8 citations · 19 across the 32 of their papers we have counts for
13 papers · 1 filter
CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations
Subash Neupane, Himanshu Tripathi, Shaswata Mitra +4
This paper presents ClinicSum, a novel framework designed to automatically generate clinical summaries from patient-doctor conversations. It utilizes a two-module architecture: a r…
IRSKG: Unified Intrusion Response System Knowledge Graph Ontology for Cyber Defense
Damodar Panigrahi, Shaswata Mitra, Subash Neupane +2
Cyberattacks are becoming increasingly difficult to detect and prevent due to their sophistication. In response, Autonomous Intelligent Cyber-defense Agents (AICAs) are emerging as…
Multivariate Data Augmentation for Predictive Maintenance using Diffusion
Andrew Thompson, Alexander Sommers, Alicia Russell-Gilbert +7
Predictive maintenance has been used to optimize system repairs in the industrial, medical, and financial domains. This technique relies on the consistent ability to detect and pre…
Poison Attacks and Adversarial Prompts Against an Informed University Virtual Assistant
Ivan A. Fernandez, Subash Neupane, Sudip Mittal +1
Recent research has shown that large language models (LLMs) are particularly vulnerable to adversarial attacks. Since the release of ChatGPT, various industries are adopting LLM-ba…
AAD-LLM: Adaptive Anomaly Detection Using Large Language Models
Alicia Russell-Gilbert, Alexander Sommers, Andrew Thompson +7
For data-constrained, complex and dynamic industrial environments, there is a critical need for transferable and multimodal methodologies to enhance anomaly detection and therefore…
Transfer Learning Applied to Computer Vision Problems: Survey on Current Progress, Limitations, and Opportunities
Aaryan Panda, Damodar Panigrahi, Shaswata Mitra +2
The field of Computer Vision (CV) has faced challenges. Initially, it relied on handcrafted features and rule-based algorithms, resulting in limited accuracy. The introduction of m…
Explainable Anomaly Detection: Counterfactual driven What-If Analysis
Logan Cummins, Alexander Sommers, Sudip Mittal +4
There exists three main areas of study inside of the field of predictive maintenance: anomaly detection, fault diagnosis, and remaining useful life prediction. Notably, anomaly det…
A Survey on Privacy Attacks Against Digital Twin Systems in AI-Robotics
Ivan A. Fernandez, Subash Neupane, Trisha Chakraborty +5
Industry 4.0 has witnessed the rise of complex robots fueled by the integration of Artificial Intelligence/Machine Learning (AI/ML) and Digital Twin (DT) technologies. While these…
A Survey of Transformer Enabled Time Series Synthesis
Alexander Sommers, Logan Cummins, Sudip Mittal +4
Generative AI has received much attention in the image and language domains, with the transformer neural network continuing to dominate the state of the art. Application of these m…
From Questions to Insightful Answers: Building an Informed Chatbot for University Resources
Subash Neupane, Elias Hossain, Jason Keith +6
This paper presents BARKPLUG V.2, a Large Language Model (LLM)-based chatbot system built using Retrieval Augmented Generation (RAG) pipelines to enhance the user experience and ac…
Generating Synthetic Time Series Data for Cyber-Physical Systems
Alexander Sommers, Somayeh Bakhtiari Ramezani, Logan Cummins +4
Data augmentation is an important facilitator of deep learning applications in the time series domain. A gap is identified in the literature, demonstrating sparse exploration of th…
MedInsight: A Multi-Source Context Augmentation Framework for Generating Patient-Centric Medical Responses using Large Language Models
Subash Neupane, Shaswata Mitra, Sudip Mittal +3
Large Language Models (LLMs) have shown impressive capabilities in generating human-like responses. However, their lack of domain-specific knowledge limits their applicability in h…
Patient-Centric Knowledge Graphs: A Survey of Current Methods, Challenges, and Applications
Hassan S. Al Khatib, Subash Neupane, Harish Kumar Manchukonda +4
Patient-Centric Knowledge Graphs (PCKGs) represent an important shift in healthcare that focuses on individualized patient care by mapping the patient's health information in a hol…