collaborators

6 papers

cs.DB2026

AutoPK: Leveraging LLMs and a Hybrid Similarity Metric for Advanced Retrieval of Pharmacokinetic Data from Complex Tables and Documents

Hossein Sholehrasa, Amirhossein Ghanaatian, Doina Caragea +3

Pharmacokinetics (PK) plays a critical role in drug development and regulatory decision-making for human and veterinary medicine, directly affecting public health through drug safe…

cs.IR2026

Leveraging Large Language Models for Automated Scalable Development of Open Scientific Databases

Nikita Gautam, Doina Caragea, Ignacio Ciampitti +1

With the exponential increase in online scientific literature, identifying reliable domain-specific data has become increasingly important but also very challenging. Manual data co…

physics.chem-ph2026

Neural Network Based Molecular Structure Retrieval from Coulomb Explosion Imaging Data

Amirhossein Ghanaatian, Aravinth K. Ravi, Joshua Stallbaumer +6

Determining the structure and following the structural evolution of molecules undergoing chemical reactions is one of the key goals of ultrafast molecular physics and chemistry. Re…

cs.LG2025

Predictive Modeling and Explainable AI for Veterinary Safety Profiles, Residue Assessment, and Health Outcomes Using Real-World Data and Physicochemical Properties

Hossein Sholehrasa, Xuan Xu, Doina Caragea +2

The safe use of pharmaceuticals in food-producing animals is vital to protect animal welfare and human food safety. Adverse events (AEs) may signal unexpected pharmacokinetic or to…

cs.CR2025

Benchmarking Android Malware Detection: Traditional vs. Deep Learning Models

Guojun Liu, Doina Caragea, Xinming Ou +1

Android malware detection has been extensively studied using both traditional machine learning (ML) and deep learning (DL) approaches. While many state-of-the-art detection models,…

cs.CR2025

The Impact of Train-Test Leakage on Machine Learning-based Android Malware Detection

Guojun Liu, Doina Caragea, Xinming Ou +1

When machine learning is used for Android malware detection, an app needs to be represented in a numerical format for training and testing. We identify a widespread occurrence of d…