Topics

<> prediction tools (2)

Promoters identification and analysis

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B1 L2 R2202

Promoter is a key region that is involved in differential transcription regulation of protein-coding and RNA genes. The gene-specific architecture of promoter sequences makes it extremely difficult to devise the general strategy for their computational identification.

Novel computational methods for promoter identification and analysis

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B2 L5 R5209

In this dissertation, I present the methods I have developed for prediction of promoters for different organisms. Instead of focusing on the classification accuracy of the discrimination between promoter and non-promoter sequences, I predict the exact positions of the TSS inside the genomic sequences, testing every possible location. The developed methods significantly outperform the previous promoter prediction programs by considerably reducing the number of false positive predictions. Specifically, to reduce the false positive rate, the models are adaptively and iteratively trained by changing the distribution of samples in the training set based on the false positive errors made in the previous iteration. The new methods are used to gain insights into the design principles of the core promoters. Using model analysis, I have identified the most important core promoter elements and their effect on the promoter activity. I have developed a novel general approach to detect long range interactions in the input of a deep learning model, which was used to find related positions inside the promoter region. The final model was applied to the genomes of different species without a significant drop in the performance, demonstrating a high generality of the developed method.
<> price formation (2)

On mean-field game price models

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B9 L2 H1 R2322

Abstract In this talk, we discuss a mean-field game price formation model. This model describes a large number of rational agents that can trade a commodity with an exogenous supply. The price is determined by a balance condition between supply and demand. We discuss the well-posedness of the model, the uniqueness and regularity of the price function. Then, we examine two explicit models - the linear-quadratic problem and a model with finitely many agents. Time permitting, we will examine the connections between this problem and optimal transport with constraints. Brief Biography Diogo Gomes

David Evangelista

David Evangelista is a Ph.D. Candidate at King Abdullah University of Science and Technology (KAUST), working in the areas of partial differential equations, mean-field games (MFG), and market microstructure. He is expect to receive a Ph.D. from KAUST in June 2019, under the direction of Professor Diogo A. Gomes. David's research interests are in optimal control theory, nonlinear partial differential equations, MFG, and market microstructure. MFG is a framework to study interactions of a large number of indistinguishable players that play differential games. MFG has become an active research
<> printed RF electronics (2) <> probabilistic sensitivity analysis (2) <> probabilities (2) <> problems (2)

Finite element approximation of parameter dependent eigenvalue problems

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B9 L2 R2322

Eigenvalue problems arising from partial differential equations are used to model several applications in science and engineering, ranging from vibrations of structures, industrial microwaves, photonic crystals, and waveguides, to particle accelerators.

Finite element approximations for variable-order fractional diffusion problems

Prof. Wenyu Lei, University of Electronic Science and Technology of China

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B4 L5 R5209

We propose a finite element scheme for fractional diffusion problems with varying diffusivity and fractional order. A number of challenges are encountered when discretizing such problems. The first is the heterogeneous kernel singularity in the fractional integral operator. The second comes from the dense discrete operator with its quadratic growth in memory footprint and arithmetic operations. To address these challenges, we propose a strategy that decomposes the system matrix into three components. The first is a sparse matrix that handles the singular near-field separately and is computed by adapting singular quadrature techniques available for the homogeneous case to the case of spatially variable order.
<> promoters (2)

Promoters identification and analysis

-

B1 L2 R2202

Promoter is a key region that is involved in differential transcription regulation of protein-coding and RNA genes. The gene-specific architecture of promoter sequences makes it extremely difficult to devise the general strategy for their computational identification.

Novel computational methods for promoter identification and analysis

-

B2 L5 R5209

In this dissertation, I present the methods I have developed for prediction of promoters for different organisms. Instead of focusing on the classification accuracy of the discrimination between promoter and non-promoter sequences, I predict the exact positions of the TSS inside the genomic sequences, testing every possible location. The developed methods significantly outperform the previous promoter prediction programs by considerably reducing the number of false positive predictions. Specifically, to reduce the false positive rate, the models are adaptively and iteratively trained by changing the distribution of samples in the training set based on the false positive errors made in the previous iteration. The new methods are used to gain insights into the design principles of the core promoters. Using model analysis, I have identified the most important core promoter elements and their effect on the promoter activity. I have developed a novel general approach to detect long range interactions in the input of a deep learning model, which was used to find related positions inside the promoter region. The final model was applied to the genomes of different species without a significant drop in the performance, demonstrating a high generality of the developed method.
<> prompt optimization (2) <> protein coding (2)

Promoters identification and analysis

-

B1 L2 R2202

Promoter is a key region that is involved in differential transcription regulation of protein-coding and RNA genes. The gene-specific architecture of promoter sequences makes it extremely difficult to devise the general strategy for their computational identification.

Novel computational methods for promoter identification and analysis

-

B2 L5 R5209

In this dissertation, I present the methods I have developed for prediction of promoters for different organisms. Instead of focusing on the classification accuracy of the discrimination between promoter and non-promoter sequences, I predict the exact positions of the TSS inside the genomic sequences, testing every possible location. The developed methods significantly outperform the previous promoter prediction programs by considerably reducing the number of false positive predictions. Specifically, to reduce the false positive rate, the models are adaptively and iteratively trained by changing the distribution of samples in the training set based on the false positive errors made in the previous iteration. The new methods are used to gain insights into the design principles of the core promoters. Using model analysis, I have identified the most important core promoter elements and their effect on the promoter activity. I have developed a novel general approach to detect long range interactions in the input of a deep learning model, which was used to find related positions inside the promoter region. The final model was applied to the genomes of different species without a significant drop in the performance, demonstrating a high generality of the developed method.
<> protein structure prediction (2) <> Public health surveillance (2) <> QD laser (2) <> Quality of service (2) <> quantile regression (2) <> Quantinuum (2) <> quantum chemistry (2)

Introduction to High Performance Computational Chemistry with an Application of Hierarchical Matrices

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B2 B3 A0215

This talk begins with an introduction to quantum chemistry for HPC researchers. We discuss the main computational kernels, how their performance is limited by various bottlenecks, and algorithms and implementations that improve performance. One particular kernel is the calculation of the Coulomb matrix. Whereas the fast multipole method (FMM) can be used to rapidly compute the Coulomb potential for sets of point charges, continuous variants of FMM were developed in the 1990s for sets of charge distributions that arise in quantum chemistry.

Mani Sarathy

Professor Sarathy's research interest is in developing sustainable energy technologies with decreased net environmental impact. A major thrust of research is improving the operation of power generation technologies. The goal of Professor Sarathy's research is study conventional and alternative fuels (e.g., biofuels, synthetic fuels, etc.), so the environmental impact of combustion systems can be reduced. He applies AI and ML techniques to study complex energy related problems such as fuel design, renewable hydrogen production, and process control and optimization in energy intensive operations.
<> quantum computing. (2) <> Quantum Dots (2) <> quantum engineering (2) <> quantum information processing (2) <> Quantum information theory (2) <> Quantum Measurements (2) <> quantum mechanical kinetic theory (2) <> quantum mechanics (2)

Quantum Inspired Photonics

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B1 L2 R4214

Quantum mechanics and photonics share mathematical equivalence. By carefully exploiting the interplay between optical index, gain and loss in the complex dielectric permittivity plane, optics has become an ideal platform to explore some exotic quantum concepts, such as topological physics and parity-time (PT) symmetry. Instead of counteracting optical losses at micro and nano scales in integrated photonics, we started from an opposite viewpoint and developed a new paradigm of positively and strategically manipulating optical losses by the quantum-inspired photonics concept enrich fundamental optical physics and realized novel photonic synthetic matters with unique optical functionalities. In this seminar, I will present our recent efforts on engineering the complex optical potentials at an exceptional point (i.e. PT symmetry transition point). Based on the exceptional point-induced unidirectionality, we harness optical losses to enable unique microlaser functionalities, in particular, an orbital angular momentum (OAM) microlaser that structures and twists the lasing radiation at the microscale, which is expected to address the growing demand for information capacity. Additionally, I will discuss non-Hermitian topological photonics where optical non-Hermiticity and topological physics are coupled.

Esraa Fakeih

<> Quantum optics (2) <> Quasi-Monte Carlo (2) <> radar (2) <> radar applications (2) <> Radar imaging (2) <> Radio Wave Propagation Modeling (2) <> raman scattering microscopy (2) <> random fields (2) <> Random number generator (2)

Random number generation based on digital differential chaos

1 min read ·
Mohamed Zidan, et al., "Random number generation based on digital differential chaos." In 2011 IEEE 54th International Midwest Symposium on Circuits and Systems (MWSCAS), 2011, 1. In this paper, we present a fully digital differential chaos based random number generator. The output of the digital circuit is proved to be chaotic by calculating the output time series maximum Lyapunov exponent. We introduce a new post processing technique to improve the distribution and statistical properties of the generated data. The post-processed output passes the NIST Sp. 800-22 statistical tests. The system

Fully digital jerk-based chaotic oscillators for high throughput pseudo-random number generators up to 8.77 Gbitss

1 min read ·
Abhinav S. Mansingka, et al., "Fully digital jerk-based chaotic oscillators for high throughput pseudo-random number generators up to 8.77 Gbitss" Microelectronics Journal 44, (9), 2013, 744. Abstract: This paper introduces fully digital implementations of four different systems in the 3rd order jerk-equation based chaotic family using the Euler approximation. The digitization approach enables controllable chaotic systems that reliably provide sinusoidal or chaotic output based on a selection input. New systems are introduced, derived using logical and arithmetic operations between two system
<> random process (2) <> reasoning (2) <> reconfigurable intelligent surface (2) <> Rectifiers (2)

All‐Oxide Thin Film Transistors and Rectifiers Enabling On‐Chip Capacitive Energy Storage

1 min read ·
Wang Zhenwei, et al., "All‐Oxide Thin Film Transistors and Rectifiers Enabling On‐Chip Capacitive Energy Storage." Advanced Electronic Materials 5 (12), 2019, 1900531. All-oxide, fully-transparent thin film transistors and rectifiers, processed entirely by atomic layer deposition, have been developed for on-chip capacitive energy storage. Fully depleted thin film transistor (TFT) operation is achieved by optimizing the carrier concentration in the ZnO channels. The TFTs show an average saturation mobility of 10.5 cm2 V−1 s−1, a stable positive turn-on voltage of 0.88 V, a low subthreshold

Mahmoud Ouda

Postdoctoral Research Fellow, Sensors
Mahmoud Ouda is currently a Postdoctoral Research Associate with the Communications and Signal Processing Group (CSP), Department of Electrical and Electronic Engineering at Imperial College London. He received his Ph.D. from King Abdullah University of Science & Technology (KAUST), Saudi Arabia in 2016, and his M.Sc. and B.Sc. (with honors) both in Electronics and Communications Engineering from Ain Shams University, Cairo, Egypt, in 2011 and 2006 respectively. He was a Graduate Research Assistant with the Sensors Lab. in King Abdullah University of Science & Technology (KAUST) from 2010 to
<> recursive self-improvement (2) <> Regression Models (2) <> regularity theory (2) <> Rehabilitation (2) <> Relay networks (2)

Anas Chaaban

Postdoctoral Research Fellow, Communication Theory Lab
Anas Chaaban was a Postdoctoral Research Fellow in CTL(Communication Theory Lab), KAUST. He now is an assistant professor in University of British Columbia (UBC), British Columbia , Canada Selected Publications Ph.D. Thesis A. Chaaban, “Relaying for Interference Management,” Faculty of Electrical Engineering and Information Technology, Ruhr-University of Bochum, Bochum, Germany, July 2013. M.S. Thesis A. Chaaban, “Some Aspects of Adaptive Decoding of Concatenated Codes,” Institute of Telecommunications and Applied Information Theory, University of Ulm, Ulm, Germany, June 2009. Journal

Ali Chelli

Postdoctoral Research Fellow, Communication Theory Lab
Ali Chelli is currently a Post doctoral Research Fellow at Norwegian University of Science and Technology, Trondheim , Norway. Selected Publications Book Chapters: A. Chelli and M. Pätzold, “A non-stationary MIMO vehicle-to-vehicle channel model derived from the geometrical T-junction model,” Chapter in Vehicular Technologies: Increasing Connectivity, Edited by: Miguel Almeida, INTECH, Apr. 2011. A. Chelli and M. Pätzold, “The impact of fixed and moving scatterers on the statistics of MIMO vehicle-to-vehicle channels,” Chapter in Radio Communications, A. Bazzi (ed.), INTECH, Apr. 2010. Ph.D
<> remote sensing applications (2) <> representation learning (2) <> research ethics (2) <> RF energy harvesting (2) <> RFID (2) <> risks (2) <> roadmap (2) <> robot (2) <> Robotics in Agriculture and Forestry (2)

Optimal Design of Agricultural Walking Robot

Prof. Sayat Ibrayev, Institute of Mechanics and Engineering

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B18 Fellowship Hall

Featured Sessions
Abstract Legged machines that can adapt to off-road conditions and irregular terrain, have a number of advantages over traditional wheeled and tracked vehicles. In particular, in agriculture, they cause the least damage to the soil, in comparison with wheeled and tracked vehicles, due to the discrete track on the ground. Meanwhile, attaining to increase productivity of agricultural machines leads to an increase of machine weight that cause increased soil pressure and unfavorable conditions for plant growth. Various designing concepts of legged robots have been proposed by research teams by now

Smart Agricultural Robotics for Monitoring Coral Reefs and Plants: A vertical farming perspective

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B18 Fellowship Hall

Featured Sessions
Abstract Aquaponics is a vertical farming technique and an integrated production of fish and hydroponic crops with recirculation of the aquaculture effluent used by the plant as fertilizer. This technique offers high water efficiency, a faster growth rate, and high crop yields. Despite all the advantages offered by this technology, its implementation on a commercial scale is hindered by many technical and economic factors, which can be addressed by integrating smart technologies, automation, and control. Together with the landmark technologies of Industry 4.0, such as robotics, artificial
<> Robotics manipulators (2) <> robotokids2021 (2) <> robust optimization (2) <> robust statistics (2) <> RTL (2) <> Runge-Kutta methods (2) <> SABIC (2) <> Safety (2) <> SAR (2) <> Scheduling and Coordination (2)

Robotics and Automation in Coral Monitoring and Restoration

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B18 Fellowship Hall

Featured Sessions
Abstract Monitoring and preservation of coral reefs are critical for marine biology research, economic development, and environmental protection. Given that long-term survey of marine environments and restoring bleached coral reefs are extremely labor-intensive, autonomous robots are emerging as one of the key solutions to address such challenge. In this talk, we present on-going projects at KAUST Robotics group in conceiving autonomous underwater robots for swift and safe navigation in complex environments to collect high-resolution coral images. We also discuss challenges and opportunities

The need for robotics and automatization to meet our global coral restoration goals

Dr. Sebastian Schmidt-Roach, BESE/Red Sea Research Center, KAUST

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B18 Fellowship Hall

Featured Sessions
Abstract Coral reefs are vital to a vast number of human livelihoods depending on them for fisheries, tourism and coastal protection. Facing dramatic global declines in coral cover and reef habitat degradation due to climate change and other anthropogenic impacts, coral reef restoration has become imperative to maintain their ecosystem services. In the Kunming-Montreal biodiversity framework the international community set ambitious goals, such as restoring, or being on the way to restore, 30% of degraded habitats by 2030. However, meeting these goals is currently constrained by the high
<> Schrödinger equation (2) <> SDN Networks (2) <> Secure communication (2) <> security (2) <> Semantic Communication (2) <> Semi-blind seismic deconvolution using orthogonal clustering (2) <> semiconductor lasers (2) <> semiconductors interfaces (2) <> sensing devices (2) <> sensing platforms (2) <> sensor (2)

Radio Frequency Sensing in Healthcare: Detection of Falls, Gait Abnormality and Vital Signs

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B9 L2 H1

In this talk, we represent recent advances of radio frequency (RF) sensing technology for healthcare, specifically in monitoring human activities inside homes, retirement facilities, and hospitals. Sensing technologies and data analytics are considered powerful tools in efficient indoor monitoring of human activities. Monitoring of activities of daily living (ADL) can identify falls, which are considered as the leading cause of fatal and non-fatal injuries for people aged 65 and over. It can also detect variants in activity patterns and changes in routines and lifestyle as well as the state of physical, cognitive, and psychological health of the person. In addition to monitoring ADL, RF-based gesture recognition using hands and arms is shown to be an important contactless technology for Man-Machine-Interface (MMI). Adding to the indoor applications, RF-based vital sign monitoring has vast medical use, as respiration and heartbeats are essential diagnostic barometers for many health problems. More recently, RF sensors have also been proposed for gait analysis for rehabilitation and timely diagnosis of many neurological, orthopedic and medical conditions. Changes in gait patterns can also be precursors of falls. In this talk, we present successful examples in each of the above application areas and discuss pertinent open problems worthy of investigations.

Recent Advances in Sensor Design

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KAUST

In this talk we will discuss the work conducted at KAUST sensors lab and KAUST sensor initiative
<> Shaheen (2) <> SiGe nanotube FET (2) <> SIGMOD (2) <> Signal processing for wireless communications (2) <> Signal processing for Wireless Networks (2) <> silicon (2) <> Silicon photonics (2) <> silicon solar cell (2)

Flexing for the next silicon wave

1 min read ·
Ultrathin, rigid silicon segments that are wired through interdigitated metal contacts produce ultraflexible high-performance solar cells.

Stefaan De Wolf

Stefaan De Wolf is a Professor of​ Material Science and Engineering, and the Interim Associate Director for the KAUST Solar Center. ​Stefaan De Wolf's expertise lies in the science and technology of photovoltaics for terrestrial applications. His research focuses on the fabrication of high-efficiency silicon-and perovskite based solar cells, with specific attention to the fundamental understanding of interface structures and electrical contact formation, relevant to solar cells and electronic devices in general. He is also interested in new device architectures and applications, such as multi-junction solar cells, aimed at the improved utilization of the full solar spectrum for electricity generation, and the development of photovoltaic solutions for hot and sunny climates. He is also interested in new device architectures and applications, such as multi-junction solar cells, aimed at the improved utilization of the full solar spectrum for electricity generation, the development of photovoltaic solutions for hot and sunny climates, as well as exploring machine-learning methods to accelerate photovoltaic research.
<> silicon-based photodetectors (2) <> Simulations (2) <> Single atom catalysts (2)

Abdullah Bukhamsin

Ph.D. Student (former), Bioengineering
Selected Publications: Bukhamsin, Abdullah, et al. " In vivo dynamics of indole-and phenol-derived plant hormones: Long-term, continuous, and minimally invasive phytohormone sensor." (2025) Science Advances. Bukhamsin, Abdullah, et al. " Accelerating adoption of species-agnostic plant sensors for precision farming." (2025) Nature Reviews Electrical Engineering. Bukhamsin, Abdullah, et al. " Early and high-throughput plant diagnostics: strategies for disease detection." (2024) Trends in Plant Science. Bukhamsin, Abdullah, et al. " Minimally-invasive, real-time, non-destructive, species

Abdullah Bukhamsin

Selected Publications: Bukhamsin, Abdullah, et al. " In vivo dynamics of indole-and phenol-derived plant hormones: Long-term, continuous, and minimally invasive phytohormone sensor." (2025) Science Advances. Bukhamsin, Abdullah, et al. " Accelerating adoption of species-agnostic plant sensors for precision farming." (2025) Nature Reviews Electrical Engineering. Bukhamsin, Abdullah, et al. " Early and high-throughput plant diagnostics: strategies for disease detection." (2024) Trends in Plant Science. Bukhamsin, Abdullah, et al. " Minimally-invasive, real-time, non-destructive, species
<> single cell biology (2) <> smart agriculture (2)
COEfoodsecurity

AI-enabled UAVs and Multimodal Monitoring for Protected and Controlled Environment (PACE)

This project aims to utilize advanced technologies for UAVs to enhance the efficiency, accuracy, and responsiveness of crop monitoring and management within the diverse PACE settings. The primary objectives revolve around employing a fleet of micro-UAVs equipped with cameras and LiDAR sensors to capture high-resolution images and 3D point clouds and perform multi-layered AI analysis. While cameras offer visual insights into surface-level plant health and characteristics, LiDAR provides deeper insights about plant physical attributes for a more comprehensive crop assessment. This project is

Flying LoRA IoT Gateway for Agricultural Applications

Prof. Samsuzana Abd Aziz, Department of Biological and Agricultural Engineering, Universiti Putra Malaysia

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B18 Fellowship Hall

Featured Sessions
Abstract Low-Power Wide Area Network (LPWAN) technologies like LoRa have become prominent for IoT deployments in large agricultural areas due to their low-power and long-range transmission. However, data transmission in large farms with diverse landscapes suffers from obstructions or occlusions, and wired gateways are still difficult to cover the whole agricultural areas without proper network or power infrastructures. This study integrates LoRa gateways with a flying drone to enhance the connectivity to sensor nodes deployed in an oil palm plantation. The LoRa gateway was mounted on a multi
<> smart systems (2)

Extreme Computing Universals

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B9 L2 R2325

This talk redefines "extreme" computing as operating under severe resource constraints rather than just massive scale, outlining universal algorithmic, hardware, and system-level strategies to overcome these challenges, illustrated by KAUST success stories.

Developing smart systems to connect communities.

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KAUST

In this talk, we address fundamental questions that should be asked when contemplating future smart and connected systems, namely, How, Where and What? How can we design computing and communication nodes that best utilize resources in a way that is cognizant of both the abilities of the platform, as well as the requirements of the network? Where are the nodes deployed? By understanding the context of deployment, one can architect unique solutions that are currently unimaginable. With the transformation to diverse applications such as body area networking, critical infrastructure monitoring, precision agriculture, autonomous driving etc., the need for innovative solutions becomes even more amplified. What benefit can be inferred from the data gathered by nodes in the capacity of computing, communication and sensing? The talk will discuss how recent advances in wireless computing and communication nodes can be harnessed to serve the multitude of deployment scenarios required to empower communities of the future with smart and connected systems.
<> smartphone (2) <> SO2 (2)

Highly sensitive and selective SO2 MOF sensor: the integration of MFM-300 MOF as a sensitive layer on a capacitive interdigitated electrode

1 min read ·
Valeriya Chernikova, et al., "Highly sensitive and selective SO2 MOF sensor: the integration of MFM-300 MOF as a sensitive layer on a capacitive interdigitated electrode." Journal of Materials Chemistry A 6(14), 2018, 5550. We report on the fabrication of an advanced chemical capacitive sensor for the detection of sulfur dioxide (SO2) at room temperature. The sensing layer based on an indium metal–organic framework (MOF), namely MFM-300, is coated solvothermally on a functionalized capacitive interdigitated electrode. The fabricated sensor exhibits significant detection sensitivity to SO2 at

Fluorinated MOF Platform for Selective Removal and Sensing of SO 2 from Flue Gas and Air

1 min read ·
Mohamad Tchalala, et al., " Fluorinated MOF Platform for Selective Removal and Sensing of SO 2 from Flue Gas and Air", Nature communications, 10(1), 2019, 1. Conventional SO2 scrubbing agents, namely calcium oxide and zeolites, are often used to remove SO2 using a strong or irreversible adsorption-based process. However, adsorbents capable of sensing and selectively capturing this toxic molecule in a reversible manner, with in-depth understanding of structure–property relationships, have been rarely explored. Here we report the selective removal and sensing of SO2 using recently unveiled
<> Sobolev Spaces (2) <> Social media (2) <> Social robot navigation (2) <> Sound Source Localization (2) <> Spatial data (2) <> spatial transcriptomics (2) <> spectral efficiency (2) <> SPIE (2) <> Spintronics devices (2) <> splitting methods (2) <> SRSI (2) <> Stability (2)