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GE Technical Reports are internal publications that undergo peer review from senior technical staff and management.

GE Global Research
(19) “Efficient Robust Design Optimization using 
        Gaussian Process and Intelligent Sampling”
        2018 Multidisciplinary Analysis &
        Optimization Conference.

(18) “Polynomial Representation of the Gaussian
        ASME IDETC/CIE 2018.

(17) “A Gaussian Process Modeling Approach for
        Fast Robust Design with Uncertain Inputs”
        ASME IGTI, 2018 (paper ID: GT2018-77007)

“Bayesian multi-source modeling with legacy
        GE technical report, 2018.

(15) “An intelligent sampling framework for multi
        objective optimization in high-dimensional
        design space”
        SciTech, 2018.

(14) “A Gaussian process modeling approach for
        fast robust design with uncertain inputs”
        GE technical report, 2017.

(13) “Increasing the efficiency and accuracy of
        Bayesian Hybrid Modeling with Adaptive
        Sequential Monte Carlo (ASMC).”
        GE technical report, 2017.

(12) “Portable Bayesian Hybrid Modeling”
        GE technical report, 2017.

(11) “Documentation of the GE Piston GUI and
        Transient Calibration of Large Data Sets”
        GE technical report, 2017.

(10) “Predictive analytics with an advanced  
        Bayesian modeling framework”
        MODSIM World, 2017

 “Modern Probabilistic Methods for Pump 
 Predictability and Optimization at the System   
 and Component Levels”
      GE technical report, 2016.

(8) “Expected-Improvement Based Methods for     
     Adaptive Sampling in Multi-Objective     
     Optimization Problems”
     ASME IDETC/CIE, 2016.

(7) “Adaptive simulation selection for the discovery
     of the ground state line of binary alloys with a
     limited computational budget.”
     Chapter in:
     Recent Progress and Modern Challenges in 
      Applied Mathematics, Modeling and 
      Computational Science,
      Springer-Verlag, 2017.

“Quantifying uncertainties in first-principles alloy thermodynamics using cluster expansions.”
Journal of Computational Physics, 2016.

(5) “Predicting low-thermal-conductivity Si-Ge 
     nanowires with a modified cluster expansion
     Physical Review B, 2015.
     PDF (free)
      ©2015 American Physical Society

(4) “Bayesian uncertainty quantification in the 
     evaluation of alloy properties with the cluster
     expansion method.”
     Computer Physics Communications, 2014.

(3) “Relative entropy as model selection    
     tool in cluster expansions.”
     Physical Review B, 2013.
     PDF (free)
      ©2013 American Physical Society

(2) “Hydronium-dominated ion transport in    
     carbon-dioxide-saturated electrolytes
     at low salt concentrations in
     Physical Review E, 2011.
     PDF (free)
      ©2011 American Physical Society

(1) “Low-loss polarization-maintaining
     fusion splicing of single-mode fibers
     and hollow-core photonic crystal fibers,    
     relevant for monolithic fiber laser pulse
     Optics Express, 2009.


GE Global Research
ASME V&V, Minneapolis, MN, US
May 2018
        “Optimal Information Acquisition Algorithms
        for Inferring the Order of Sensitivity Indices”
        Link to conference

(14) ASME IDETC/CIE, Quebec City, Canada
        To be held in August 2018.
        “Polynomial Representation of the
        Gaussian Process”.
        Paper ID: DETC2018-85145.

(13)  AIAA Aviation and Aeronautics Forum and
        Exposition, GA, US
        To be held in June 2018.
        “Efficient robust design optimization using
         Gaussian process and intelligent sampling”.

(12) IGTI ASME, Oslo, NO
        To be held in June 2018.
        “A Gaussian Process Modeling Approach for
        Fast Robust Design with Uncertain Inputs”.
        Link, Paper ID: TE2018-77007

AIAA SciTech Forum, FL, US    
Talk 1: “Bayesian Multi-Source Modeling with  
 Legacy Data.”
        Talk 2: “Intelligent sampling framework for 
         multi-objective optimization in high 
         dimensional design space.”

(10) ASME V&V, Las Vegas, NV, US     
       “Heteroskedastic Gaussian Process Meta-
       models for Improved Predictive Uncertainties.”
       the talk (p. 19).

MODSIM World, Virginia Beach, VA, US
Analytics and decision making.

(8) ASME IDETC/CIE, Charlotte, NC, US

(7) TMS (144th), Orlando, FL, US
      PDF of talk 1.
      PDF of talk 2.    

(6) University of Warwick, UK
     Warwick centre for predictive modeling Seminar
     PDF of talk.

(5) University of Florida, FL, US
     MSE Department
(4) TMS (143rd), San Diego, CA, US

(3) SIAM on UQ 2014, Savannah, Georgia, US
     download presentation.

(2) USNCCM (12th), Raleigh, NC, US

(1) TMS (142nd), San Antonio, TX, US
     download presentation.


Jesper Toft Kristensen

Peer Reviewed Publications and Book Chapters
Conference and Seminar Talks

For my full citations list: Link to Citations Profile