Welcome to my Portfolio
You can look at my blogs and work on this website, mostly in the areas of Quantum materials, semiconductor devices, quantum machine learning and algorithms.
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Research Highlights
An overview of key projects and contributions in quantum materials and applications.
Implemented Quantum Convolutional Neural Networks (QCNNs) to process and classify images efficiently. Leveraged platforms like Google Colab, PennyLane, and Qiskit to demonstrate the potential of quantum machine learning in complex data analysis tasks.
Quantum Machine Learning for Image Classification
Quantum Computing
Investigated the effects of amplitude damping and generalized amplitude damping channels on Bell states using Mathematica. This research provided insights into noise impact on coherence and entanglement in quantum systems.
Effect of Noise on Quantum States
Quantum Information
Designed wireless sensor networks integrated with nanomaterials to monitor and mitigate indoor air pollution. This project explored innovative solutions for improving indoor air quality through advanced sensing technologies.
Pollution Mitigation Using Nanomaterials
Environmental Applications
Developed protocols for the large-area synthesis of 2D Transition Metal Dichalcogenides (TMDCs) using advanced techniques like Chemical Vapor Deposition (CVD) and Low-Pressure CVD (LPCVD). Characterized materials using SEM, Raman Spectroscopy, and XRD to study their properties for sensing and optoelectronic applications.
Synthesis and Characterization of 2D TMDCs
Quantum Materials
Implemented Quantum Convolutional Neural Networks (QCNNs) to process and classify images efficiently. Leveraged platforms like Google Colab, PennyLane, and Qiskit to demonstrate the potential of quantum machine learning in complex data analysis tasks.
Quantum Machine Learning for Image Classification
Quantum Computing
Investigated the effects of amplitude damping and generalized amplitude damping channels on Bell states using Mathematica. This research provided insights into noise impact on coherence and entanglement in quantum systems.
Effect of Noise on Quantum States
Quantum Information
Designed wireless sensor networks integrated with nanomaterials to monitor and mitigate indoor air pollution. This project explored innovative solutions for improving indoor air quality through advanced sensing technologies.
Pollution Mitigation Using Nanomaterials
Environmental Applications
Developed protocols for the large-area synthesis of 2D Transition Metal Dichalcogenides (TMDCs) using advanced techniques like Chemical Vapor Deposition (CVD) and Low-Pressure CVD (LPCVD). Characterized materials using SEM, Raman Spectroscopy, and XRD to study their properties for sensing and optoelectronic applications.
Synthesis and Characterization of 2D TMDCs
Quantum Materials
Implemented Quantum Convolutional Neural Networks (QCNNs) to process and classify images efficiently. Leveraged platforms like Google Colab, PennyLane, and Qiskit to demonstrate the potential of quantum machine learning in complex data analysis tasks.
Quantum Machine Learning for Image Classification
Quantum Computing
Investigated the effects of amplitude damping and generalized amplitude damping channels on Bell states using Mathematica. This research provided insights into noise impact on coherence and entanglement in quantum systems.
Effect of Noise on Quantum States
Quantum Information