energy efficiency

Integrated Silicon Photonics with Quantum Dot On-Chip Lasers: Enabling Scalable and Energy-Efficient Photonic Systems

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This talk presents how quantum dot lasers integrated on silicon provide the missing on-chip light source for scalable photonic systems spanning AI computing, hardware security, and coherent LiDAR sensing.
Syed Abidullah Fareed

Syed Abidullah Fareed

Visiting Student (former), Information Science Lab

Nanomaterials and Nanostructure Based Energy Efficient In-Memory Sensing

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KAUST

In this talk, I will present the potential of nano-islands grown by the atomic layer deposition (ALD) in addition to novel material combinations in scaled memory devices. Moreover, in order to relax the scalability requirement, I will introduce an integrated potential single device solution by infusing memory device which can monitor and remember our actions and the surrounding environment. Such a device performs the roles of both a MEMory and a senSOR at once and is referred to as a MEMSOR. The MEMSOR is directly programmed by external physical stimuli rather than an applied electric potential as in conventional devices. As a result, the MEMSOR leads to faster data analysis, lower footprint area, energy consumption, and ideally, the cost of the system. Finally, the MEMSOR device will be based on a MOSFET architecture with a mature manufacturing process, and thus it can be integrated with conventional Flash devices on the same silicon wafer with minimal additional process steps.

Maha Alsabban

Research Interests Maha is pursuing her M.Sc nowadays at King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia under the supervision of Prof. Shehab Ahmed. She received her B.Sc degree in Electrical and Computer Engineering from Effat University in Jeddah, Saudi Arabia in 2021 with a concentration in power and control systems. Her capstone project entitled “Smart Electricity Meter Monitoring and Power Consumption Analysis” focused on monitoring and analyzing power consumption readings from smart meters. Her research interests are in the areas of power distributions

Anas Daghistani

Anas Daghistani obtained his Master's Degree in Computer Science under the supervision of Prof. Basem Shihada from King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia. Anas received a B.Sc. degree in Computer Engineering from Umm Al-Qura University, Makkah, Saudi Arabia. Currently, he is a Ph.D. student at Purdue University. Master Thesis title: " Green-Frag: Energy Efficient Frame Fragmentation Scheme for Wireless Sensor Networks". Research Interest Anas's research interests cover a wide range of topics in computer networking such as wireless sensors, MIMO systems

Anas Saleh Mohammed

Visiting Student (former), Electrical and Computer Engineering
Visiting student at King Abdullah University of Science and Technology (KAUST).

Abdulrahman Alabbasi

Abdulrahman Alabbasi obtained his Ph.D. degree in Electrical Engineering under the supervision of Professor Basem Shihada at King Abdullah University of Science and Technology (KAUST). Currently, he is working as a Senior Researcher at Ericsson in Sweden. Thesis title: " Towards Energy Efficient Cognitive Radio System". Education Profile ​PhD. in Electrical Engineering, King Abdullah University of Science and Technology, Thuwal, KSA M.Sc. in Electrical Engineering, University of Electro-Communications (UEC), Tokyo, Japan Scientific and Professional Membership ​IEEE Research Interest