Alp Dener received his B.S. in mechanical engineering from the University of Maryland, Baltimore County in 2012 and his Ph.D. in aeronautical engineering from Rensselaer Polytechnic Institute in 2017. For his doctoral research, he developed a matrix-free multidisciplinary design optimization algorithm tailored for large-scale engineering problems, demonstrated its efficacy on test problems drawn from the aerospace industry.
Alp’s work at Argonne builds on his past efforts by developing and implementing gradient-based PDE-constrained optimization algorithms in TAO (Toolkit for Advanced Optimization), with particular emphasis on the efficient treatment of nonlinear state-based constraints. In this context, he is currently pursuing applications in the physics-constrained training of neural networks and modeling the movement of the Earth’s mantle.
- Numerical Optimization
- Simulation-based Design
- High Performance Computing
- Open Source Software