collaborators

6 papers

cs.IR2026

Improving User Experience with Personalized Review Ranking and Summarization

Muhammad Jawad Mufti, Omar Hammad, MD. Mahfuzur Rahman

Online consumer reviews are important decision-support resources in e-commerce, yet the increasing volume of reviews often creates information overload and makes it difficult for u…

cs.LG2026

A Rolling-Window Framework for Churn Prediction and Behavioral Driver Identification

Muhammad Jawad Mufti, Omar Hammad, Haitham Saleh +1

Customer churn prediction is a central task in customer analytics, particularly in non-contractual, pay-per-use service environments where disengagement is not explicitly observed…

cs.HC2026

Context-Aware Workflow Decomposition for Automated Mobile UI Annotation Using Multimodal Large Language Models

Athar Parvez, Muhammad Jawad Mufti, Muqaddas Gull +1

Accurate mobile user interface annotation is important for UI understanding, accessibility tools, automated testing, dataset construction, and GUI agents. However, mobile screens a…

cs.HC2026

MUIAnno: An Expert-Annotated Dataset and Evaluation Benchmark for Mobile UI Understanding

Athar Parvez, Muhammad Jawad Mufti, Muqaddas Gull +1

Understanding mobile user interfaces is important for building intelligent systems such as automation tools, accessibility solutions, and UI-aware agents. However, progress in this…

cond-mat.mtrl-sci2026

From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

Aritra Roy, Kevin Shen, Andrew MacBride +350

Large language models (LLMs) are rapidly changing how researchers in materials science and chemistry discover, organize, and act on scientific knowledge. This paper analyzes a broa…

cs.LG2025

Generalizable Diabetes Risk Stratification via Hybrid Machine Learning Models

Athar Parvez, Muhammad Jawad Mufti

Background/Purpose: Diabetes affects over 537 million people worldwide and is projected to reach 783 million by 2045. Early risk stratification can benefit from machine learning. W…