Subhayan De, Ph.D. (This website is not maintained anymore. Please visit www.subhayande.com)

 
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Postdoctoral Associate
University of Colorado Boulder

A pdf version of my CV from 2018 is available here.

I am currently a postdoctoral associate in the Department of Aerospace Engineering sciences at the University of Colorado Boulder. My research here focuses on Topology Optimization, Physics-driven Machine Learning, and Uncertainty Quantification.

Previously, I earned my Ph.D. from USC (University of Southern California). My doctoral research focused on model validation, computationally efficient structural system identification and control. During my Ph.D., I was supported by a Viterbi Ph.D. Fellowship at USC.

I earned my Master's degrees in Civil Engineering with specialization in Structural Engineering from Indian Institute of Science (IISc) in 2013 and in Electrical Engineering from University of Southern California in 2016. I carried out research on Bayesian model selection and was supported by scholarships from Ministry of Human Resource and Development, Govt. of India during my stay at IISc.

I received my Bachelor of Engineering (B.Eng.) degree in Civil Engineering from Jadavpur University in 2011. My research topic was Application of Genetic Algorithm in Civil Engineering Problems.

Education:

  • Ph.D. in Civil Engineering (2018) University of Southern California, Los Angeles
    GPA - 4.0/4.0
  • M.S. in Electrical Engineering (2016) University of Southern California, Los Angeles
    GPA - 4.0/4.0
  • M.Eng. in Structural Engineering (2013) Indian Institute of Science, Bangalore
    GPA - 7.5/8.0 (Rank: 1st)
  • B.Eng. in Civil Engineering (2011) Jadavpur University, Kolkata
    GPA - 9.28/10.00 (Rank: 3rd)

Experience:

  • Postdoctoral Associate (June 2018 - present)
    University of Colorado, Boulder
    Collaborators: Alireza Doostan, Ph.D., and Kurt Maute, Ph.D.
  • Graduate Research Assistant (2014, 2016-2017)
    University of Southern California
    Supervisor: Erik A. Johnson, Ph.D.
  • Graduate Research Assistant (August, 2012 to July, 2013)
    Indian Institute of Science
    Supervisors: C. S. Manohar, Ph.D., and Debraj Ghosh, Ph.D.
  • Lecturer for Random Vibrations (Spring 2019) Ann and H.J. Smead Department of Aerospace Engineering Sciences
    University of Colorado, Boulder
  • Teaching Assistant for CE 408: Risk Analysis in Civil Engineering (Fall 2017)
    Sonny Astani Department of Civil and Environmental Engineering
    University of Southern California
  • Teaching Assistant for CE 529a: Finite Element Analysis (Summer 2017)
    Sonny Astani Department of Civil and Environmental Engineering
    University of Southern California
  • Teaching Assistant for CE 205: Statics (Fall 2016)
    Sonny Astani Department of Civil and Environmental Engineering
    University of Southern California
  • Asia-Pacific Summer School on Smart Structures Technology (July - August, 2015)
    Department of Civil and Environmental Engineering
    University of Illinois at Urbana-Champaign
  • Uncertainty Quantification Summer School (August, 2016)
    Sonny Astani Department of Civil and Environmental Engineering
    University of Southern California

Research Interests:

  • Topolog Optimization under Uncertainty (TOuU)
  • Machine Learning for Uncertainty Quantification
  • Probabilistic Model Validation Framework
  • Efficient Bayesian Model Selection
  • Efficient Optimal Design of Passive Structural Control Devices
    • Topolog Optimization under Uncertainty (TOuU) (2018 - ) University of Colorado Boulder

      This work is done in collaboration with Prof. Alireza Doostan and Prof. Kurt Maute of CU-Boulder.
      Our contributions are:
      • Development of a stochastic gradient approach for TOuU (paper).
      • Development of bi-fidelity stochastic gradient descent algorithms with proven linear convergence (paper).


    • Machine Learning for Uncertainty Quantification (2019 - ) University of Colorado Boulder

      This work is done in collaboration with Prof. Alireza Doostan of CU-Boulder and Dr. Matthew Reynolds of National Renewable Energy Laboratory (NREL).
      Our contributions are:
      • Development of transfer learning strategies for uncertainty quantification of complex engineering systems.
      • Application of the proposed strategies to multi-physics engineering prblems.
    • Probabilistic Model Validation Framework (2014 - ) University of Southern California

      Development of a computationally efficient model validation framework applicable to models from vast domains.
      This work is done in collaboration with Prof. Steven Wojtkiewicz of Clarkson University and Dr. Patrick T. Brewick of United States Naval Research Laboratory.
      Our contributions are:
      • Introduction of false discovery rate and likelihood-bound in model falsification (paper).
      • A probabilistic machine learning framework is proposed for efficient validation of models (paper).
      • Applications to structural, turbulence, and material modeling problems.



    • Efficient Bayesian Model Selection (2013 - ) University of Southern California

      Development of a computationally efficient method using Nonlinear Volterra type Integral Equations (NVIE) to model selection problems.
      This work is done in collaboration with Prof. Steven Wojtkiewicz of Clarkson University and Dr. Patrick T. Brewick of United States Naval Research Laboratory.
      Our contributions are (paper):
      • Incorporating dynamic time history data for nonlinear models as the modal parameters changes with time in nonlinear models.
      • Using NVIE approach the speedup is upto three orders of magnitude compared to traditional nonlinear solvers.
      • The approach is demonstrated using a 100 DOF building structure subjected to earthquake and a 1623 DOF three-dimensional building subjected to wind.

    • Figure: Efficient Bayesian model selection of a 100 DOF building structure.

    • Efficient Optimal Design of Passive Structural Control Devices (2013 - ) University of Southern California

      Development of computationally efficient design procedure of passive control devices for complex structures using NVIE approach.
      This work is done in collaboration with Prof. Steven Wojtkiewicz of Clarkson University.
      The proposed method has the following characteristics (paper):
      • Realizable computation time for large and complex structures.
      • Trade-off between accuracy and speedup exists.
      • Uncertainty in the existing structure can be incorporated.
      • Application in a benchmark cable-stayed bridge.
      bridge pic
      Figure: Efficient optimal design of passive control devices for a cable-stayed bridge.


    • Bayesian Model Selection in Structural Engineering (August 2012 to July 2013) Indian Institute of Science

      A rigorous study on prior sensitivity, incorporation of training and validation data in Bayesian model selection.

    Academic Background:

    • Dynamics: Structural Dynamics, Finite Element Method in Dynamics, Random Vibrations and Structural Reliability ....
    • Control Theory: Linear Feedback Control, Linear System Theory, Robust and Multivariable Control ....
    • Probability, Ordinary Differential Equations, Finite element method, Digital Signal Processing, Computational tools for Optimization, Machine Learning, Wavelets ....

    Publications:

    Journals

    1. De, S., Wojtkiewicz S.F. and, Johnson, E.A. "Computationally Efficient Optimal Design of Passive Control Devices for a Benchmark Cable-Stayed Bridge", Structural Control and Health Monitoring, 2016.
    2. De, S., Johnson, E.A., Wojtkiewicz S.F. and, Brewick, P.T. "Computationally-Efficient Bayesian Model Selection for Locally Nonlinear Structural Dynamical Systems", Journal of Engineering Mechanics (Editor's choice) (2018).
    3. De, S., Brewick, P.T., Johnson, E.A. and, Wojtkiewicz S.F. "Investigation of Model Falsification using Error and Likelihood Bounds with Application to a Structural System", Journal of Engineering Mechanics (Editor's choice) (2018).
    4. De, S., Brewick, P.T., Johnson, E.A. and, Wojtkiewicz S.F. "A Probabilistic Hybrid Framework for Model Validation of Dynamic Systems", Mechanical Systems and Signal Processing (2019).
    5. De, S., Hampton, J., Maute, K. and, Doostan A. "Topology Optimization under Uncertainty using a Stochastic Gradient-based Approach", Structural and Multidisciplinary Optimization, (in review).
    6. De, S., Hampton, J., Maute, K. and, Doostan A. “Bi-fidelity Stochastic Gradient Descent for Structural Optimization under Uncertainty", Computational Mechanics,, (in review).
    7. De, S., Britton, J., Reynolds, M. and, Doostan A. "Transfer Learning of Neural Networks using Bi-fidelity Data for Uncertainty Propagation", International Journal for Uncertainty Quantification, (in review).
    8. De, S., Johnson, E.A. and, Wojtkiewicz S.F. "Likelihood level adapted estimation of marginal likelihood for Bayesian model selection", Mechanical Systems and Signal Processing (in review).
    9. De, S., Brewick, P.T., Johnson, E.A. and, Wojtkiewicz S.F. "Robust Prediction of Structural Systems using Model Falsification", Journal TBD (in preparation).
    10. De, S., Brewick, P.T., Johnson, E.A. and, Wojtkiewicz S.F. "A Probabilistic Model Validation Framework for Reynolds Averaged Navier-Stokes Models for Turbulence", Journal TBD (in preparation).

    Conference Proceedings

    1. De, S., Kamalzare, M., Johnson, E.A. and , Wojtkiewicz S.F., "Efficient Optimal Design of Passive Structural Control Devices for Complex Structures", ASCE Engineering Mechanics Institute Conference, August 2014 . McMaster University, ON, Canada.
    2. De, S., Kamalzare, M., Johnson, E.A. and , Wojtkiewicz S.F., "Computationally-Efficient Bayesian Model Selection for Structural Systems with Local Nonlinearities", ASCE Engineering Mechanics Institute Conference, August 2014, McMaster University, ON, Canada.
    3. De, S., Johnson, E.A. and , Wojtkiewicz S.F., "Efficient Optimal Design-Under-Uncertainty of Passive Structural Control Devices", 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12, July 2015, Vancouver, BC, Canada.
    4. De, S., Johnson, E.A. and , Wojtkiewicz S.F., "Fast Bayesian Model Selection with Application to Large Locally-Nonlinear Dynamic Systems ", 6th International Conference on Advances in Experimental Structural Engineering, 11th International Workshop on Advanced Smart Materials and Smart Structures Technology, August 1-2, 2015, University of Illinois, Urbana-Champaign, USA.
    5. De, S., Johnson, E.A. and , Wojtkiewicz S.F., Brewick, P.B., "Efficient Bayesian Model Selection for Locally Nonlinear Systems incorporating Dynamic Measurements", 10th International Workshop on Structural Health Monitoring (IWSHM), September 2015, Stanford University, CA, USA.
    6. De, S., Brewick, P.T., Johnson, E.A. and, Wojtkiewicz S.F. "Exploration of Error Rate Criteria to Decide Bounds for Model Falsification'', ASCE Engineering Mechanics Institute Conference, May, 2016, Vanderbilt University, Nashville, TN, USA.
    7. De, S., Brewick, P.T., Johnson, E.A., Wojtkiewicz S.F. and, Bermejo-Moreno I. "Error and Likelihood Bounds for Falsification of Dynamical Models'', IMAC XXXV Conference, 2017, Hyatt Regency Orange County, CA, USA.
    8. De, S., Johnson, E.A. and, Wojtkiewicz S.F. "Efficient Uncertainty Quantification for Locally Nonlinear Dynamical Systems'', ASCE Engineering Mechanics Institute Conference, 2017, University of California, San Diego, CA, USA.
    9. De, S., Brewick, P.T., Johnson, E.A. and, Wojtkiewicz S.F. "Model Falsification in a Bayesian Framework'', ASCE Engineering Mechanics Institute Conference, 2017, University of California, San Diego, CA, USA.
    10. De, S., Yu, T., Johnson, E.A. and, Wojtkiewicz S.F. "Model Validation of a 4 Story Base Isolated Building using Seismic Shake-Table Experiments'', 11th U.S.~National Conference on Earthquake Engineering, 2018, Los Angeles, CA, USA.
    11. De, S., Johnson, E.A. and, Wojtkiewicz S.F. "Uncertainty Quantification of Locally Nonlinear Dynamical Systems using Polynomial Chaos Expansion", SIAM Conference on Uncertainty Quantification (UQ18), 2018, Hyatt Regency Orange County, Garden Grove, CA, USA.
    12. De, S., Dasgupta, A., Johnson, E.A. and, Wojtkiewicz S.F. "Probabilistic Model Validation of Large-Scale Systems using Reduced Order Models", SIAM Conference on Uncertainty Quantification (UQ18), 2018, Hyatt Regency Orange County, Garden Grove, CA, USA.
    13. De, S., Yu, T., Dasgupta, A., Johnson, E.A. and, Wojtkiewicz S.F. "Probabilistic Model Validation of the Isolation layer of a Full-Scale Four-Story Base-Isolated Building", ASCE Engineering Mechanics Institute Conference, , 2018, Massachusetts Institute of Technology, Cambridge, MA, USA.
    14. Dasgupta A., De, S., Yu, T., Johnson, E.A. and, Wojtkiewicz S.F. "Probabilistic validation of material models", ASCE Engineering Mechanics Institute Conference, , 2018, Massachusetts Institute of Technology, Cambridge, MA, USA.
    15. De, S., Maute, K. and, Doostan, A. "Topology Optimization under Uncertainty using Stochastic Gradients", Topology Optimization Roundtable,, 2019, Albuquerque Marriot, Albuquerque, NM, USA.
    16. De, S., Maute, K. and, Doostan, A. "Optimization under Uncertainty Using Stochastic Gradients", 15th U.S. Congress on Computational Mechanics, 2019, Austin, TX, USA.
    17. De, S., Johnson, E.A. and, Wojtkiewicz S.F. "Efficient Evidence Estimation for Bayesian Model Selection", ASCE Engineering Mechanics Institute Conference, , 2019, California Institute of Technology, Pasadena, CA, USA.
    18. Glaws, A., King, R, Reynolds, M., Doostan, A. and, De, S. "Physics-informed Deep Learning for Multi-fidelity Uncertainty Quantification", Workshop on Research Challenges and Opportunities at the interface of Machine Learning and Uncertainty Quantification, 2019, Los Angeles, CA, USA.

    Mechanics of Deformable Bodies:

    Probability and Statistics for Engineers

    Model Validation:

    Introduction to Statistics using Python:

    Invited Talks:

    • Department of Aerospace Engineering Sciences, University of Colorado, Boulder, "Incorporating Uncertainty into Modeling: Applications to Model Validation and Design Optimization", November, 2019.
    • Department of Civil Engineering, Indian Institute of Technology, Kanpur, "Applications of Probabilistic Hybrid Model Validation Framework to Structural Problems", January, 2018.
    • Department of Civil Engineering, Indian Institute of Science, Bangalore, "Probabilistic Hybrid Model Validation Framework", December, 2017.
    • Department of Civil and Environmental Engineering, University of Southern California, "Efficient Bayesian Model Selection for Locally Nonlinear Systems incorporating Dynamic Measurements", March, 2015.

    Synergistic Activities:

    • Organized and chaired a minisymposium on “Advances in Design Optimization under Uncertainty” at the 15th U.S. Congress on Computational Mechanics, July-August, 2019.
    • Chaired a session on “Polynomial Chaos and Polynomial Approximation” at the SIAM Conference on Uncertainty Quantification (UQ18), Hyatt Regency Orange County, Garden Grove, California, USA, April, 2018.
    • Reviewer for Structural Control and Health Monitoring, Computer Methods in Applied Mechanics and Engineering, Computational Geomechanics, ASCE Journal of Bridge Engineering, and AIAA Journal.

    Honors and Awards:

    • Recipient of best dissertation award in Civil Engineering at University of Southern California, 2018.
    • Recipients of Viterbi PhD Fellowship (2013-2017) and Gammel scholarship (Spring 2017) from University of Southern California.
    • Recipient of Ministry of Human Resource Development, Govt. of India Scholarship for Graduate studies (August, 2011-July, 2013).
    • Received travel grants from USC Graduate Student Government for attending ASCE Engineering Mechanics Institute Conference, 2014 and 2017, IMAC XXXV Conference, 2017.
    • ASCE Engineering Mechanics Institute Conference Probabilistic Methods student paper competition finalist in 2014, 2017.
    • Received scholarship from National Science Foundation to attend the Asia-Pacific Summer School on Smart Structures Technology, 2015.
    • Selected as Research Assistant of the month in March 2015.
    • GATE (Graduate Aptitude Test in Engineering) All India Rank: 5th in the year 2011 (Civil Engineering).
    • University Bronze Medal in Jadavpur University.

    Computer Skills:

    • Programming: C, FORTRAN, Python.
    • Scientific tools: MATLAB, Mathematica, Maple, ANSYS, AUTOCAD.
    • OS: Windows, Mac OSX, Linux/Unix.

    Languages:

    • English: Fluent
    • Bengali: Mother-tongue
    • Hindi: Fluent
    pic_with_prof

    (from left) Agnimitra Dasgupta, Tianhao Yu, Prof. Erik Johnson, Subhayan De, Qian "Monica" Fang (2017).

    pic_with_group1

    (from left) Dr. Brewick, Tianhao Yu, Qian "Monica" Fang, Subhayan De (2016).

    pic_with_prof

    With my advisor Prof. Erik A. Johnson (2015).

    Contact:

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