PSAM 16 Conference Paper Overview
Welcome to the PSAM 16 Conference paper and speaker overview page.
Lead Author: Leticia Hengartner Co-author(s): Eric Allison, eric@joby.aero
George Ligler, gtligler@tamu.edu
Zahra Mohaghegh, zahra13@illinois.edu
| National Academies' Panel on Evaluation of the Transport Airplane Risk Assessment Methodology |
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| The U.S. Congress mandated the FAA to enter into an agreement with the National Academies of Sciences, Engineering, and Medicine (National Academies) to develop a report regarding the methodology and effectiveness of the Transport Airplane Risk Assessment Methodology (TARAM) process used by the FAA. TARAM is used to identify potential risks in currently operating airplanes, which will alert FAA officials if they need to take action to prevent potential accidents. The National Academies appointed an ad hoc committee of 12 members to undertake a study to evaluate the FAA’s TARAM process. This panel discussion will cover: Role and objectives of TARAM within the FAA’s overall safety oversight system; Assessment of the TARAM analysis process; Effectiveness of TARAM for the purposes of improving aviation safety; Recommendations to improve the methodology and effectiveness of TARAM as an element of aviation safety. |
Paper LE338 Preview
Author and Presentation Info
Presentation only, a full paper is not available.
Lead Author Name: Leticia Cuellar-Hengartner (leticia@lanl.gov)
Bio: LETICIA CUELLAR-HENGARTNER is a data scientist at Los Alamos National Laboratory (LANL) in the Information Systems and Modeling group. She has expertise in statistics, stochastic modeling, machine learning, and model validation. Her work at LANL includes agent-based models, predicting disaster response, risk assessment of illegal trafficking of nuclear materials, modeling user behavior analytics, and uncertainty quantification for disease propagation models. She is the PI for an Ernst & Young founded project that focuses on developing forecasting models for audit quality, a project studying the effect of human mobility on disease propagation, and lead as co-PI the Probabilistic Effectiveness Methodology project that performs probabilistic risk assessments of nuclear smuggling. She is the recipient of the LANL 2012 Distinguished Performance Award and the 2020 and 2011 Los Alamos Award Program. She earned her masters and Ph.D. in statistics from the University of California, Berkeley.
Country: United States of America
Company: Los Alamos National Laboratory
Job Title: Scientist
Bio: LETICIA CUELLAR-HENGARTNER is a data scientist at Los Alamos National Laboratory (LANL) in the Information Systems and Modeling group. She has expertise in statistics, stochastic modeling, machine learning, and model validation. Her work at LANL includes agent-based models, predicting disaster response, risk assessment of illegal trafficking of nuclear materials, modeling user behavior analytics, and uncertainty quantification for disease propagation models. She is the PI for an Ernst & Young founded project that focuses on developing forecasting models for audit quality, a project studying the effect of human mobility on disease propagation, and lead as co-PI the Probabilistic Effectiveness Methodology project that performs probabilistic risk assessments of nuclear smuggling. She is the recipient of the LANL 2012 Distinguished Performance Award and the 2020 and 2011 Los Alamos Award Program. She earned her masters and Ph.D. in statistics from the University of California, Berkeley.
Country: United States of America
Company: Los Alamos National Laboratory
Job Title: Scientist