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Students



Ph.D. Students

  1. Ritu Kumari (In progress).

  2. Yash Vats (PMRF fellow) (jointly with Prof. Dietmar Oelz, University of Queensland, Australia), (in progress)

  3. Shweta Kumari (In progress).

  4. Abhishek Singh (Numerical methods and data-driven approach for stochastic integro-differential/differential equations containing non-local operators), 2023, Currently postdoc in Greifswald University, Germany.

  5. Nitin (Wavelet collocation methods for fractional optimal control problems), 2023.

  6. Vaibhav Mehandiratta(Analysis and discretization for optimal control problems goverend by fractional differential equations on metric graphs), 2022 (Distinction in Doctoral reserach), Currently postdoc in KAUST, Saudi Arabia.

  7. Ankita Shukla (Compact filter regularization and adaptive spectral graph wavelet method with regularization for PDEs on graph), 2020.

  8. kuldip Singh Patel (Compact Finite Difference Methods with error analysus for problems arsing in option pricing), 2018, Currently faculty at IIT Patna, India.

  9. kavita Goyal (Fast adaptive meshfree wavelet based methods for numerical solutions of partial differential equations and integral equations), 2014, Currently faculty at Thapar Institute of Engineering & Technology, Patiala, India.

  10. Ratikanta Behera (Multilevel adaptive wavelet methods for solution of PDEs), 2013, Currently faculty at IISc. Bangalore, India.

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M.Tech. Project Students

  1. Rohan Mahala (Beyond Traditional Activations: Harnessing Muntz-Legendre and other Orthogonal Polynomial Functions in PINNs), 2024.

  2. Prateek Singh (Comparative analysis of PINNs and ELMs for efficient and accurate solutions of Partial Differential Equations), 2023.

  3. Anshul Tak (An adaptive meshfree spectral graph wavelet method fo partial differential equations containing non-local Laplacian), 2023.

  4. Aman Kumar Sahu (Non-local physics informed neural networks for forward and inverse problems containing fractional integro-differential equations), 2022.

  5. Akshay Royal (Deep learning architectures and data augementation techniques for brain tumor segmentation), (jointly with Prof. Anup), 2022.

  6. Ashray Aman (Histopathological Image Analysis for Diagnosis for classification and grading of Breast Cancer using Deep Learning), (jointly with Prof. Anup), 2021.

  7. Anish Kumar (Learning fractional Differential equations via data discovery), 2021.

  8. Samarth Gulyani (Learning Parameters of a System of Variable Order Fractional Differential Equations), 2020.

  9. Ratnesh Kumar (Optimization of number of flip angles required for T1 mapping), (jointly with Prof. Anup), 2018.

  10. Amar Kumar (Finite difference schemes for Heston Model), 2016 .

  11. Preeti Bhonsle (Pricing American Options using Monte Carlo Simulation), 2014.

  12. Saurav Gupta (Fourier Transform in option pricing), 2014.

  13. Shubham Kumar (Second generation wavelet methods), 2013.

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  14. Gajendra Kumar Twinwal (Solution of Mathematical Model arising from Diabetes), 2013.

  15. Atendra Kumar (Wavelets on Geodesic grids), 2013.

  16. Rahul Bhutani (Optimization of portfolio tail measures), (jointly with prof. Nomesh Bolia), 2012 .

B.Tech Project Students

  1. Adarsh Roy and Abhinna Agarwal (Partial and Fractional Difference Equations for Image Denoising), 2024.

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  2. Shivam Madan (Deep Learning Based Quantitative Image Analysis), (jointly with Prof. Anup), 2024.

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M.Sc. Project Students

  1. Kunkika and Rashmi Pandey (Error Approximation of Munz Legendre Polynomial), 2023-2024 (part1 and part2).

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  2. Rupendra Yadav and Mayank Yadav (Fractional calculus), 2022.

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  3. Biswa Prakash Prusty and Nirakara Bag (Numerical methods for fractional calculus), 2021.

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  4. Rakesh Prasad and Manish Kumar (Numerical methods), 2020.

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  5. Pulkit Mandowara and Komal Lawat (Numerical methods for stocastic differential integro equations), 2019.

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  6. Ankit Kumar and Akash Arora (Finite difference methods of partial differential equations), 2016.

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  7. Chandan Kumar and Abhishek Yadav (Finite difference methods), 2016.

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  8. Saurabh Shukla and Shubha Agnihotri (Fourier methods in option pricing), 2014.

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  9. Guru Prasad Singh and Vaibhav Mishra (PDEs in image processing), 2014.

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  10. Debasis Das and Sabir Hasan (Wavelets and its applications), 2013.

  11. Abhinav and Akhilesh Pandey (Numerical methods and its applications), 2013 .

  12. M. Srinivas and K. Prakash (The singular value decomposition), 2012 .

  13. Navjot Parmar and Kuldip Singh Patel (Comparison between numerical and analytical solution of Black-Scholes PDE), 2012 .

  14. Kr. Gaurav and Amiya Biswas (PDE Model for Imatinib-treated chronic Myelogenous Leukemia), 2011 .

  15. Rahul Kumar and Nutan Patel (Comparison between different numerical methods for discretization of PDEs), 2010.



Mini Project Students

  1. Ashray Aman(Histopathological Image Analysis for Diagnosis), (jointly with Prof. Anup), 2020.

    2.

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