Dr. Manoj kumar Yadav is an Associate Professor at the Department of Mathematics, Ecole Centrale School of Engineering, Mahindra University. He obtained his PhD from the Department of Mathematics, IIT Madras followed by postdoctoral positions at IISc Bangalore and Czech Technical University in Prague and a visiting position at the Czech Academy of Sciences. His expertise, experience and research interests span across several domains of Applied Mathematics such as Asymptotic analysis and computation of nonlinear partial differential equations describing evolution processes. Homogenization of PDE models describing composite material properties and fluid flows in heterogeneous media. Stochastic modeling and simulation in Mathematical Finance. Data driven modeling and analysis of real world problems. He has published research papers in peer reviewed international journals along with contributing in various talks in India and abroad.

• Ph.D. Mathematics, IIT Madras, Chennai

• M.Sc. Mathematics, Kalyani University, WB

• B.Sc. (H) in Mathematics, Kalyani University, WB

Peer Reviewed Journals

• Sumit Mishra, Chirala Satyanarayana, Manoj Kumar Yadav, Fourth order RBF-HFD method for elliptic PDE problems with optimal shape parameter selection : Sixth order convergence and improved accuracy, Engineering Analysis with Boundary Elements, 180, 106489, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0955799725003765
• Sreedhar, Manoj Kumar Yadav, Chirala Satyanarayana, RBF based backward differentiation methods for stiff differential equations, Engineering Analysis with Boundary Elements, 176, 106215, 2025. https://www.sciencedirect.com/science/article/abs/pii/S0955799725001031

• Chirala Satyanarayana, Manoj Kumar Yadav, Madhumita Nath, Multiquadric based RBF-HFD approximation formulas and convergence properties, Engineering Analysis with Boundary Elements, 160, 234–257, 2024. https://www.sciencedirect.com/science/article/abs/pii/S0955799723005994

• Manoj K. Yadav, Initial boundary value problems for some damped nonlinear conservation laws, Electronic J. Qualitative Theory of Differential Equation, No. 86, 1-11, 2015.
• Michal Benes, Ales Nekvinda, Manoj K. Yadav, Multi-time step domain decomposition method with non-matching grids for parabolic problems, Appl. Math. Comp. 267, 571-582, 2015.

• Manoj K. Yadav, Solutions of a system of forced Burgers equation in terms of generalized Laguerre polynomials, Acta Math. Sci. Ser. B, 34(5), 1461-1472, 2014.

• Manoj K. Yadav, Solutions of a system of forced Burgers equation, Appl. Math. Comp. 225, 151-157, 2013.

• Ch. Srinivasa Rao, Manoj K. Yadav, Large time behaviour of solutions of the inviscid non-planar Burgers equation, J. Engrg. Math. 69, 345-357, 2011.

• Ch. Srinivasa Rao, Manoj K. Yadav, Solutions of a nonhomogeneous Burgers equation, Stud. Appl. Math. 124 (4), 411-422, 2010.
• Ch. Srinivasa Rao, Manoj K. Yadav, Solution of an initial boundary value problem for non-planar Burgers equation using Hermite interpolants, Int. J. Nonlinear Sci., 9 (2), 159-164, 2010.
• Ch. Srinivasa Rao, Manoj K. Yadav, Large time asymptotics for solutions of a nonhomogeneous Burgers equation, Appl. Math. Mech., 31 (9), 1189-1196, 2010.
• Ch. Srinivasa Rao, Manoj K. Yadav, On the solution of a nonhomogeneous Burgers equation, Int. J. Nonlinear Sci., 10 (2), 141-145, 2010.

Conference Proceedings

• Manoj K. Yadav, Large time behaviour of solutions of an inviscid generalized Burgers equation with linear damping. Proceedings of ICIAM 2011, Vancouver, Canada.

• P. L. Sachdev and Manoj K. Yadav, Nonplanar Burgers equation – An overveiw. Proceedings of the International Symposium on Recent Advances in Fluid Mechanics, Bangalore University, 2004.

• Assistant Professor, Mahindra Ecole Centrale

• Researcher, Czech Technical University, Prague

• Ad hoc Faculty at National Institute of Technology, Warangal

• Assistant Professor at Jaypee University of Information Technology, Solan

• Post Doctoral Researcher, IISc Bangalore

Areas of Expertise: Analysis of evolutionary PDEs. Homogenization of PDE models describing composite material properties and fluid flows in heterogeneous media. Mathematical theory of compressible Navier-Stokes flows. Stochastic modeling and computation of problems in Mathematical Finance. Data driven modeling and analysis of real world problems.

Current Research Interests:

• PDE and Monte Carlo simulations based numerical techniques for option pricing problems in finance.
• Analysis and application of various Reinforcement Learning algorithms in optimal stopping problems in finance. Search for optimal early exercise policy in American option pricing.
• Mathematical and data driven modeling of various intervention strategies impact on epidemic evolution and control.