DDFL: A Deep Dual Function Learning-Based Model for Recommender Systems. - Syed Tauhid Ullah Shah; Jianjun Li; Zhiqiang Guo; Guohui Li 001; Quan Zhou 003 (DASFAA (3), 2020)

Trustworthy and Reliable Deep-Learning-Based Cyberattack Detection in Industrial IoT. - Fazlullah Khan; Ryan Alturki; Md. Arafatur Rahman; Spyridon Mastorakis; Imran Razzak; Syed Tauhid Ullah Shah (IEEE Trans. Ind. Informatics, 2023)

A Secure Ensemble Learning-Based Fog-Cloud Approach for Cyberattack Detection in IoMT. - Fazlullah Khan; Mian Ahmad Jan; Ryan Alturki; Mohammad Dahman Alshehri; Syed Tauhid Ullah Shah; Ateeq Ur Rehman 001 (IEEE Trans. Ind. Informatics, 2023)

Explainable Detection of Fake News on Social Media Using Pyramidal Co-Attention Network. - Fazlullah Khan; Ryan Alturki; Gautam Srivastava 001; Foziah Gazzawe; Syed Tauhid Ullah Shah; Spyridon Mastorakis (IEEE Trans. Comput. Soc. Syst., 2024)

From Inductive to Deductive: LLMs-Based Qualitative Data Analysis in Requirements Engineering. - Syed Tauhid Ullah Shah; Mohamad Hussein; Ann Barcomb; Mohammad Moshirpour (REFSQ Workshops, 2025)

DSRS: DELIGHT sequential recommender system. - Syed Tauhid Ullah Shah; Fazlullah Khan; Shirin Yamani; Ryan Alturki; Foziah Gazzawe; Muhammad Imran Razzak (Eng. Appl. Artif. Intell., 2025)

TinyVit-LightGBM: A lightweight and smart feature fusion framework for IoMT-based cancer diagnosis. - Hongwei Wang; Xu Dai; Shipeng Ning; Jinjun Ye; Gautam Srivastava 001; Fazlullah Khan; Syed Tauhid Ullah Shah; You Pan (Inf. Fusion, 2025)

Explainability as a Compliance Requirement: What Regulated Industries Need from AI Tools for Design Artifact Generation. - Syed Tauhid Ullah Shah; Mohammad Hussein; Ann Barcomb; Mohammad Moshirpour (CoRR, 2025)