020 – PRESENT
ASSISTANT PROFESSOR,
DEPARTMENT OF INDUSTRIAL ENGINEERING
Clemson University - Clemson, SC
AUGUST 2019 – AUGUST 2020
RESEARCH ASSOCIATE (ADVISOR: SEAN BARNES),
ROBERT H. SMITH SCHOOL OF BUSINESS
Uni. of Maryland – College Park, MD
AUGUST 2018 – AUGUST 2019
RESEARCH TRAINEE, DIVISION OF GENERAL INTERNAL MEDICINE
Mayo Clinic – Rochester, MN
AUGUST 2017 - AUGUST 2018
RESEARCH INTERN, DEPARTMENT OF BIOMEDICAL INFORMATICS
Emory University – Atlanta, GA
MAY 2017 - AUGUST 2017
RESEARCH INTERN, CENTER FOR THE SCIENCE OF HEALTH CARE DELIVERY
Mayo Clinic – Rochester, MN
JUNE 2016Â - AUGUST 2016
RESEARCH INTERN, CENTER FOR THE SCIENCE OF HEALTH CARE DELIVERY
Mayo Clinic – Rochester, MN
MAY 2015 - AUGUST 2015
Education
WHAT I’VE LEARNED
PH.D. - OPERATIONS RESEARCH
TITLE: Analytics Approaches To Improve Strategic, Operational, And Clinical Decision-Making In Healthcare
ADVISOR: Turgay Ayer
AUGUST 2019
Georgia Institute of Technology
Atlanta, GA
M.S. - OPERATIONS RESEARCH
DECEMBER 2015
Georgia Institute of Technology
Atlanta, GA
MASTER OF INDUSTRIAL ENGINEERING
DECEMBER 2013
North Carolina State University
Raleigh, NC
B.S. - INDUSTRIAL ENGINEERING
JUNE 2011
Boğaziçi University
Istanbul, TURKEY
My Skills
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Expertise: Data-driven Decision-making under Uncertainty
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Application Areas: Disease Management and Health Service Operations
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Primary Methods: Optimization, Queuing Theory, Survival Analysis, Simulation, Machine Learning
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Software: C, C++, Matlab, R, Python, Mathematica, GAMS, IBM Cplex, Simio, Arena, M. Office, Latex, Tensorflow
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My research interests include mathematical modeling, optimization under uncertainty, and data- and decision-centric analytics. I utilize a broad range of analytical methods and collaborate with healthcare providers and researchers to conduct data-driven research with methodological contributions and clinically impactful findings.
DISEASE MANAGEMENT
Medical-Decision Making for the Control, Prevention, Detection, and Treatment of Chronic and Infectious Diseases
HEALTH SERVICE OPERATIONS
Analysis and Optimization of Complex Health Service Operations
Publications
COVID-19 MONOCLONAL ANTIBODY INFUSION SITE CALCULATOR
ÇaÄŸlayan Ç., Thornhill, J., Stewart, M.A., Lambrou, A.S., Richardson, D., Rainwater-Lovett, K., Freeman, J.D., Pfundt, T. and Redd, J.T., 2022. Staffing and Capacity Planning for SARS-CoV-2 Monoclonal Antibody Infusion Facilities: A Performance Estimation Calculator based on Discrete-Event Simulations. Frontiers in Public Health, p.2415. https://www.frontiersin.org/articles/10.3389/fpubh.2021.770039/full
MULTI-DRUG RESISTANT ORGANISMS IN ICU - PREDICTIVE MODELING
ÇaÄŸlayan Ç., Barnes S., Pineles L., Harris, A, Klein E.. A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized with Multi-drug Resistant Organisms. Frontiers in Public Health. Published online on March, 2022. https://www.frontiersin.org/articles/10.3389/fpubh.2022.853757
ÇaÄŸlayan Ç., Goodman K., Barnes S., Mehta A., Pineles L., Harris, A, Klein E. Development, Transportability, Generalizability, and External Validation of Machine Learning-Based Models for Predicting Multi-Drug Resistant Organism Carriage at ICU Admission. Working Paper.
FL MULTI-STATE SURVIVAL
Caglayan C., Terawaki H., Ayer T., Goldstein J., Rai. A., Chen Q., & Flowers C. R. Assessing the Effectiveness of Treatment Sequences for High-Risk Follicular Lymphoma Patients with a Multi-state Model. Clinical Lymphoma, Myeloma & Leukemia. Published online on Jan 3, 2019: https://www.sciencedirect.com/science/article/pii/S2152265018311248
Dixon J., ÇaÄŸlayan Ç., Salles G., … , Shi Q., and Flowers C. R. A Multistate Survival Analysis for Patients with Follicular Lymphoma (FL) Using 13 First-Line Randomized Trials from FL Analysis of Surrogate Hypothesis (FLASH) Group. Working Paper. https://ashpublications.org/blood/article-abstract/134/Supplement_1/2812/423469
ÇaÄŸlayan Ç., Mehta A., Chihara D., and Flowers C. Investigation of Watchful Waiting and Sequential Follicular Lymphoma Treatments Leveraging National Lymphocare Study Data: A Multistate Survival Analysis Study. Working Paper.
DLBCL MULTI-STATE SURVIVAL
Caglayan C., Goldstein J., Ayer T., Rai. A., & Flowers C. R. A Population-based Multi-state Model for Diffuse Large B Cell Lymphoma-Specific Mortality in Older Patients. Cancer. Published online on Feb 1, 2019: https://onlinelibrary.wiley.com/doi/abs/10.1002/cncr.31981
ÇaÄŸlayan Ç., Dixon J., Salles G., … , Shi Q., and Flowers C. R. The Clinical Course Of Diffuse Large B-Cell Lymphoma (DLBCL) Over Time: A Multistate Survival Analysis Using Meta-Data From 13 First-Line Randomized Trials. Working Paper. https://onlinelibrary.wiley.com/doi/10.1002/hon.56_2630
MULTI-MODALITY BREAST CANCER SCREENING HIGH RISK
Caglayan C., Ayer T., & Ekwueme D.U. Assessing Multi-Modality Screening Strategies for Women at High Risk of Developing Breast Cancer. Major Revision (Round One) Operations Research.https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3139779
ER PHYSICIAN STAFFING - QUEUING NETWORK
Caglayan C., Liu Y., Pasupathy K., Nestler D., Ayer T., & Sir M.Y. Physician Staffing in Emergency Rooms (ERs): Opening the Black-box of ER Care via a Multi-Class Multi-Stage Network. submitted to Management Science.
MICROSIMULATION REVIEW
Caglayan C., Terawaki H., Chen Q., Ayer T., & Flowers C. R. Microsimulation Modeling in Oncology. JCO Clinical Cancer Informatics. http://ascopubs.org/doi/10.1200/CCI.17.00029
PUBLICATIONS FOR FUN (NON PEER-REVIEWED)
ÇaÄŸlayan Ç. The Use of Quantitative Methods with Two Different Perspectives: Data-Centric versus Problem-Centric. INFORMS OR/MS Tomorrow. https://pdfs.semanticscholar.org/396f/f227f9fc67cdb948723539981da3c7ea1d1c.pdf
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