Onkar Jadhav

Onkar Jadhav

Postdoctoral Researcher

University of Luxembourg

Biography

I am a postdoctoral researcher at the University of Luxembourg. Currently, I am working on developing machine learning and reduced-order modeling frameworks for wind engineering and CFD problems.

I was an MSCA fellow at the institute of mathematics at the Technical University of Berlin, where I received my Ph.D. in applied mathematics. My thesis was a cross-disciplinary work, where I developed complexity reduction methods using machine learning algorithms for financial risk analysis.

I have an interdisciplinary background, a bachelor’s in mechanical engineering, a master’s in computational science focusing on computational methods and high-performance computing, and I am currently working in the field of numerical mathematics. Additionally, I am highly skilled in Python and MATLAB.

My primary research interest is in applied mathematics, and specifically, I find problems in differential equations, numerical analysis, reduced modeling, stochastic analysis, and machine learning interesting.

Interests
  • Numerical Mathematics
  • Computational Mathematics
  • Machine learning
  • Model Order Reduction
  • Computational Fluid Dynamics
  • Computational Finance
  • Stochastic Analysis
  • Optimization
  • High performance computing
Education
  • PhD in Mathematics, 2022

    Technical University of Berlin

  • MSc in Computational Science and Engineering, 2018

    University of Rostock

  • BEng in Mechanical Engineering, 2015

    University of Pune

Skills

Matlab
Matlab

Advanced

Python

Advanced

Ansys
Ansys Mechanical

Advanced

c
C++

Intermediate

Latex
Latex

Advanced

Ansys
Ansys Fluent

Intermediate

Experience

 
 
 
 
 
Postdoctoral Researcher
University of Luxembourg
Jan 2022 – Present Esch-sur-Alzette, Luxembourg

Responsibilities:

  • Reduced order modeling and machine learning for computational fluid dynamics (CFD).
  • Testing developed tools for wind flow over urban location based on the experimental and CFD datasets.
  • Surrogate modeling optimization for faster computations.
  • Wind energy harvesting and urban comfort studies.
 
 
 
 
 
Researcher
MathConsult GmbH
Nov 2018 – Apr 2020 Linz, Austria

Responsibilities:

  • Parametric model order reduction for financial risk analysis.
  • Analysis of stochastic differential equations (SDE) in finance.
  • Numerical methods for nonlinear partial differential equations (PDEs).
  • Implementation of CFD techniques in finance.
  • Artificial neural network for faster computations.
 
 
 
 
 
Research Assistant
University of Rostock, Collaborative Research Center ELAINE
Oct 2017 – Sep 2018 Rostock, Germany

Responsibilities:

  • Designed thermoelectric generators (TEGs) for energy autonomous implants for medical applications.
  • Computational methods for nonlinear PDEs in fluid dynamics and thermodynamics.
  • Thermal and electrothermal simulations of TEG.
  • Implemented nonlinear model order reduction for faster computation.
 
 
 
 
 
Teaching Assistant
University of Rostock
Oct 2017 – Sep 2018 Rostock, Germany

Responsibilities:

  • Tutor two courses as a tutor involving numerical methods for PDEs, linear algebra, and compact modeling (model order reduction).
  • Supervised and guided students on their software projects.
  • Designed and conducted exams.

Contact