1 citations · 1 across the 12 of their papers we have counts for
12 papers
BetXplain: An Explanation-Annotated Dataset for Detecting Manipulative Betting Advertisements on Social Media
MSVPJ Sathvik, Parmitha Vangapandu, Nishit Rane +3
The promotion of betting applications on social media platforms has increased significantly in recent years. Many of these advertisements use persuasive techniques that may mislead…
RSPC: A Benchmark for Modeling Stress and Psychiatric Conditions in Digitally Mediated Relationships using Psychiatrist Annotations
Parmitha Vangapandu, Sai Ganesh Mokkapati, Sathwik Narkedimilli +4
In NLP, mental health conditions are often modeled as isolated phenomena, without interpersonal context. We use Reddit posts about long-distance relationships to capture both menta…
From Design to Deorbit: A Solar-Electric Autonomous Module for Multi-Debris Remediation
Om Mishra, Jayesh Patil, Sathwik Narkedimilli +3
The escalating accumulation of orbital debris threatens the sustainability of space operations, necessitating active removal solutions that overcome the limitations of current fuel…
Explainable Galaxy Interaction Prediction with Hybrid Attention Mechanisms
Sathwik Narkedimilli, Satvik Raghav, Om Mishra +5
Galaxy interaction classification remains challenging due to complex morphological patterns and the limited interpretability of deep learning models. We propose an attentive neural…
A Novel XAI-Enhanced Quantum Adversarial Networks for Velocity Dispersion Modeling in MaNGA Galaxies
Sathwik Narkedimilli, N V Saran Kumar, Aswath Babu H +5
Current quantum machine learning approaches often face challenges balancing predictive accuracy, robustness, and interpretability. To address this, we propose a novel quantum adver…
REDDIX-NET: A Novel Dataset and Benchmark for Moderating Online Explicit Services
MSVPJ Sathvik, Manan Roy Choudhury, Rishita Agarwal +2
The rise of online platforms has enabled covert illicit activities, including online prostitution, to pose challenges for detection and regulation. In this study, we introduce REDD…
Comparative Analysis of Black Hole Mass Estimation in Type-2 AGNs: Classical vs. Quantum Machine Learning and Deep Learning Approaches
Sathwik Narkedimilli, Venkata Sriram Amballa, N V Saran Kumar +5
In the case of Type-2 AGNs, estimating the mass of the black hole is challenging. Understanding how galaxies form and evolve requires considerable insight into the mass of black ho…
Enhancing IoT Network Security through Adaptive Curriculum Learning and XAI
Sathwik Narkedimilli, Sujith Makam, Amballa Venkata Sriram +3
To address the critical need for secure IoT networks, this study presents a scalable and lightweight curriculum learning framework enhanced with Explainable AI (XAI) techniques, in…
FAPL-DM-BC: A Secure and Scalable FL Framework with Adaptive Privacy and Dynamic Masking, Blockchain, and XAI for the IoVs
Sathwik Narkedimilli, Amballa Venkata Sriram, Sujith Makam +2
The FAPL-DM-BC solution is a new FL-based privacy, security, and scalability solution for the Internet of Vehicles (IoV). It leverages Federated Adaptive Privacy-Aware Learning (FA…
FL-DABE-BC: A Privacy-Enhanced, Decentralized Authentication, and Secure Communication for Federated Learning Framework with Decentralized Attribute-Based Encryption and Blockchain for IoT Scenarios
Sathwik Narkedimilli, Amballa Venkata Sriram, Satvik Raghav
This study proposes an advanced Federated Learning (FL) framework designed to enhance data privacy and security in IoT environments by integrating Decentralized Attribute-Based Enc…
Photometric Analysis for Predicting Star Formation Rates in Large Galaxies Using Machine Learning and Deep Learning Techniques
Satvik Raghav, Prasanth Ayitapu, Sathwik Narkedimilli +2
Star formation rates (SFRs) are a crucial observational tracer of galaxy formation and evolution. Spectroscopy, which is expensive, is traditionally used to estimate SFRs. This stu…
Predicting Stellar Metallicity: A Comparative Analysis of Regression Models for Solar Twin Stars
Sathwik Narkedimilli, Satvik Raghav, Sujith Makam +2
The research focuses on determining the metallicity ([Fe/H]) predicted in the solar twin stars by using various regression modeling techniques which are, Random Forest, Linear Regr…