Projects

Superresolution and Satellite Track Removal in Astronomical Images
under Prof. Sumohanna Channappayya
Jan-May’23

• Developed a novel method for generating high-resolution astronomical images from low-resolution, blurred observations while effectively eliminating satellite trails using Hough Transform technique.
• Conducted a comparative analysis between deep learning-based super-resolution reconstruction techniques, specifically the CNN process, and advanced wavelet-based methods.
• Evaluated the performance of our approach using metrics such as PSNR, MSE, and SSIM, and provided a benchmark for future research in this field

Residual Self-Interference Cancellation and Optimal Control with RIS for Full-Duplex Communication
under Prof. Zafar Ali Khan
during Jan-May’23

• Implemented and analyzed Full-Duplex Communication Systems using Python to improve its reliability.
• Conducted simulations to evaluate the effectiveness of the traditional method, superimposed method, and ’self-proposed’ method, demonstrating their potential to improve the performance of full-duplex communication systems.
• Proposed practical solutions for enhancing wireless network performance, focusing on capacity and reliability improvements, addressing challenges such as self-interference and transmit power consumption.

Correlation Coefficients
under Prof. Shantanu Desai
during Jan-May’22

• Conducted a statistical analysis of correlation coefficients, including Pearson’s sample correlation coefficient, Spearman rank correlation coefficient, and Kendall Tau.
• Analyzed the characteristics of each coefficient and their applications in exploratory data analysis, structural modeling, and data engineering.
• Demonstrated proficiency in data analysis and statistical modeling techniques, including hypothesis testing and regression analysis.

Cosmic Lithium Problem: Non-Gaussian Error Distribution of ⁷₃Li Abundance Measurements

• Undertook an independent study to enhance personal understanding of the Cosmic Lithium Problem, drawing inspiration from the research findings of Crandall, S., Houston, S., & Ratra, B. (2014).
• Conducted an analysis of the error distribution in ⁷₃Li abundance measurements sourced from the research conducted by Spite et al, with the aim of assessing its statistical significance.
• Employed various probability distribution functions to characterize the error distribution, contributing to a deeper comprehension of its statistical properties.
• Concluded that, while the non-Gaussian nature of the data was of interest, it did not offer a comprehensive solution to the Lithium Problem.

Electrical Projects:

• Spearheaded a project focused on Digital Signal Processing, encompassing the design and implementation of innovative solutions to real-world electrical engineering challenges.
• Demonstrated adeptness in signal conditioning techniques by conceiving and designing a Schmitt trigger circuit, leveraging Arduino and KiCAD. Employed LtSpice simulations to verify the effectiveness of the signal conditioning in eliminating noise from digital circuit signals, ultimately enhancing signal quality and reliability.