Dimitris Giovanis

Scientific Machine Learning & Uncertainty Quantification

Outreach

Development of a Coursera course on Uncertainty Quantification (Under development).

Reviewer for peer-review journals

  • Journal of Computer Methods in Applied Mechanics and Engineering
  • Journal of Probabilistic Engineering Mechanics
  • Journal of Structural Health Monitoring
  • Journal of Computational Physics
  • International Journal for Numerical Methods in Engineering
  • Journal of Artificial Intelligence
  • Journal of Computational Methods in Structural Engineering
  • Journal of Pressure Vessel Technology
  • Energy Exploration & Exploitation
  • Journal of Engineering Mechanics
  • Mechanical Systems and Signal Processing
  • Journal of Computational Design and Engineering
  • Soil Dynamics and Earthquake Engineering
  • Advances in Engineering Software
  • International Journal of Structural Stability and Dynamics
  • Archive of Applied Mechanics

Professional Memberships

:pushpin: SIAM - Society for Industrial and Applied Mathematics, member of the UQ activity group – (Since 2022)
:pushpin: ASCE/EMI - American Society of Civil Engineers, member of the Probabilistic Methods Committee (PCM) – (Since 2022)
:pushpin: ASCE/EMI - American Society of Civil Engineers, member of the Machine Learning in Mechanics Committee – (Since 2023)
:pushpin: UNCECOMP - Conference on Uncertainty Quantification in Computational Sciences and Engineering, member of the Sicientific commitee – (Since 2019)
:pushpin: TEE - Technical Chember of Greece – (Since 2006)
:pushpin: GRACM - Greek Association of computational mechanics – (Since 2015)
:pushpin: Licenced Civil Engineer, Greece – (Since 2005)

University / Department Service (JHU)

:pushpin: Assistant Coach for the man’s Water Polo team – (Since 2016).
:pushpin: Judge for the Student Paper Competition, 8th Annual Johns Hopkins Postdoctoral Conference – (April 2022).

Activities in the Profession

:pushpin: Organized Conference Sessions

  • UNCECOMP 2023, Learning from small data: Data-driven methods and machine learning for uncertainty quantification in engineering applications.
  • UNCECOMP 2021, Data-driven Uncertainty Quantification and Data Assimilation using manifold learning and Sparse and Low-rank Representations.
  • WCCM 2020, Physics-based data-driven modeling and uncertainty quantification in computational mechanics.
  • UNCECOMP 2019, Surrogate and reduced-order modeling for stochastic simulation of physical systems.

:pushpin: Organized Workshops

  • MSEE Short Course: Uncertainty Quantification in Physics-Based Modeling Using Python – (June 2021, 2022). Offered for the Materials Science in Extreme Environments University Research Alliance (MSEE URA)

:pushpin: Other

  • Judge, Student Paper Competition, Engineering Mechanics Conference (PMC) – (June 2022)