Department of Computational and Data Sciences (CDS): Recent submissions
Now showing items 1-20 of 112
-
Development of Novel Deep Learning Models for Quantitative Medical Image Analysis
Medical imaging provides a non-invasive way to visualize tissues and diseases, enabling both qualitative and quantitative assessments that are needed in diagnosing and monitoring a wide range of conditions. Modalities ... -
Scalable Distributed Frameworks for Temporal Analysis and Partitioning of Streaming Graphs
The analysis of graph-structured data has become increasingly important as networks in various domains, including science, engineering, and business, grow in size, complexity, and dynamism. While static graph analysis ... -
Dynamic hybrid partitioned non partitioned queue configurations based on workloads in supercomputer systems
Supercomputers rely on batch queues to manage parallel job execution, with commercial schedulers offering configurable parameters that influence job routing, execution order, and queue visitation. However, selecting an ... -
Efficient quantum dynamics simulations for periodic potentials
Quantum algorithms are designed to efficiently solve many problems that are thought to be difficult classically. A specific case is the efficient simulation of time evolution of quantum systems. This work provides a ... -
Some Algebraic Aspects Of Graph Similarity Algorithms
We proposed singular values-based sensitivity analysis and self-similarity studies to compare graph-isomorphism algorithms. SimRank method is found to be an application of power method and is not sensitive to noise in any ... -
Efficient parallel algorithms to compute A sub-complex of the weighted delaunay triangulation for molecular data
In the field of bio-molecules, it is utmost important to study the behaviour of a molecule while interacting with another. This interaction decides the functionality of the molecule. It is widely accepted fact that the ... -
Systems Optimizations for DNN Training and Inference on Accelerated Edge Devices
Deep Neural Networks (DNNs) have had a significant impact on a wide variety of domains, such as Autonomous Vehicles, Smart Cities, and Healthcare, through low-latency inferencing on edge computing devices close to the data ... -
Investigation of the Indian Summer Monsoon Rainfall Using Statistical and Machine Learning Techniques
The Indian Summer Monsoon is an important atmospheric phenomenon, marked by a characteristic seasonal wind reversal pattern, delivering 70 to 90% of the annual rainfall to the Indian subcontinent. Monsoon rain profoundly ... -
An error correction algorithm for long-read sequencing
Long-read sequencing technologies have transformed genomics by generating longer and suffi- ciently accurate DNA sequences, offering advantages in analysing highly repetitive and complex regions of a genome. A long-read ... -
Quantifying the past and future variability in the Bay of Bengal using statistical and deep learning methods
The Bay of Bengal, the world's largest bay, along with the Andaman Sea, a peripheral sea situated in the southeastern part of the bay, is crucial to the economic and maritime security of India. Understanding the dynamics ... -
Unsupervised Test-time Adaptation for Patient-Specific Deep Learning Models in Medical Imaging
Deep learning (DL) models have achieved state-of-the-art results in multiple medical imaging applications, resulting in the widespread adoption of artificial intelligence (AI) models for radiological workflows. Despite ... -
Algorithmic Approaches to Pangenome Graph Problems
The human reference genome serves as a foundational baseline for comparing newly sequenced human genomes. With the growing availability of high-quality human genome assemblies, there is now an opportunity to modernize the ... -
Improving hp-Variational Physics-Informed Neural Networks: A Tensor-driven Framework for Complex Geometries, and Singularly Perturbed and Fluid Flow Problems
Scientific machine learning (SciML) combines traditional computational science and physical modeling with data-driven deep learning techniques to solve complex problems. It generally involves incorporating physical ... -
Semi-analytical solution for eigenvalue problems of lattice models with boundary conditions
Closed-form relations for limiting eigenvalues of an infinite k-periodic spatial lattice in any number of dimensions d, and its semi-analytical extensions for any given size n of the lattice with free-free boundary ... -
Lesion Synthesis using Physics-Based Noise Models for Low-Data Medical Imaging Regime applications
Lesion segmentation and their progression prediction in medical imaging relies critically on the availability of manually annotated, heterogeneous large pathological datasets. Acquiring such diverse large datasets is also ... -
Learning from Limited and Imperfect Data
Deep Neural Networks have demonstrated orders of magnitude improvement in capabilities over the years after AlexNet won the ImageNet challenge in 2012. One of the major reasons for this success is the availability of ... -
Application Service Resilience In Cloud: An End-to-End Perspective
Embargo up to 10/1/2026 The idea of computing as a utility was realized with the emergence of the cloud computing paradigm. Cloud service providers offer a wide range of services that are delivered over the Internet to ... -
Designing Quality of Service aware Serverless Platforms
Serverless computing is a widely used Cloud computing service offering that provides users with managed runtimes to develop their business logic as functions. It supports eventdriven execution of functions and a powerful ... -
Learning Multiple Initial Conditions using Physics Informed Neural Networks
Physics-Informed Neural Networks (PINNs) and its variants have emerged as a tool for solving differential equations in the past few years. Although several variants of PINNs have been proposed, the majority of these ... -
Structural and functional studies on the hypothetical protein TTHA1873 from Thermus thermophilus
This thesis reports a detailed study on the structural and functional characterization of the hypothetical protein (TTHA1873) from Thermus thermophilus. In this study, both the structure and function of TTHA1873 were ...