Machine learning systems often experience performance degradation in real-world scenarios due to subpopulation shift defined as mismatches in the distribution of classes or attributes within datasets. This thesis investigates generalization failures arising from class imbalance, long-tailed distributions, and&#...

The principal objective of this thesis is, in a nutshell, to provide robust estimators of multivariate location and scale which have reasonable to high model efficiency but avoid high computational complexity so as to be practically useful in real problems. We utilize the minimum&#...

Generative modeling focuses on the task of producing new data samples that closely resemble those drawn from an original, unknown distribution. Despite being well-known in statistical estimation theory, the approach has gained substantial traction in recent years, driven by groundbre...

The thesis, consisting of nine chapters, explores the methodology of building testable brain computational models using Deep Neural Networks (DNN), which are trained by psychophysics data. Psychophysics is the quantitative study of perception of physical stimuli. In psychophysics experiments, one ...

In image processing literature, image registration is the process of spatially matching two or more images of the same scene or object obtained at various times, from different perspectives, or by separate sensors in order to simplify comparison, fusion, or analysis. Its purpose&#...

This thesis investigates computational models and methodologies for restoring images degraded by challenging environmental conditions such as haze and underwater environments. It further explores the analysis and estimation of particulate matter (PM) concentration from both day and night scenes under&...

This dissertation aims to study conflicts and protests using a game-theoretic setup. It contains six chapters. Chapter 1 is the introduction. Chapter 2 gives a brief review of the related literature. Chapter 3 explores conflicts in the presence of revenge and third par...

Reconfigurable intelligent surfaces (RIS) can dynamically reshape the propagation environment to enhance signal strength, spectral efficiency and reliability in 5th generation (5G) cellular as well as device to device (D2D) communications. However, to reap such benefits, a range of practical and&...

Sample size determination is an important as well as delicate problem in clinical trials. Often, prior information available before the beginning of the trial is used to estimate the sample size. Hence, it is of importance to quantify the prior information available in terms o...

Micro Ribonucleic Acids (miRNAs) are short length (∼24) non-coding RNAs and are considered as key biomarkers in cancer diagnosis and treatment. They play a vital role in classifying cancer patients from normal ones and drug resistant patients from control ones. The control p...

Mutually Unbiased Bases (MUBs) are an important concept in quantum information theory. Two orthonormal bases in a $d$-dimensional complex Hilbert space $\mathbb{C}^d$ are said to be mutually unbiased if the absolute value of the inner product between any pair of vectors, one from&#...

Boolean functions are fundamental to computation and presently play a crucial role in quantum information processing. This thesis presents two facets of Boolean functions in the context of quantum computing: (I) extending and applying the theoretical framework of Forrelation to cryptographic ...

This report presents the work I did during my internship at Hongkong and Shanghai Banking Corporation (HSBC), Kolkata. As a financial institution, the strength of the bank is fundamentally rooted in the behavior and reliability of its customers. Understanding this behavior is not o...

A multipacking in an undirected graph G = (V,E) is a set M ⊆ V such that for every vertex v ∈ V and for every integer r ≥ 1, the ball of radius r around v contains at most r vertices of M, that is, there are at most r vertices�...

Graph Neural Networks (GNNs) have demonstrated impressive performance across a range of graph-based learning tasks. However, their application to domains with sensitive relational data raises serious privacy concerns, as the graph structure itself may leak confidential information. This t...

The thesis presented here analyses the security of certain selected symmetric key ciphers - The ciphers analyzed are the 2 and 3-round Confusion-Diffusion Network, the 3-round Cascade Cipher with two independent keys, and the Feistel Construction with 7 and 8 rounds. Substi...

As the number of IoT (Internet of Things) devices continues to grow, ensuring secure communication among them has become increasingly important. Traditional pairing schemes rely on centralized architectures, which are vulnerable to temporary or permanent failures due to operational m...

Digital signatures, as a strong cryptographic primitive, ensure the authenticity and integrity of signed messages. On one hand, no one can forge a verifiable signature without knowing the secret key, on the other hand, any correctly formed signature is always verifiable under...

The demand for symmetric-key cryptography implemented in hardware is growing due to the increasing need for faster, more efficient, and secure encryption in small devices. However, implementing block ciphers in hardware that are side-channel secure remains a challenging goal. This&#x...