Current Research

Autonomous Systems & Smart Mobility

​​As the world’s urban population rapidly grows, cities all over the world are experiencing severe traffic congestion. Traffic congestion causes widespread socioeconomic and environmental issues for cities. In addition to the rapid growth of the number of vehicles on the road, unexpected roadway conditions caused by roadside construction/maintenance, car accidents, asynchronous traffic signals, changes in driver behavior, among other factors also cause the traffic congestion in urban areas. To address these issues, the key focus of ITL research includes natural language processing (NLP) for intelligent transportation systems, machine learning for IoT service discovery, and smart infrastructure for futuristic cities. More details are here.

Smart Cities

​​ITL is investigating many challenging problems related to the UAV operation in smart city. The ITL team also focuses on optimizing the 3D navigation of low-altitude UAVs in urban areas and determining the best courses to adopt to successfully accomplish their missions. Deterministic and reinforcement learning approaches for multiple UAVs sharing obstacle-constrained environments are employed. A trip plan is determined for the autonomous UAVs to determine its daily schedule while taking into account various aspects such as locations of the events, the durations of the events, and the priority levels of the events. More details are here.

Metamaterials and Nanophotonics

Metamaterials consist of engineered periodic or aperiodic composites that collectively behave as an effective, innovative material. ITL is working on design and development of artificially engineered materials for a broad range of promising areas like renewable energy harvesting, autonomous diagnostics solutions for healthcare, next-generation holographic displays, and bio-sensing. We also focus on intelligent optimization tools for efficiently designing nano-devices. The focus areas include intelligent nanophotonics, next-generation holographic displays, customized smart bio-imaging & sensing, and reconfigurable intelligent surfaces for next-generation networks. More details are here.

Smart Energy

Smart Energy Systems provide the scientific basis for a paradigm shift away from single-sector thinking into a coherent and integrated understanding of how to design and identify the most achievable and affordable strategies to implement coherent future sustainable energy systems. At ITL, we focus on several enabling technologies for the smart energy systems for cleaner environment. Some examples of our work include solar thermophoto voltaic (STPV) systems, intelligent design of next generation sustainable energy systems, perovskite materials for energy harvesting, and energy resources based on refractory/transition nanomaterials. More details are here.

Spintronics for Next-generation Computing Systems

​​Spintronic devices exploit the spin of electrons to generate and control charge currents, and to interconvert electrical and magnetic signals. By combining processing, storage, sensing, and logic within a single integrated platform, spintronics could complement and, in some cases, outperform semiconductor-based electronics, offering advantages in terms of scaling, power consumption, and data processing speed. The focus of ITL team spans a wide range of spintronics-related fields including magnetic materials, spintronics theory, spin-based devices, circuits utilizing the spin, novel architecture and algorithms, understanding the computing principle and finally the fabrication of such devices. More details are here.

AI for Biological Systems

According to United Nations Sustainable Development Goals (UN SDGs), ensuring healthy lives and promoting well-being at all ages is essential to sustainable development. Moreover, the KSA vision 2030’s ‘Health Sector Transformation Program’ focuses on boosting public health and disease prevention. ITL focuses on development of artificial intelligence (AI)-enabled health solutions to address these challenges. Some representative works include automated blood cell counting and classification using deep learning, modeling and progression of American digital news media during the onset of the covid-19 pandemic, and a social IoT-driven pedestrian routing approach during epidemic time. More details are here.