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Department of Computer Science and Information Systems: Recent submissions

Now showing items 301-320 of 954

A TTL-based Approach for Data Aggregation in Geo-distributed Streaming Analytics

Kumar, Dhruv (ACM Digital Library, 2019-06)

Streaming analytics require real-time aggregation and processing of geographically distributed data streams continuously over time. The typical analytics infrastructure for processing such streams follow a hub-and-spoke ...
AggNet: Cost-Aware Aggregation Networks for Geo-distributed Streaming Analytics

Kumar, Dhruv (IEEE, 2021)

Large-scale real-time analytics services continuously collect and analyze data from end-user applications and devices distributed around the globe. Such analytics requires data to be transferred over the wide-area network ...
HACCS: Heterogeneity-Aware Clustered Client Selection for Accelerated Federated Learning

Kumar, Dhruv (IEEE, 2022)

Federated Learning is a machine learning paradigm where a global model is trained in-situ across a large number of distributed edge devices. While this technique avoids the cost of transferring data to a central location ...
AggFirstJoin: Optimizing Geo-Distributed Joins using Aggregation-Based Transformations

Kumar, Dhruv (IEEE, 2023-07)

Today, data is generated in a geographically distributed manner in a wide variety of domains such as social networks, e-commerce, search engines, online advertisements, audio and video streaming, energy, smart cities, IoT ...
With Great Power Comes Great Responsibility!": Student and Instructor Perspectives on the influence of LLMs on Undergraduate Engineering Education

Kumar, Dhruv (2023-09)

The rise in popularity of Large Language Models (LLMs) has prompted discussions in academic circles, with students exploring LLM-based tools for coursework inquiries and instructors exploring them for teaching and research. ...
“It's not like Jarvis, but it's pretty close!” - Examining ChatGPT's Usage among Undergraduate Students in Computer Science

Kumar, Dhruv (ACM Digital Library, 2024-01)

Large language models (LLMs) such as ChatGPT and Google Bard have garnered significant attention in the academic community. Previous research has evaluated these LLMs for various applications such as generating programming ...
From Cash to Cashless: UPI’s Impact on Spending Behavior among Indian Users

Kumar, Dhruv (2024-01)

The emergence of digital payment systems has transformed how individuals conduct financial transactions, offering convenience, security, and efficiency. One groundbreaking innovation making waves in the Indian financial ...
AI as a Medical Ally: Evaluating ChatGPT's Usage and Impact in Indian Healthcare

Kumar, Dhruv (2024-01)

This study investigates the integration and impact of Large Language Models (LLMs), like ChatGPT, in India's healthcare sector. Our research employs a dual approach, engaging both general users and medical professionals ...
Comuniqa : Exploring Large Language Models for improving speaking skills

Kumar, Dhruv (2024-05)

In this paper, we investigate the potential of Large Language Models (LLMs) to improve English speaking skills. This is particularly relevant in countries like India, where English is crucial for academic, professional, ...
ChatGPT in the Classroom: An Analysis of Its Strengths and Weaknesses for Solving Undergraduate Computer Science Questions

Kumar, Dhruv (ACM Digital Library, 2024)

This research paper aims to analyze the strengths and weaknesses associated with the utilization of ChatGPT as an educational tool in the context of undergraduate computer science education. ChatGPT's usage in tasks such ...
Can ChatGPT Play the Role of a Teaching Assistant in an Introductory Programming Course?

Kumar, Dhruv (2024-01)

The emergence of Large language models (LLMs) is expected to have a major impact on education. This paper explores the potential of using ChatGPT, an LLM, as a virtual Teaching Assistant (TA) in an Introductory Programming ...
Unit Test Generation using Generative AI : A Comparative Performance Analysis of Autogeneration Tools

Kumar, Dhruv (2023-12)

Generating unit tests is a crucial task in software development, demanding substantial time and effort from programmers. The advent of Large Language Models (LLMs) introduces a novel avenue for unit test script generation. ...
OpineBot: Class Feedback Reimagined Using a Conversational LLM

Kumar, Dhruv (2024-01)

Conventional class feedback systems often fall short, relying on static, unengaging surveys offering little incentive for student participation. To address this, we present OpineBot, a novel system employing large language ...
Which LLM should I use?": Evaluating LLMs for tasks performed by Undergraduate Computer Science Students

Kumar, Dhruv (2024-04)

This study evaluates the effectiveness of various large language models (LLMs) in performing tasks common among undergraduate computer science students. Although a number of research studies in the computing education ...
A Comparative Analysis of Large Language Models for Code Documentation Generation

Kumar, Dhruv (2023-12)

This paper presents a comprehensive comparative analysis of Large Language Models (LLMs) for generation of code documentation. Code documentation is an essential part of the software writing process. The paper evaluates ...
Analyzing LLM Usage in an Advanced Computing Class in India

Kumar, Dhruv (2024-04)

This study examines the use of large language models (LLMs) by undergraduate and graduate students for programming assignments in advanced computing classes. Unlike existing research, which primarily focuses on introductory ...
TAMIGO: Empowering Teaching Assistants using LLM-assisted viva and code assessment in an Advanced Computing Class

Kumar, Dhruv (2024-07)

Large Language Models (LLMs) have significantly transformed the educational landscape, offering new tools for students, instructors, and teaching assistants. This paper investigates the application of LLMs in assisting ...
aFlux: Graphical flow-based data analytics

Mahapatra, Tanmaya (Elsevier, 2019-11)

aFlux is a graphical flow-based programming tool designed to support the modelling of data analytics applications. It supports high-level programming of Big Data applications with early-stage flow validation and automatic ...
Enabling Agile Clinical and Translational Data Warehousing: Platform Development and Evaluation

Mahapatra, Tanmaya (Helmut Spengler, 2020-07)

Modern data-driven medical research provides new insights into the development and course of diseases and enables novel methods of clinical decision support. Clinical and translational data warehouses, such as Informatics ...
Graphical Flow-based Spark Programming

Mahapatra, Tanmaya (Springer, 2020-01)

Increased sensing data in the context of the Internet of Things (IoT) necessitates data analytics. It is challenging to write applications for Big Data systems due to complex, highly parallel software frameworks and systems. ...

Now showing items 301-320 of 954

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