News & Updates
Latest publications, achievements, and announcements from our lab.
Our paper on Personalized Vigilance Estimation has been accepted at CogSci 2026.
Our paper, 'KANformer: Personalized Vigilance Estimation with Transformer Features and Kolmogorov–Arnold Sequence Modeling,' has been accepted at CogSci 2026 with a highly competitive 9.3% acceptance rate. Congratulations to the team!
Our paper on Dynamic Ensembles Multimodal Prediction accepted on ICPR 2026.
Our paper, "MM-DES: Enhancing Multimodal Clinical Prediction with Joint Contrastive Embeddings and Dynamic Ensembles," has been accepted at the 28th International Conference on Pattern Recognition (ICPR 2026). Congratulations to the team!
Our new paper on trustworthy medical diagnosis published in Engineering Applications of Artificial Intelligence.
Our new paper on Trustworthy Alzheimer's diagnosis has been published in Engineering Applications of Artificial Intelligence (JCR top 2%). Congratulations to the team!
Read moreA Deep Dive into Function Inlining and its Security Implications for ML-based Binary Analysis
Our paper has been accepted at the Network and Distributed System Security Symposium (NDSS 2026).
Read more(AdvChar) Attacking Interpretable NLP Systems
Our paper is published in IEEE Transactions on Information Forensics and Security.
Read moreWelcome new lab members; Leila Shakuova, Abdulrahman Al-Sharabati, and Zichen Song
We are excited to welcome Leila, Abdulrahman, and Zichen as new graduate students joining our lab. Looking forward to their contributions and collaborations!
Exposing Deep Vulnerabilities in Interpretable NLP Systems
Natural Language Processing (NLP) models, even those built for transparency and interpretability, remain highly vulnerable to adversarial manipulation. Our newly submitted paper, AdvChar, presents a stealthy black-box attack that preserves semantic meaning and interpretability while misleading classifiers. By applying minimal character-level modifications (only two characters on average), AdvChar can dramatically deteriorate model accuracy across seven NLP models and three interpretation paradigms revealing that interpretability tools can be exploited to disguise malicious inputs. Read more on arXiv.
Read moreAdViT; Breaking Vision Transformers and Their Interpreters
Vision Transformers (ViTs), often paired with interpretation models, are widely viewed as robust and reliable for security-critical domains such as healthcare, autonomous driving, drones, and robotics. However, our latest paper challenges this assumption by introducing AdViT, a novel attack that successfully deceives both ViT classifiers and their interpreters. AdViT achieves a 100% attack success rate across diverse models, with up to 98% misclassification confidence in white-box and 76% in black-box settings while still producing convincing interpretations. These results reveal that even state-of-the-art transformer systems remain highly vulnerable to stealthy adversarial threats. Read more on arXiv.
Read moreChronic Kidney Disease Detection Augmented with Hybrid Explainable AI
Our paper was presented at the 15th International Conference on Electrical Engineering (ICEENG 2025).
Read moreStealthy Query-Efficient Opaque Attack Against Interpretable Deep Learning
Our paper was published in IEEE Transactions on Reliability.
Read moreSustainable energy management in the AI era; a comprehensive analysis of ML and DL approaches
Our paper was published in *Computing* (Vol. 107, Issue 6, p.132).
Read moreIoT-based approach method for learning geometric shapes in early childhood and device thereof
Our patent application was submitted to the US Patent Office (App. No. 18/821,509).
Read moreSemantic information retrieval method for augmented reality domain and device thereof
Our patent application was submitted to the US Patent Office (App. No. 18/818,158).
Read moreTowards Robust Federated Learning Investigating Poisoning Attacks Under Clients Data Heterogeneity
Our paper was published in the 2025 19th International Conference on Ubiquitous Information Management and Communication (IMCOM).
Read moreExplainable Multi-Layer Dynamic Ensemble Framework Optimized for Depression Detection and Severity Assessment
Our paper was published in Diagnostics journal.
Read moreSmart Collaborative Intrusion Detection System for Securing Vehicular Networks Using Ensemble Machine Learning Model
Our paper was published in Information journal.
Read moreNew team members joining
New researcher joined our team at InfoLab, Welcome Shatha!
New team members joining
New researcher joined our team at InfoLab, Welcome Bobonazar!
New team members joining
New researcher joined our team at InfoLab, Welcome Abdenour!
Hardening Interpretable Deep Learning Systems Investigating Adversarial Threats and Defenses
Our paper was accepted at IEEE Transactions on Dependable and Secure Computing (TDSC)
New team members joining
New researchers joined our team at InfoLab, Welcome Chensheng 'Chris' and Shweta!
Explainable AI for Trustworthy AI
Our paper on Explainable Artificial Intelligence is available online at Information Fusion Journal (IF:17.56)
Early Prediction of Parkinson's Disease
Our paper on early prediction of Parkinson's disease using multimodal deep learning is available at Computer Methods and Programs in Biomedicine (IF:7.02)
Toward Comprehensive Chronic Kidney Disease Prediction Based on Ensemble Deep Learning Models
Our paper was published in Applied Sciences journal.
Read moreNew team member joining
New researcher joined our team at InfoLab, Welcome Amir!
Predicting CTS Diagnosis and Prognosis Based on Machine Learning Techniques
Our paper was published in Diagnostics journal.
Read moreAnatomical Structure Segmentation in X-ray
Our paper on anatomical structure segmentation in chest X-ray images is available at Scientific Reports (Nature)
A Holistic Approach to Identify and Classify COVID-19 from Chest Radiographs, ECG, and CT-Scan Images Using ShuffleNet Convolutional Neural Network
Our paper was published in Diagnostics journal.
Read morePrediction of Alzheimer's Progression
Our paper using multimodal deep learning is available at Information Fusion Journal (IF:17.56)
Colon Cancer Diagnosis Based on Machine Learning and Deep Learning Modalities and Analysis Techniques
Our paper was published in Sensors journal.
Read moreAHA-AO Artificial Hummingbird Algorithm with Aquila Optimization for Efficient Feature Selection in Medical Image Classification
Our paper was published in Applied Sciences journal.
Read moreNew team member joining
New researcher joined our team at InfoLab, Welcome Haseeb!
Bug Bounty Competition at SKKU
Our lab member Omar got 2nd place in the SKKU Bug Bounty competition
Sentiment Analysis of Users Reactions on Social Media during the Pandemic
Our paper was published in Electronics journal.
Read moreMLxPack; Investigating Packers' Effect on Malware Detection
Our paper was accepted at CySSS workshop, ACM ASIACCS 2022
Flow Behavior of Mg Alloy using ML
Our fourth collaborative paper with Hamad's Lab is published in Mathematics journal
Uzbek Researchers Competition
Firuz Juraev won 1st place in IT section at World Association of Youth of Uzbekistan in Korea
Optimizing Adversarial Perturbations
Our paper at CSoNET 2021 is available online
Design of Hard Materials Using ML
Our third collaborative paper with Hamad's Lab is now online
AdvEdge; Adversarial Perturbations for Interpretable DL
Eldor presented our work at CSoNET 2021, Canada
Sepsis Prediction in ICU
Our paper is published in Neural Computing and Applications Journal
Discovering Hard Materials
Our second paper with Hamad's Lab is now online
New team member joining
New researcher joined our team at InfoLab, Welcome Omar!
Alzheimer's Diagnosis Using Semantic Rule-Based Modeling
Paper available in CMC-Computers, Materials & Continua journal
Robust Code Authorship Identification
Paper published in ACM Transactions on Privacy and Security
An Extended Semantic Interoperability Model for Distributed Electronic Health Record Based on Fuzzy Ontology Semantics
Our paper was published in Electronics journal.
Read moreAndroid Malware Analysis
Paper on classification and analysis of Android malware is available online
New team member joining
New researcher joined our team at InfoLab, Welcome Sajid!
Hybrid Deep Learning for Alzheimer's
Paper available in Knowledge-Based Systems journal
ML-aided Design of Aluminum Alloys
First collaborative paper with Hamad's Lab is now online
New team members joining
New researchers joined our team at InfoLab, Welcome Firuz, Junaid, and Nasir!
New team members joining
New researchers joined our team at InfoLab, Welcome Eldor and Sun!
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