Dr Nakka Shekhar

About

Research scientist focused on next-generation technologies, with particular interest in the intersection of quantum computing, artificial intelligence, and scientific computing. The goal of my research is to build scalable algorithms to solve computationally complex inverse problems in Earth observation and scientific computing. The integration of quantum algorithms, sparse optimization, and machine learning, I aim to build next-generation computational tools for scientific discovery. My long-term goal is to create an independent interdisciplinary research program on scientific imaging with quantum AI.

Employment

Employment history is unavailable.

Education

• SRM University, Andhra Pradesh Ph.D
  2024 - 2026
• Jawaharlal Nehru Technological University, Hyderabad M.Tech
  2013 - 2015
• Jawaharlal Nehru Technological University, Hyderabad B.Tech
  2009 - 2013

Projects & Funding

Projects & funding information is unavailable.

Publications (6)

• DEAE-INR: Dual Encoder Based Autoencoders With Implicit Neural Representations for Seismic Random Noise Attenuation
  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2026 DOI: 10.1109/JSTARS.2026.3683423
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• Evolutionary Intelligence-Based IRS Deployment and Power Allocation for Sum-Rate Enhancement in 6G Networks
  IEEE Access 2026 DOI: 10.1109/ACCESS.2026.3726167
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• Quantum-Accelerated Dictionary Learning Based on HHL and QSVT for Seismic Data Denoising
  IEEE Access 2026 DOI: 10.1109/ACCESS.2026.3672906
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• Seismic Denoising Based on Convolutional Dictionary Learning With ADMM
  IEEE Transactions on Geoscience and Remote Sensing 2026 DOI: 10.1109/TGRS.2025.3646696
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• Double Dictionary Learning for Seismic Random and Erratic Noise Attenuation
  IEEE Geoscience and Remote Sensing Letters 2025 DOI: 10.1109/LGRS.2025.3580580
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• Seismic Denoising Based on Dictionary Learning With Double Regularization for Random and Erratic Noise Attenuation
  IEEE Transactions on Geoscience and Remote Sensing 2025 DOI: 10.1109/TGRS.2025.3540208
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