Welcome to the Information Science Lab!

Welcome to the Information Science Lab (ISL)—a dynamic research hub led by Professor Tareq Al-Naffouri. Our work centers on cutting-edge signal processing techniques, including adaptive, sparse, and statistical methods, with applications spanning wireless communications, ultrawideband and ultrasound-based localization, and real-time tracking systems.

At ISL, we’re driven by innovation and collaboration. Our diverse team tackles complex challenges in wireless network design and intelligent sensing, pushing the boundaries of what's possible in both theory and application. Explore our ongoing projects, discover internship opportunities, and meet the brilliant minds shaping the future of information science.

News

Asymptotic Analysis of One-bit Quantized Box-Constrained Precoding in Large-Scale Multi-User Systems

Happy to share that our paper has been accepted for publication as a SPECIAL ISSUE paper in the IEEE Journal of Selected Topics in Signal Processing!

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Happy to share that our paper "Asymptotic Analysis of One-bit Quantized Box-Constrained Precoding in Large-Scale Multi-User Systems", co-authored by Xiuxiu Ma, Dr Abla Kammoun, Prof Tareq Al-Naffouri, and Prof Mohamed-Slim Alouini, has been accepted for publication as a SPECIAL ISSUE paper in the IEEE Journal of Selected Topics in Signal Processing! 📡 In this study, we provide a precise asymptotic characterization of the performance of a quantized precoder, obtained by applying quantization to the output of a box-constrained precoder, within the asymptotic regime where the numbers of antennas
RIS-Aided Near-Field Channel Estimation under Mutual Coupling and Spatial Correlation

Our paper has been accepted for presentation at IEEE GLOBECOM in Taipei, Taiwan, this December.

1 min read ·
Our paper, "RIS-Aided Near-Field Channel Estimation under Mutual Coupling and Spatial Correlation," has been accepted for presentation at IEEE GLOBECOM in Taipei, Taiwan, this December. This work investigates how mutual coupling and subspace spatial correlation affect channel estimation in near-field RIS-aided systems. We developed an improved estimator that leverages mutual coupling information for better performance. Our findings show that by accounting for these factors, our new estimator performs significantly better than the standard method. It also achieves performance close to the MMSE
Multimodal biometric authentication using camera-based PPG and fingerprint fusion

Our recent work on multimodal biometric system is published in Pattern Recognition Letters

1 min read ·
We’re excited to share our recent work is published in Pattern Recognition Letters, where we introduce a novel multimodal biometric system that fuses camera-based PPG signals and fingerprint data—all captured using just a smartphone camera! 🎥👆 💡 Key Highlights: ✅ No specialized sensors needed—both fingerprint and PPG are acquired through the same video stream from a user touching the smartphone lens. 🧠 Powered by a homogeneous neural architecture with dual structured state-space model (SSM) encoders for fingerprint and PPG signals. 🔄 Introduces a cross-modal attention mechanism and a
KAUST-CEMSE-ECE-ISL-PhD-Alumni-Vijith-Farewell

ISL bids farewell to Dr. Vijith Varma Kotte

1 min read ·
Information Science Lab, CEMSE, KAUST bids farewell to Dr. Vijith Varma Kotte, who recently defended his PhD dissertation in Electrical and Computer Engineering at #KAUST under the supervision of Prof. Tareq Al-Naffouri. During his time at #ISL, Vijith made impactful contributions in the areas of FMCW radar signal processing in automotive, non-contact biomedical monitoring, and THz communication. His research focused on enabling smart sensing systems through AI-driven signal processing techniques, with real-world applications in health, automotive, and next-generation wireless systems. Dr

No Wearables, No Lab Tests—Just a Screen Touch for Hydration Tracking

1 min read ·
At the Information Science Lab, we are constantly exploring innovative solutions that merge everyday technology with impactful scientific advancements. One of our most exciting recent discoveries is a noninvasive hydration monitoring system, utilizing the capacitive sensors embedded in smartphone screens. Our researchers have demonstrated that a simple fingertip touch can assess hydration levels in real time—without the need for needles, wearables, or cumbersome lab equipment. The Science Behind Our Discovery Led by our research scientist, Dr Muhammad Mahboob-ur-Rahman, and PI Prof Tareq Al
KAUST-CEMSE-ECE-ISL-PhD-Defense-Vijith

Congratulations to Vijith Varma Kotte on successfully defending his PhD dissertation

1 min read ·
🎉 Congratulations to Vijith Varma Kotte on successfully defending his PhD dissertation titled “FMCW Radar Systems for Automotive and Biomedical Applications” under the supervision of Prof. Tareq Al-Naffouri. This work advances FMCW radar as a versatile and robust sensing modality by developing cutting-edge signal processing and deep learning techniques across two impactful domains: 🔹 Automotive Applications: Introduced a forward-looking MIMO-SAR radar imaging system, significantly enhancing azimuthal resolution using unsupervised Deep Basis Pursuit and Convolutional Decoder models. 🔹
KAUST-CEMSE-ECE-Omar-Khalifa-Winner-Of-Non-Terrestrial-Networks-for-6G-(NTNYS'24

KAUST ECE students achieve high honors in Competition on Non-Terrestrial Networks for 6G (NTNYS'24)

4 min read ·
KAUST Ph.D. candidate Omar Khalifa earned an impressive second place in the global Competition on Non-Terrestrial Networks for 6G (NTNYS'24). The IEEE Future Networks Initiative organized the competition as part of the "Connecting the World from the Skies Global Forum," which took place last November in Riyadh. Second place, and a prize of $10,000, was awarded to Khalifa based on his work titled "Supplying Data for Digital Twins in Green Smart Cities: A Non-Invasive NTN-IoT Approach." The international forum, which focused on the theme “Shaping the Future of Converged Connectivity,” was hosted
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KAUST CEMSE ISL CST Course 2024 at Riyadh

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