Ruchi Sandilya, Ph.D.
Welcome to my website! I am an applied mathematician with background in control theory for complex dynamical systems. Presently, I am bringing these concepts together with machine learning to address the challenges associated with the diagnosis and treatment of major depressive disorder.
Peer-Reviewed Publications (in Reverse Chronological Order)
- Numerical stabilization of the Boussinesq system using boundary feedback control
Praveen Chandrashekar, Mythily Ramaswamy, Jean-Pierre Raymond, Ruchi Sandilya
Computers & Mathematics with Applications, 2021
Paper (PDF)
- Conservative discontinuous finite volume and mixed schemes for a new four-field formulation in poroelasticity
Sarvesh Kumar, Ricardo Oyarzúa, Ricardo Ruiz-Baier, Ruchi Sandilya
ESIAM: Mathematical Modelling and Numerical Analysis, 2019
Paper (PDF)
- Error bounds for discontinuous finite volume discretizations of Brinkman optimal control problems
Sarvesh Kumar, Ricardo Ruiz-Baier, Ruchi Sandilya
Journal of Scientific Computing, 2018
Paper (PDF)
- Mixed and discontinuous finite volume element schemes for the optimal control of immiscible flow in porous media
Sarvesh Kumar, Ricardo Ruiz-Baier, Ruchi Sandilya
Computers & Mathematics with Applications, 2018
Paper (URL)
- On discontinuous interpolated finite volume approximations for semilinear elliptic optimal control problems
Ruchi Sandilya, Sarvesh Kumar
Numerical Methods for Partial Differential Equations, 2017
Paper (PDF)
- Trajectory controllability of a semilinear parabolic system
Ruchi Sandilya, Raju K. George, Sarvesh Kumar
The Journal of Analysis, 2017
Paper (PDF)
- Discontinuous finite volume methods for the optimal control of Brinkman equations
Sarvesh Kumar, Ricardo Ruiz-Baier, Ruchi Sandilya
Finite Volume for Complex Applications, 2017
Paper (PDF)
- Convergence of discontinuous finite volume discretizations for a semilinear hyperbolic optimal control problem
Ruchi Sandilya, Sarvesh Kumar
International Journal of Numerical Analysis and Modeling, 2016
Paper (PDF)
- On discontinuous finite volume approximations for semilinear parabolic optimal control problems
Ruchi Sandilya, Sarvesh Kumar
International Journal of Numerical Analysis and Modeling, 2016
Paper (PDF)
- Convergence analysis of discontinuous finite volume methods for elliptic optimal control problem
Ruchi Sandilya, Sarvesh Kumar
International Journal of Computational Methods, 2016
Paper (URL)
- Discontinuous finite volume methods for parabolic optimal control problems
Ruchi Sandilya, Sarvesh Kumar
Mathematical Sciences International Research Journal, 2015
Paper (PDF)
- Discontinuous Galerkin finite volume element methods for elliptic optimal control problems
Ruchi Sandilya, Sarvesh Kumar
International Conference on Computational Methods (ICCM), 2014
Paper (PDF)
Invited talks
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Sep 2021: Mathematics Seminar, CUA, Washington, D.C.
July 2021: UNC Greensboro PDE Conference, North Carolina, USA
May 2020: The Computational and Applied Math Seminar, Oak Ridge National Laboratory, USA
Aug 2019: 6th International Conference on Continuous Optimization, Technical University Berlin, Germany
Jul 2019: 9th International Congress on Industrial and Applied Mathematics, University of Valencia, Spain
Nov 2018: Conference on Celebrating 75 years of Mathematics of Computation, ICERM, Brown University, USA
Jun 2017: Conference on Recent advances in PDEs: Theory, Computations and Applications, IIT Bombay, India
Dec 2016: International Conference on Recent Advances in Theoretical and Computational PDEs with Applications, Panjab University, India
Nov 2016: International Conference on Mathematical Analysis and its Applications, IIT Roorkee, India
Jun 2016: Conference on Mathematics of Finite Elements and Applications, Brunel University, London, UK
Dec 2015: International Conference on Current Trends in PDEs: Theory and Computations, South Asian University, India
Nov 2015: International Conference on Mathematics, University of Kerala, India. Received best presentation award
Summits
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Jan 2023: HPE and NVIDIA Data Science Summit, NYC, USA
Apr 2021: Safety and Security of Deep Learning, ICERM, Brown University, USA