Course
Difficulty: Beginner
ENE-4302A - Numerical Methods for Energy, Thermal, and Fluid Engineering
Prerequisites:
Ordinary Differential Equations
Partial Differential Equations
Professional Summary
My research focuses on the development of advanced computational fluid dynamics algorithms for the large-scale numerical modeling of multi-scale, multi-physics, and multi-phase flows. I combine sharp-interface methods with high-performance computing (HPC) to accurately simulate heat, mass, and momentum transfers in complex flow configurations relevant to process engineering and energy conversion systems at the micro-scale.
Education
Ph.D. in Mechanical Engineering
2009-09-01
2012-06-30
Stanford University
Master of Science in Mechanical Engineering
2007-09-01
2009-06-30
Stanford University
Diplôme d'Ingénieur (Engineering Diploma)
2005-09-01
2007-06-30
École Centrale Paris
Interests
Computational Fluid Dynamics
Multiphase Flow
Scientific Computing
Numerical Analysis
📚 My Research
Use this area to speak to your mission. I’m a research scientist in the Moonshot team at DeepMind. I blog about machine learning, deep learning, and moonshots.
I apply a range of qualitative and quantitative methods to comprehensively investigate the role of science and technology in the economy.
Please reach out to collaborate 😃
Recent Publications
(2025).
A levelset-based cut-cell method for interfacial flows: part 1—{Navier}–{Stokes} equations and {Rayleigh}–{Bénard} instability with melting boundary.
Acta Mechanica.
(2025).
A levelset-based cut-cell method for interfacial flows: part 2—free-surface flows and dynamic contact angle treatment.
Acta Mechanica.
(2024).
Uncertainty quantification and sensitivity analysis of an unsteady axisymmetric reacting solid particle.
Combustion and Flame.
(2023).
Adjoint-based optimization of two-dimensional {Stefan} problems.
Journal of Computational Physics.
Courses