Search Results - "Puranik, Tejas G."

Classification and Analysis of Go-Arounds in Commercial Aviation Using ADS-B Data by Kumar, Satvik G., Corrado, Samantha J., Puranik, Tejas G., Mavris, Dimitri N.

“…Go-arounds are a necessary aspect of commercial aviation and are conducted after a landing attempt has been aborted. It is necessary to conduct go-arounds in…”
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Attrition Risk and Aircraft Suitability Prediction in U.S. Navy Pilot Training Using Machine Learning by Prasad-Rao, Jubilee, Pinon Fischer, Olivia J, Rowe, Neil C, Williams, Jesse R, Puranik, Tejas G, Mavris, Dimitri N, Natali, Michael W, Tindall, Mitchell J, Atkinson, Beth W

“…The cost to train a basic qualified U.S. Navy fighter aircraft pilot is nearly USD 10 M. The training includes primary, intermediate, and advanced stages, with…”
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Application of structural topic modeling to aviation safety data by Rose, Rodrigo L., Puranik, Tejas G., Mavris, Dimitri N., Rao, Arjun H.

“…Data-driven frameworks for analyzing aviation safety data have recently gained traction. Text-based machine learning techniques often rely purely on word…”
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Natural Language Processing Based Method for Clustering and Analysis of Aviation Safety Narratives by Rose, Rodrigo L., Puranik, Tejas G., Mavris, Dimitri N.

“…The complexity of commercial aviation operations has grown substantially in recent years, together with a diversification of techniques for collecting and…”
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Critical Parameter Identification for Safety Events in Commercial Aviation Using Machine Learning by Lee, HyunKi, Madar, Sasha, Sairam, Santusht, Puranik, Tejas G., Payan, Alexia P., Kirby, Michelle, Pinon, Olivia J., Mavris, Dimitri N.

“…In recent years, there has been a rapid growth in the application of data science techniques that leverage aviation data collected from commercial airline…”
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Predicting Airport Runway Configurations for Decision-Support Using Supervised Learning by Puranik, Tejas G., Memarzadeh, Milad, Kalyanam, Krishna M.

“…One of the most critical tasks in air traffic management is runway configuration management (RCM). It deals with the optimal selection of runways for arrivals…”
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Machine Learning Approach for Aircraft Performance Model Parameter Estimation for Trajectory Prediction Applications by Rohani, Aida Sharif, Puranik, Tejas G., Kalyanam, Krishna M.

“…Inaccurate prediction of aircraft trajectory by ground-based decision support tools (DST) is a major concern in air traffic management (ATM). Aircraft…”
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Application of Trajectory Clustering for Aircraft Conflict Detection by Madar, Sasha, Puranik, Tejas G., Mavris, Dimitri N.

“…This paper presents the application of machine learning and open-source data to improve the prediction capability of conflict between aircraft in terminal…”
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Towards online prediction of safety-critical landing metrics in aviation using supervised machine learning by Puranik, Tejas G., Rodriguez, Nicolas, Mavris, Dimitri N.

“…•Provides a novel online predictive model of aircraft landing performance using data collected on-board an aircraft during the approach phase.•Demonstrates…”
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Flight Data Driven System Identification Using Neural Networks for Landing Safety Assessment by Lee, HyunKi, Puranik, Tejas G., Fischer, Olivia Pinon, Mavris, Dimitri N.

“…Multiple studies and reports have identified threshold exceedance precursors that significantly contribute to flight accidents. Reducing the occurrence of…”
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Aircraft Braking Performance Classification Through Braking Rollout Clustering by Lee, HyunKi, Payan, Alexia P., Anvid, David, Zhang, Wenxin, Puranik, Tejas G., Kirby, Michelle, Mavris, Dimitri N.

“…The IATA safety report shows that runway excursions are the major cause of accidents when organized by flight phase. Additionally, runway overrun of the…”
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Multi-level aircraft feature representation and selection for aviation environmental impact analysis by Gao, Zhenyu, Kampezidou, Styliani I., Behere, Ameya, Puranik, Tejas G., Rajaram, Dushhyanth, Mavris, Dimitri N.

“…A wholesome understanding of aviation’s environmental impacts is indispensable to the realization of a sustainable future of aviation. An accurate assessment…”
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A clustering-based quantitative analysis of the interdependent relationship between spatial and energy anomalies in ADS-B trajectory data by Corrado, Samantha J., Puranik, Tejas G., Fischer, Olivia Pinon, Mavris, Dimitri N.

“…As air traffic demand grows, robust, data-driven methods are required to ensure that aviation systems become safer and more efficient. The terminal airspace is…”
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Trajectory Clustering within the Terminal Airspace Utilizing a Weighted Distance Function by Samantha J. Corrado, Tejas G. Puranik, Oliva J. Pinon, Dimitri N. Mavris

“…To support efforts to modernize aviation systems to be safer and more efficient, high-precision trajectory prediction and robust anomaly detection methods are…”
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An ODE-fitting approach to estimate critical aircraft performance parameters for trajectory prediction by Puranik, Tejas G., Sharif Rohani, Aida, Kalyanam, Krishna M.

“…Ground-based decision support tools (DST) in air traffic management (ATM) typically perform trajectory prediction based on aircraft performance model (APM)…”
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Multi-Class Multiple Instance Learning for Predicting Precursors to Aviation Safety Events by Bleu-Laine, Marc-Henri, Puranik, Tejas G, Mavris, Dimitri N, Matthews, Bryan

“…In recent years, there has been a rapid growth in the application of machine learning techniques that leverage aviation data collected from commercial airline…”
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