RIGHT FACULTY PROJECT

Ali I. Al-Naimi Petroleum Engineering Research Center

Graduate

A blueprint for an Indonesian Landslide Early Warning System

Academic Program: Statistics

The main aim of this research project is to scientifically explore the possibility to derive local alarm levels for rainfall-fed landslides and debris flows that are sufficiently reliable to become operational. These local alarm levels could serve as the basis for an operational Landslide Early Warning System (LEWS) in Java. This exploration of possibilities would be beneficial to BLS, the end-user technical organization with the task to provide technical input on landslide and lahar early warning systems in Indonesia. The successful VSRP student will focus on the statistical part of the project described above. He/she will build a reference statistical model based on past landslide occurrences explained as a function of meteorological data. Then, from this model, simulations will be generated in near-real-time as the current/future meteorological forecasts are streamlined from Indonesian partners. This will ensure a nowcast prediction for landslides with the same temporal frequency of the climatic forecast but most importantly, will provide early estimates of when and where landslides may occur as the incoming cloudburst move into the Indonesian territory.

BAS/1/1672-01-01

raphael.huser@kaust.edu.sa

Early warning systems; natural hazards; extreme rainfall events; widespread landslides.

Statistics, Hydrology, Climatology, Geomorphology

In the short term, the main deliverable consists of a platform where the calibrated landslide prediction model can be run together with the meteorological forecast to serve as an operational tool in the future. At this stage, we do not expect the product to be final but at least it should be efficiently working. In the long term, we aim at sharing this platform with Indonesian colleagues to strengthen an existing collaboration with them and to ultimately publish this work.

Statistics

Computer, Electrical and Mathematical Sciences and Engineering

Nitrogen availability is a key limiting factor for primary production on many coral reefs. As such, benthic organisms such as corals adapted and evolved efficient uptake and (re)cycling of the available nitrogen. The microbiome of coral holobionts aids in this cycling of nitrogen by 1) creating de novo bioavailable nitrogen via fixation of atmospheric dinitrogen (N2) performed by so called diazotrophs, and 2) alleviating bioavailable nitrogen through denitrification. While the latter seems counterintuitive at first, the majority of energy for coral holobionts is produced by a symbiotic relationship with photosynthetic dinoflagellates of the family Symbiodiniaceae which need to be in a nitrogen-limited state to translocate their photosynthates to the coral host. As such, denitrification could benefit coral holobiont health by aiding in keeping Symbiodiniaceae in a nitrogen-limited state. Recent research suggests that N2 fixation and denitrification essentially cancel each other out in several Red Sea corals (Tilstra et al., 2019). In contrast, Glaze et al. (2021) recently provided evidence that the significance of denitrification in hard corals from the Great Barrier Reef is negligible relative to other coral holobiont associated N-cycling pathways. However, besides focusing on different reef locations (central Red Sea vs. Eastern Indo-Pacific), both studies utilized different methods for their assessment. While the former used an acetylene based method quantifying holobiont-wide fluxes, the latter used labelled isotopes suitable for targeted quantifications. As such, a comparison between both studies may be confounded. To accurately assess the significance of denitrification relative to other N-cycling pathways (e.g. N2 fixation) associated with Red Sea corals, a comparative analysis using both methods with a range of corals will be conducted.

Link between heterotrophic capacity of Red Sea coral holobionts

Academic Program: Marine Science

Relative importance of denitrification within the nitrogen budget of Red Sea coral holobionts

Academic Program: Marine Science

BAS/1/1095-01-01

susana.carvalho@kaust.edu.sa

coral reefs, nitrogent cycling, coral microbiome

Coral reef microbiology

To generate a dataset that can be used for the student's master thesis and one associated publication.

Marine Science

Biological and Environmental Sciences and Engineering

While the measurement of temperature and chemical species is of current practice in conventional combustion processes (e.g., flames or engines), the experimental characterization of detonation usually relies on the determination of simple characteristic means (e.g., velocity, temperature, density gradient). Such diagnostics provide little confidence in the numerical simulation validations and the phenomenological comprehension extracted from them. Thus, recent studies are focused on employing laser diagnostics, such as the planar laser-induced fluorescence of hydroxyl radical (OH-PLIF), to characterize detonations. Besides the OH-PLIF is a powerful technique to characterize reaction fronts, direct experimental-numerical comparison of the results is not possible in detonation studies. Thus, we developed a spectroscopic code, called KATLIF, to enable such experimental-numerical comparisons. KATLIF simulates the LIF signal as a function of the thermodynamic conditions and the laser parameters provided as an input. The code is currently composed of several MATLAB routines and needs to be converted into a more efficient coding language for its future usage (web interface and high-performance computing). The objectives of the project are to improve the performance of the code and to ensure its portability on both web interface and high-performance computing architecture.

Red Sea Research Center

Fully 3D Printed Flexible ECG Patch with Dry Electrodes

Academic Program: Electrical Engineering

Fabrication and characterization of crossbar arrays of h-BN based memristors

Academic Program: Materials Science & Engineering

Fabrication of memristors with localized nanofilament

Academic Program: Materials Science & Engineering

Exploration of dielectric breakdown in hBN

Academic Program: Materials Science & Engineering

Spectroscopic code optimization for web interface integration and high-performance computing simulations

Academic Program: Mechanical Engineering

BAS/1/1396-01-01

karl.chatelain@kaust.edu.sa

Spectroscopy, Matlab code, web-interface integration

computer science

First, the student will have to become familiar with the preexisting version of KATLIF and its workflow. Then, the most appropriate coding language will be selected based on portability and performance criteria (web-interface integration, time to solution, parallelization, and possible future developments). Finally, the KATLIF code will be re-written in the selected language.

Mechanical Engineering

Clean Combustion Research Center

Graduate

Bioenergy Carbon Capture and Storage (BECCS) scaling potential in consideration of planetary boundaries

Academic Program: Chemical Engineering

Stochastic Differential Equations for Quantifying Forecast Uncertainty and Application to Renewable Power Forecast Data

Academic Program: Applied Mathematics and Computer Science

The student will work on building stochastic forecast models. We propose to model wind and

solar power forecast errors using parametric stochastic differential equations (SDEs). This

approach has been applied in various works: (Elkantassi et al., 2017 and Møller et al., 2016)

for wind power and (Badosa et al., 2018) for solar power. These SDEs will describe the evolution

over time of wind and solar power forecast errors. By inferring the parameters of our SDEs,

we can construct several possible forecast scenarios that are crucial to the decision-making

process. To compute the SDEs' parameters, we will use historical power production and an available deterministic forecast provided by official sources. We will also introduce an adaptive stepping method to simulate the paths of our SDE. We apply our approach on data from Uruguay as the country has been a global leader in the renewable energy transition.

The outcome of this project will be a general framework for uncertainty quantification and scenario

generation. In particular, this framework will be useful to:

provide novel different parametric model forms for renewable power using probabilistic forecasts based on stochastic differential equations.
develop computationally efficient and mathematically rigorous methods for estimating the SDE model parameters.
quantify the uncertainty of the given physic based renewable power numerical forecasts.
compare systematically power numerical forecasts in terms of the available data.

Baseline account: 4000000024

raul.tempone@kaust.edu.sa

Stochastic Differential Equations; Computational Statistics, Numerical Analysis, Stochastic Optimal Control, energy system modeling and optimization; data-driven modeling; machine learning, non-convex optimization, uncertainty quantification.

As the main project deliverable, we expect a scientific report (eventually a research manuscript) including detailed description and analysis of the proposed methodology developed within the course of the internship and providing all numerical experiments to showcase the versatility of the proposed framework.

The working environment the student will use should include a GIT repository shared with the project collaborators in which he includes all project-related materials such as progress reports codes, figures, and important references from the literature to facilitate the supervision task and communicate ideas more effectively.

We will meet weekly during the period of the project. The student is asked to work within a team that includes myself, an Associate Professor at Universidad De La Republica (Uruguay) and an Associate Professor at Paris 13 University.

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

Graduate

Coral Microbiology and probiotics

Academic Program: Marine Science

Efficient pricing of high-dimensional (multi-assets) European Options

Academic Program: Applied Mathematics and Computer Science

The student will work on designing new numerical methods based on hierarchical adaptive sparse grids quadratures combined with Fourier techniques for efficient pricing of high-dimensional (multi-assets) European Options. Specifically, the student will contemplate the possibility of finding a heuristic framework for an optimal choice of the integration contour (damping parameter) which controls the analyticity of the integrand in the Fourier space and hence accelerate the performance of the quadrature methods. He will also develop a systematic comparison between hierarchical deterministic quadrature methods, Tensor Product (TP) quadrature, Smolyak (SM) Sparse Grids quadrature, and Adaptive Sparse Grids (ASG) quadrature to numerically evaluate the option price under different pricing dynamics, Geometric Brownian Motion (GBM), Variance Gamma (VG) and Normal Inverse Gaussian (NIG) for different multi-asset payoff functions such as Basket Call/Put and Rainbow options. The student is also asked to elaborate a comparison in terms of computational complexity against the quadrature methods for different dimensions, and various combination of parameter sets within the mentioned pricing models.

400000024

chiheb.benhammouda@kaust.edu.sa

Multi-Asset Option Pricing, Fourier Transform, Lewis Valuation Approach, Damping Parameters, Lévy models, Hierarchical Adaptive Sparse Grids Quadrature, Monte Carlo

Computational Finance, Computational Mathematics, Numerical Analysis

As the main project deliverable, we expect a scientific report (eventually a research manuscript) including a detailed description and analysis of the proposed methodology developed within the course of the internship and providing all numerical experiments to showcase the versatility of the proposed heuristic framework. The working environment the student will use should include a GIT repository shared with the project collaborators in which he includes all project-related materials such as progress reports, codes, figures, and important references from the literature to facilitate the supervision task and communicate ideas more effectively.

Applied Mathematics and Computer Science

Computer, Electrical and Mathematical Sciences and Engineering

The goal of this project is developing methods to merge Machine Learning (ML) with physics-based models to create control algorithms can significantly enhance the resiliency of Cyber-Physical Systems (CPS). The approach will combine recent results in ML with control theory via constrained optimization to create novel systems and methods for protecting CPS from malicious cyber intruders via detection and prevention strategies. Specifically, the research project focuses on (1) refining the offline/online training and execution algorithms of ML models through physics-based constrained optimization, (2) developing secure estimation and control algorithms that are significantly more resilient to cyber-attacks than the state-of-the-art counterparts, and (3) improving the distributed resiliency for networked systems supporting multi-agent autonomous systems.

Learning to model geophysical processes with NNs

Academic Program: Earth Science and Engineering

Resilient Models for Attacks Detection in Cyber-Physical Systems

Academic Program: Electrical Engineering

BAS/1/1692-01-01

charalambos.konstantinou@kaust.edu.sa

Cyber-physical systems, resiliency, cybersecurity, control methods, machine learning, physics-based methods.

Electrical and Computer Engineering/Computer Science

The goal of this internship is to analyze and improve existing data-driven and physics-based algorithms for attack detection in CPS. The student will be expected to learn about existing solutions, as well as the challenges and requirements to applying such techniques in their settings. With guidance of other team members, the student will then find new solutions for improving algorithmic resiliency in order to reduce cyber-risks related to the CPS operation. Candidates should be motivated to work on research-oriented problems with a team and develop new solutions. They should have a strong background in controls, in particular with regards to machine learning and power systems. They are also expected to be proficient in MATLAB/Simulink.

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

Corals play an integral part in the health of the oceans as ecosystem engineers, building highly diverse and large reef systems. However, rapid increases in natural and human-induced stressors mean that coral reefs are under more pressure than ever and are declining rapidly. In particular, increases in sea surface temperature threaten the functioning of the coral holobiont (the coral host plus its associated microbes). In order to better understand how corals will perform in warmer seas, this study will assess coral physiology across a temperature gradient in the central Red Sea, where some coral colonies are inhabiting high-temperature reef flats that serve as analogs to future ocean conditions. In particular, this project aims to evaluate total energy reserves (lipid, protein, and carbohydrate content) of corals across this temperature gradient from several reefs near KAUST. This project will focus, among others, on the following research questions: 1. Are there significant differences in total energy reserves of corals from sites experiencing different temperature ranges? 2. What are the seasonal differences in total energy reserves, and does season attenuate/magnify differences between sites? This position will primarily assist with extraction and quantification of lipids, protein and carbohydrates of samples in the laboratory. Assistance with sample collection in the field is also possible. As all of the colonies inhabit shallow water and are sampled via snorkeling, SCUBA certification is not required for this fieldwork. Due to the COVID-19 pandemic, all VSRP students are required to be fully vaccinated before arrival. Please refer to the VSRP webpage for more information.

Real-Time (co-)Simulation for Cybersecurity

Academic Program: Computer Science

Regaining Trust in IoT

Academic Program: Computer Science

Cyber-Secure Integration of Renewable Energy Sources

Academic Program: Electrical Engineering

Ransomware in Industrial Control Systems

Academic Program: Computer Science

Physiology of corals from Red Sea reef flats

Academic Program: Marine Science

BAS/1/1010-01-01

Walter.richiv@kaust.edu.sa

Coral; Coral reefs; Physiology; Thermal tolerance

Coral physiology

The project is intended to assist with a PhD thesis exploring coral holobiont functioning across thermal gradients in the Red Sea. The goal is to have a peer-reviewed publication, in which the student would be a co-author.

Marine Science

Biological and Environmental Sciences and Engineering

Liquid-repellent surfaces are utilized in a wide spectrum of practical applications, including anti-fogging coatings, reducing frictional drag, water desalination, separating alcohols and other volatile organics from fermenter broths, and beyond. The most common criteria for quantifying their liquid-repellence are based on measuring apparent contact angles – advancing and receding– of sessile droplets of probe liquids placed onto them. Of these, the receding contact angles provide crucial information about the chemical or topographical make-up of the surface. However, despite over two centuries of research on contact angles, there are no well-established theories for predicting receding contact angles, for instance, as a function of the surface micro/nano (hierarchical) texture and chemical make-up and the speed of the liquid front. Here, we propose to assess the efficacy of a Machine Learning approach towards predicting receding contact angles from surface roughness features. We aim to design and evaluate a neural network architecture for automatic inference of dynamic wetting properties including advancing and receding contact angles at various speeds, surface topography and chemical make-up, and drop size and volume. Subsequent analysis of model parameters can point to key surface features that contribute to changes in the output variable, which can help advance our fundamental understanding of wetting of complex surfaces, implicit in water science and technology.

Red Sea Research Center

Machine learning techniques for divergence-free field reconstruction

Academic Program: Applied Mathematics and Computer Science

Concentrated Solar Thermal Energy for Mineral Processing

Academic Program: Mechanical Engineering

A Machine Learning Approach to Unentangle Wetting

Academic Program: Chemical Engineering

Academic Program: Environmental Science and Engineering

BAS/1/1070-01-01

himanshu.mishra@kaust.edu.sa

machine learning, microstructures, wetting

The intern student will be tasked with: 1. Collecting a dataset of images of hierarchically textured natural surfaces and micro/nano fabricated surfaces, labeled with static and dynamic wetting properties and chemical composition. 2. Helping design and implement a neural network architecture, optimized for the prediction of apparent contact angles on hierarchical surfaces (e.g., mico, nano, or mili meter scale). Project-duration will be 3-6 month, and the student arrival/departure dates will be discussed.

Chemical Engineering

Biological and Environmental Sciences and Engineering

Water Desalination and Reuse Center

Electro-catalyzed C-C and C-X bond cross-couplings

Academic Program: Chemical Science

Expediting surface wave dispersion curve picking with ML

Academic Program: Earth Science and Engineering

Machine Learning and Dynamical Systems

Academic Program: Applied Mathematics and Computer Science

Learning to Cooperate in Multi-Robot Systems

Academic Program: Electrical Engineering

How can we make a group of robots to cooperate in perception and manipulation to perform a variety of missions? Examples include a team of small robot helicopters and ground robots, equipped with manipulators (robotic arms), productively monitoring and harvesting crops in precision agriculture or proactively identifying and removing potential hazards in smart infrastructure applications. To realize this, the robots need to have the ability to organize as a team and to cooperate with their peers in team missions. The project aims at studying principles and algorithms to realize robots' ability to learn to cooperate. In particular, the main theme of the study focuses on how to generalize the robots' learning capability across diverse environments and even different application domains. To answer this question, we begin by studying reinforcement learning principles designed for multi-robot cooperation and systematically investigate how the robots' learning process depends on parameters defining the systems and environments. Then we develop new models and computational tools to train a team of robots that provide performance guarantees across a wide range of application scenarios.

BAS/1/1695-01-01

shinkyu.park@kaust.edu.sa

Robotics, Multi-Robot Learning, Multi-Robot Cooperation

Electrical and Computer Engineering

The goal of this project is to develop, implement, and test a multi-robot learning framework. The students will have opportunities to learn many of computational methods designed for multi-robot cooperation/learning and experience designing and implementing their own algorithms using multi-robot systems. The students are encouraged to work on research-oriented problems and expected to come up with their own creative solutions. They should have backgrounds in reinforcement learning and know fundamentals in multi-robot control/planning, and they are expected have experience with robotics software and proficiency in programming languages (C/C++ and Python).

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

The past two decades have provided unprecedented growth in data modalities and data availability within the biomedical research. As a result, methodologies for the multi-omic analysis of bulk (average profiles derived from hundreds to millions of cells), single-cell data or both are in continuous development. Our team has been involved in such developments working on multi-omic frameworks (STATegra framework + STATEgRa Bioconductor package), multi-omic DeepLearning based analysis (LIBRA - BioarXiv) and specific tools such as GeneSetCluster to summarize information derived from gene-set enrichment analysis. We are looking for highly motivated and skilled visiting students to work on one or several of the following challenges sub-projects: - Upgrading STATegRA Bioconductor package to account for the novel developments, including the single-cell analysis applications and the integration with GeneSetCluster analysis tool. - Novel Deep Learning-based methodologies for multi-omic analysis. - Implementing Cell-to-cell interaction analysis as part of a multi-omic integrative framework. We have existing proprietary data to work in the context of the Bone Marrow. For any selected student, the project to be conducted will be decided based on the student's interest, technical proficiency, and level of study. We expect for any participant (a) to bring motivation, enthusiasm, creativity, and hard work, (b) give lab seminars on your work, (c) collaborate with other lab members, and (d) produce a final written report. References of interest: - STATegra framework: https://www.frontiersin.org/articles/10.3389/fgene.2021.620453/abstract - STATegRa package: https://www.bioconductor.org/packages/release/bioc/html/STATegRa.html - LIBRA single-cell multi-omic framework: https://www.biorxiv.org/content/10.1101/2021.01.27.428400v1 Link to recent publications of the team: http://www.lunacab.org/publications/

Developing bioinformatic tools for Multi-omic data integration

Academic Program: BioScience

BAS/1/1093-01-01

David.gomezcabrero@kaust.edu.sa

Single-cell analysis, multi-omic analysis, Deep Learning,

Biosciences, bioinformatics

Enhancing critical thinking, presentations skills, and scientific writing. The research, in collaboration and with support of team members, may lead to scientific publications. Obtaining a hands-on perspective at the frontier of bioinformatics, multi-omic analysis, and its applications in an interdisciplinary research group and environment.

Biological and Environmental Sciences and Engineering

The past two decades have provided unprecedented growth in data modalities and data availability within the biomedical research. As a result, methodologies for the multi-omic analysis of bulk (average profiles derived from hundreds to millions of cells), single-cell data or both are in continuous development. Our team has been involved in such developments working on multi-omic frameworks (STATegra framework + STATEgRa Bioconductor package), multi-omic DeepLearning based analysis (LIBRA - BioarXiv) and specific tools such as GeneSetCluster. As a next step, we aim to integrate into current integrative pipelines additional data-types such as Chromatin Conformation and Spatial profiling. We are looking for highly motivated and skilled visiting students to work on one or several of the following challenges sub-projects: - Integrating Chromatin Conformation information (such as HiC) in clinical oriented research. Myeloma as a case study. Proprietary data is available for such integration. - Integrating Spatial Transcriptomics and Cell-to-cell interaction analysis as part of a multi-omic integrative framework. We have existing proprietary data to work in the context of the Bone Marrow. For any selected student, the project to be conducted will be decided based on the student's interest, technical proficiency, and level of study. We expect for any participant (a) to bring motivation, enthusiasm, creativity, and hard work, (b) give lab seminars on your work, (c) collaborate with other lab members, and (d) produce a final written report. The project relies on multi-skilled collaborations involving biologists, clinicians, bioinformaticians and computational biologists. References of interest: - STATegra framework: https://www.frontiersin.org/articles/10.3389/fgene.2021.620453/abstract - STATegRa package: https://www.bioconductor.org/packages/release/bioc/html/STATegRa.html - LIBRA single-cell multi-omic framework: https://www.biorxiv.org/content/10.1101/2021.01.27.428400v1 - 3D data: https://www.nature.com/articles/s41467-020-20849-y

Bringing Chromatin Conformation and Spatial profiling into clinical research

Academic Program: BioScience

BAS/1/1093-01-01

David.gomezcabrero@kaust.edu.sa

Single-cell analysis, Multi-omic analysis, Deep Learning, Chromatin Conformation, Spatial Transcriptomics, Translational research

Biomedicine

Biological and Environmental Sciences and Engineering

One of big challenges in robotics research is in enabling robot navigation in crowded environments. As one key technical difficulty, in such environment, a robot would trap into a deadlock state where the robot is unable to advance to its destination, especially when it is surrounded by pedestrians and perceives them as obstacles which the robot is programmed to avoid collision against. This problem is widely known as a "freezing robot problem" and acts as a major hurdle in deploying robotic systems in real-world applications. We study this problem in the context of human-robot interaction and develop new algorithms that ensure deadlock-free robot navigation in pedestrian-populated environments. The project aims at developing both principles and algorithms to address the freezing robot problem: we begin by investigating how the human-robot interaction can be understood as a feedback interconnection of human and robot decision-making models and then identify under what specifications on the robot's decision-making model, the robot is guaranteed to be deadlock-free. We will explore tools from feedback control theory and game theory to find such specifications and develop robot navigation algorithms satisfying them. Ultimately, we will carrying out experiments using multiple mobile robot platforms to validate our framework in pedestrian-populated areas.

Characterization of chemical contaminants in wastewater to predict its role on natural transformation among microorganisms

Academic Program: Environmental Science and Engineering

Robot Navigation in Crowded Environments

Academic Program: Electrical Engineering

BAS/1/1695-01-01

shinkyu.park@kaust.edu.sa

Robotics, Human-Robot Interaction, Feedback Control

Electrical and Computer Engineering

The goal of this project is to develop, implement, and test a deadlock-free robot navigation framework based on well-established multi-agent decision-making models. The students will get to learn many of tools designed for robot perception and navigation tasks and gain experience in designing and implementing their own algorithms into robot platforms. Then the students are expected to design new methods to predict pedestrian motions using data from on-board sensors and to maneuver the robot in crowded areas. The students are encouraged to work on research-oriented problems and expected to come up with their own creative solutions. They should have backgrounds in robot perception and motion planning, and they are expected have experience with robotics software and proficiency in programming languages (C/C++ and Python).

Electrical Engineering

Computer, Electrical and Mathematical Sciences and Engineering

The aim of the project will be to contribute to the assessment of the CCUS potential in Saudi Arabia through the assessment of stationary CO2 emissions as well as the cost analysis (separation, capture, and transportation costs involved in CCS). The database for CO2 emissions from stationary sources in the Kingdom includes emissions from electricity generation, desalination, oil refineries, cement industry, petrochemicals, and iron & steel from 2016, that need to be verified and updated with most up-to-date data. The assessment will also include looking at identifying potential storage locations and estimating the capacity of storing CO2 in deep aquifers, depleted hydrocarbon reservoirs, and basaltic rocks.

The VSRP student will be involved in data analysis and interpretation in Petrel and, by picking up new ideas and techniques, will be able contribute to the further development of the Petrel/ArcGIS geological model of Saudi Arabia in order to identify and characterize potential CO2 storage sites in the country.
The student will also help in establishing and developing the national carbon storage atlas for KSA. A carbon storage atlas is a comprehensive assessment of all aspects of CCS including CO2 emissions, best practices, and emerging technologies related to carbon capture, transportation, and assessments of storage in potential geological sites and associated costs.

The work may include this section petrography using optical and electron microscopes to characterize rocks for carbon disposal.

Numerical approximation of partial differential equations

Academic Program: Applied Mathematics and Computer Science

Imaging with a Drone-borne Synthetic Aperture Radar

Academic Program: Electrical Engineering

Causal and Fair Machine Learning

Academic Program: Computer Science

Robust/Differentially Private Machine Learning

Academic Program: Applied Mathematics and Computer Science

Foundations of Private and Fair Statistics

Academic Program: Statistics

Lithofacies classification with transition-aware Neural Networks

Academic Program: Environmental Science and Engineering

Hydrodynamic characterization of membrane spacers

Academic Program: Environmental Science and Engineering

Protocol development for biomass quantification in membrane autopsies

Academic Program: Environmental Science and Engineering

KAUST-BioMOFs

Academic Program: Chemical Science

Impact of Holocene climatic shifts on the spatial sediment distribution in a carbonate lagoon

Academic Program: Energy Resources and Petroleum Engineering

Influence of short-term climate changes on the spatial facies distribution ina carbonate platform lagoon during Holocene (N Red Sea)

Academic Program: Earth Science and Engineering

Numerical Study of CO2 Storage in a Deep Aquifer in Saudi Arabia

Academic Program: Energy Resources and Petroleum Engineering

Tectonic evolution through analogue modelling

Academic Program: Energy Resources and Petroleum Engineering

High-resolution numerical modeling of atmospheric processes over the Arabian Peninsula

Academic Program: Earth Science and Engineering

Assessment of CCS in Saudi Arabia

Academic Program: Energy Resources and Petroleum Engineering

BAS/1/1400-01-01

Alexandros Tasianas eamail alexandros.tasianas@kaust.edu.sa

CO2 storage, CCS, GIS, geology

Carbon Capture Utilization and Storage (CCUS)

Contribute to the construction, verification and use of the 3D geological model of the Saudi Arabia using GIS and specialized geological interpretation software (creation/modification of formation top surfaces corresponding to potential storage sites, input of data e.g. well information, etc)

Verification of input and update of the existing GHG emissions database with the most recent data for the current CO2 stationary sources with locations, rates and industry sector for the country.

Energy Resources and Petroleum Engineering

Ali I. Al-Naimi Petroleum Engineering Research Center

Body Area Networks

Academic Program: Electrical Engineering

Conceptual design of membrane processes

Academic Program: Chemical and Biological Engineering

Data and power conversion using Microelectromechanical systems (MEMS)

Academic Program: Electrical Engineering

Spintronics Memory, Logic Devices and Circuits for Neuromorphic Computing Systems

Academic Program: Electrical Engineering

Molecular doping of organic semiconductors for high efficiency optoelectronic devices

Academic Program: Materials Science & Engineering

Doping of organic semiconductors plays a fundamental role to overcome typical limitations observed in organic electronic devices. Organic light-emitting diodes (OLEDs) and organic solar cells (OSC) benefits for instance of the introduction of highly conducting injection layers, while high conductivity is one of the basic requirements for organic thermoelectric materials. Organic field-effect transistors (OFETs), on the other hand, are almost entirely based on intrinsic materials and doping has been mainly employed to pattern areas close to the contacts in order to improve charge injection.1 Beside the investigation of high degree of doping, ultralow doping has been recently attracting great interest, with the aim of directly dope the devices active layer that were usually based on intrinsic organic semiconductors. OSC containing small weight percentage of molecular dopants in the bulk heterojunction were found to display an increased short-circuit current (Jsc) and hence higher power conversion efficiency (PCE), when compared to their intrinsic counterpart.2 OLEDs have been reported with improved performance and device color modulation with dopant concentration was reported.3 A similar approach has been employed for OFETs, where extremely high mobilities, beyond the highest reported in literature, have been reported for organic semiconductors blended with low concentrations of dopants.4–6 These latter approaches are based on the addition of low fractions of dopants (£ 1-2 mol%), hence providing a different scenario from that of highly doped conducting layers. Strong efforts have been spent in the understanding of doping in organic semiconductors, both from a chemical and physical point of view, providing hence guidelines for the synthesis and application of more effective dopants. Recently, Lewis acid have been reported to show promising features as dopants for solution-processed polymers and small molecules.4 Here we propose a systematic study of different types of Lewis acids to investigate the potentiality of this doping strategy for organic field-effect transistors. Different processing routes and compositions will be studied in order to establish relevant structure/processing/property interrelationships.

BAS/1/1389-01-01

Materials science

1. Prepare solutions and learn coating methods for the formation of solution processable thin films. [Month 1-6] 2. Learn how to prepare and measure organic electronic devices, such as high emitting diodes, organic solar cells and field-effect transistor. [Month 3] 3. Study the influence of dopants in structural and optical properties of organic semiconductors and devices. [Month 4] 4. Prepare project updates reports and presentation. [Month 6]

Materials Science & Engineering

Grafting is a common agronomic practice performed on different fruit plants such as, among others, apple tree, other Rosaceae and grapevine. It is used for improving the fruit cultivar adaptation to specific soil and for controlling some plant parasites. The rootstock affects scion development by influencing the reproductive performance, vigor, biomass accumulation and distribution in the plant, phenology and fruit yield. Moreover, a recent publication highlighted that rootstock type influences the recruitment by plants of microorganisms from the soil, which can be defined as the ‘seed-bank’ for root microbiome assemblages (Marasco et al., 2018, Microbiome 6:3. Doi 10.1186/s40168-017-0391-2). An aspect that is still overlooked is if and how the rootstock-scion combination affect the recruitment of the microbiome and their migration and colonization of the tissues in different plant compartments and organs. A deeper knowledge on this aspect is pivotal to better understand the factors steering the recruitment and the flux of microorganisms from the soil through the roots and within the plant compartments. Moreover, it would be interesting to unravel which rootstock-scion combinations can primarily influence the fruit quality, by inferring the functional diversity of the selected microbiome starting from high-throughput Illumina 16S rRNA gene sequencing. To investigate the community structure of the endophytic microbiome in different plant compartments (e.g. root, shoot, leaf, fruit) comparing several combinations of rootstock-scion pairs. The research will be conducted on fruit trees, e.g. grapevine, and the bulk soil (i.e. the soil not affected by root exudates) will be used as the reference microbial ‘seed-bank’.

KAUST Solar Center

Statistical models based on stochastic partial differential equations

Academic Program: Statistics

Biodiversity of Red Sea Reef Fishes

Academic Program: Marine Science

Connectivity of Shark Populations

Academic Program: Marine Science

Lactate signaling in synaptic plasticity

Academic Program: BioScience

Unraveling fungi community patterns in Red Sea coral reefs

Academic Program: Marine Science

The effect of rootstock-scion combination on microbiome selection by fruit plants

Academic Program: BioScience

BAS/1/1065‐01‐01

Plant-microbe interactions

-Creation of 16S rRNA gene libraries from soil and plant metagenomes for the description of the structure and taxonomy of the bacterial community associated to different plant compartments and to the bulk soil - Quali/quantitative identification of the bacterial taxa present in 16S rRNA libraries - Study of the alpha- and beta-diversity of the microbiome in different plant compartments according to the rootstock-scion combinations.

Biological and Environmental Sciences and Engineering

CRISPR-based genetic engineering of stem cells for in vitro production of human blood

Academic Program: BioScience

Multilevel and Unbiased Monte Carlo Methods for Option Pricing

Academic Program: Applied Mathematics and Computer Science

Online Outlier Detection for Functional Data

Academic Program: Statistics

Internship on Deep learning Methods for Satellite Data Downscaling

Academic Program: Statistics

Imaging the interfacial charge carrier dynamics at axial p-n junction nanowires

Academic Program: Chemical Science

To optimize the light harvesting, multiple junctions with different band gaps can be combined to match the solar spectrum, but lattice matching requirements severely limit the materials available for devices based on thin film growth. In general, nanowires (NWs) have emerged as building blocks for electronic and photonic technologies due to their distinct advantages over its bulk and planar counterparts. Multi-junction solar cells containing several p-n junctions which can be used to surpass the Shockley−Queisser efficiency limit in solar cells. However, the carrier dynamics at the interfaces of the p-n junctions are still not well understood. Being in this regime, the classical picture of photo-induced charge transfer at a heterojunction can be described as follows: right after excitation, electron-hole pairs are generated. This is followed either by electron-hole separation and drifting in opposite directions under the influence of the electric field of the p-n junction, or the electron-hole pairs can recombine radiatively by emitting a photon, or non-radiatively by carrier trapping or/and Auger recombination. However, where the exciton is localized and trapped, how the transfer occurs and how it depends upon the local environment is an important as yet unanswered question. The processes by which carriers transfer back across the interface and recombine, thereby returning to the equilibrium state, are highly dependent upon the local environment and are not fully understood and they cannot be catalogued using spectroscopic techniques. In other words, the accessibility of these dynamical processes by static imaging or steady-state and time-resolved spectroscopic techniques is very limited. The unique opportunity to visualize the carrier dynamics selectively on the material surface can only be accessed by 4D S-UEM with fs temporal and nm spatial resolutions. We will begin by utilizing the S-UEM technique to investigate charge dynamics in n-InGaN/p-GaN nanowires. For the S-UEM measurement, right after laser excitation, the time-resolved secondary electron images arising from the first few nm of the sample surface will be recorded, providing the image-contrast changes for mapping charge dynamics. Straightforwardly, bright or dark image contrast correspond to increase or decrease in the local electron density, telling us where the carriers (electrons/holes) are localized. In other words, bright and dark image contrast is interpreted as an increase in the local electron and hole densities, respectively. Moreover, charge separation and charge recombination can be directly accessed from the spreading out the bright contrast or from diminishing the dark contrast.

Electron imaging, interface dynamics, oproelectronic applications

With real-space imaging, we can examine the temporal behavior of a local surface area (i.e., pixel areas), providing direct information about the charge carrier dynamics including trapping and recombination on the surface and at the interface of inorganic single crystals, different structural compositions of InGaN nanowires and the electron-hole localization across the p-n junction based on GaN/InGaN nanowires. The results would help us in gaining valuable insights into the photo-physics of such materials and guide in the better designing of optoelectronic devices

Chemical Science

While charge carrier dynamics in the bulk of semiconductor materials are well understood, charge transport including ejection and diffusion on surfaces and interfaces is still one of the prime challenges facing the communities of solar cells and surface sciences. Unfortunately, time-resolved laser spectroscopies that have been commonly used to understand the dynamics of photo-generated carriers in condensed matter are limited by the large penetration depth (100s of nanometers) of their pump and probe pulses, making them only sensitive to the bulk properties of the investigated materials. Only rare, bespoke techniques based on ultrafast electron microscopies offer the surface sensitivity needed to track light-triggered carrier dynamics in real-time and space, such as four-dimensional scanning ultrafast electron microscopy (4D-SUEM) which has emerged recently as a powerful tool to investigate real space-time dynamics selectively, on top surfaces of various materials with high temporal and spatial resolutions. In 4D-SUEM, an optical laser pulse at 515 nm is used to excite the material surface; a pulsed primary electron beam is then generated through a delayed UV excitation pulse at 343 nm from the cooled Schottky field-emitter tip, emitting secondary electrons from the surface of the specimen in a manner that is extremely sensitive to the local electron/hole density at the surfaces and interfaces. Time-resolved secondary electrons images produced from the excited surface are detected and then analyzed, pixel-by-pixel. In this study, we will use 4D-SUEM to selectively map surface dynamics including carrier diffusion length of the MAPbI3 single crystals with different facets and different surface treatment. We will also try to image the interface of solar cells base on these single crystals including the charge carrier ejection to the electron and hole transporting layers as well as the impact of the oxide layers on the carrier dynamics and device performance

Real-Space Imaging of Perovskite Single Crystals Using 4D Electron Microscopy

Academic Program: Chemical Science

Surface Dynamics Characterization

The finding of this project may offer a clear view of the extreme carrier diffusion behavior as a result of facet termination and surface treament. The results will be useful to address device performance bottle-necks, opening a new avenue to create MAPbI3 single crystal-based optoelectronic devices that take advantage of previously unknown, extreme surface behaviors.

Chemical Science

Electrospray ionization (ESI) is a process that entails flowing liquids though metallic capillaries, typically held at voltages > 3 kV, leading to the formation of a fine spray of charged droplets (due to the imbalance between the cohesive surface tension and repulsive electrostatics). ESI is extensively used to characterize a diverse array of solutes, from simple ions to complex macromolecular complexes, using mass spectrometry (MS) - together, the platform is known as ESIMS. In the recent years,usingESIMS, researchers have reported that a number of chemical reactions accelerate by orders of magnitude, when carried out in ESI droplets in comparison to the reactions in the bulk phase. Examples include, the phosphorylation of glucose and ribose, Pomeranz-Fritsch synthesis of isoquinoline, the reaction between o-phthalaldehyde and alanine, and the ozonation of oleic acid. However, the mechanisms underlying these dramatic rate accelerations remain hotly debated. Most recently, using a variety of experimental and computational tools, we have demonstrated that ESI of solutions of water lead to gas-phase reactions, which are not representative of the air-water interface at thermodynamic equilibrium. 1 Now, we would like to develop an reactor based on ESI to investigate acid-catalyzed reactions towards the goal of producing high-value chemicals, for instance, of interest to the pharmaceutical industry.Specifically, the Summer Intern will investigate operational parameters, including the ionic strength and pH of water, ESI voltage, coaxial gas-flow rate, length of the reactor, etc., to optimize conditions based on reactions, such as the Fries Rearrangement of phenylacetate. We will analyze the reaction products through nuclear magnetic resonance and chromatography techniques. References:1. Gallo, et al., Chemical Science (2019) DOI: 10.1039/C8SC05538F

Model- vs. Data-Parallelism for Training of Deep Neural Networks

Academic Program: Computer Science

Design and Control of Power Conversion Systems

Academic Program: Electrical Engineering

Continual Learning

Academic Program: Computer Science

Imagination Inspired Vision

Academic Program: Computer Science

Accelerated Chemistries in High-voltage Sprays of Water

Academic Program: Environmental Science and Engineering

BAS/1/1070-01-01

Environmental and Materials Science

The VSRP intern will work with a senior graduate student and learn the following skills:• Laboratory experiments: ESI-MS, ESI reactions, voltagesources,identifying reactions of interest • Theory: basic electrostatics, data analysis, scientific writing We expect the intern to be knowledgeable in chemical engineering, driven by curiosity, hard-working, and thrive in a multicultural work environment.

Environmental Science and Engineering

Biological and Environmental Sciences and Engineering

Water Desalination and Reuse Center

Liquid marbles

Academic Program: Environmental Science and Engineering

How Insects-inspired Surfaces Prevent Wetting?

Academic Program: Environmental Science and Engineering

Diel Variations in the primary productivity of the upper ocean from autonomous glider and autonomous profiling float observations

Academic Program: Marine Science

Microfluidics-based single-molecule fluorescence imaging of nanoscopic cellular interactions

Academic Program: BioScience

Development of shortwave infrared emitting fluorophores and bioimaging application

Academic Program: BioScience

Numerical modeling of enhanced geothermal systems

Academic Program: Earth Science and Engineering

Stochastic analysis of multiple fracture propagation and interaction in reservoir rocks

Academic Program: Earth Science and Engineering

Joint models for longitudinal and survival data

Academic Program: Applied Mathematics and Computer Science

Impacts of UV radiation on corals and other organisms in the Red Sea

Academic Program: Marine Science

Biological stability of chlorinated and non-chlorinated drinking water

Academic Program: Environmental Science and Engineering

Characterization of biofilm growthrate in a membrane system

Academic Program: Environmental Science and Engineering

3D Bioprinting of Cell-Laden Microgels for the General Construction of Vascularized Tissue Structures and Organoids

Academic Program: BioScience

3D bioprinting is a fabrication technology that aims to produce complex 3D functional living tissues suitable for disease modeling and even organ transplantation. Consequently, this technology has gained strong interest in areas such as tissue engineering and regenerative medicine. It is believed that 3D bioprinting gives promising solutions to solve the organ shortage for transplantation and to bridge the gap between 2D cell culture and live tissue experiments. In 3D bioprinting technology, biomaterials and cells are printed together to produce viable tissue-constructs with different shapes and sizes at the micro- and macro-scale level. However, 3D bioprinting technology is currently facing problems in terms of poor performance in shape fidelity of the 3D constructs, biocompatibility, and vascularization. These drawbacks could arise from the biomaterial and the bioprinting method used. For instance, synthetic polymers lack cell adhesion motifs while naturally derived materials lack appropriate mechanical strength. Moreover, most of the bioprinting methods rely on UV- or chemical crosslinking that could be harmful to the cells. To overcome these problems, we have developed a 3D bio-printing method to print under physiological conditions using self-assembling ultrashort peptides (SUP) as bioinks. SUP are natural peptides that are chemically synthesized and can be tailored to include biological and physicochemical cues for the improvement in biocompatibility and shape fidelity of the 3D construct. Nevertheless, our bioprinting approach still has technical challenges in controlled cell distribution and vascularization. To address these issues, we are working on the incorporation of SUP microgels covered by endothelial cells into the 3D bioprinting process to drive the cell to cell connection among microgels.

BAS/1/1075-01-01

Materials Science

Print self-assembling ultrashort peptides (SUP) as bioinks

Biological and Environmental Sciences and Engineering

Computational Bioscience Research Center

Modelling and numerical simulation

Academic Program: Applied Mathematics and Computer Science

MPS modelling of carbonate rocks

Academic Program: Earth Science and Engineering

Vertical and Lateral Heterogeneity in Unconventional Source Rock Sequences

Academic Program: Energy Resources and Petroleum Engineering

Economic production of a hydrocarbon reservoir is critically influenced by a good understanding of the distribution of litho- and organo-facies, porosity, geochemical and geomechanical properties of the reservoir layers. This, in turn, is primarily a function of both the vertical and lateral heterogeneity in the distribution and geochemical composition of soft organic-rich layers and more brittle organic-lean layers, taking in an account the regional assessment of the stress regime, heatflow and thermal conductivity. The proposed study will help to conduct a detailed assessment on a production scale of depositional and geochemical heterogeneities with unconventional development scenarios. The main aim of this research project is to describe and analyze the vertical and lateral heterogeneities of unconventional reservoirs through outcrop analogue investigations, in order to: 1. characterize the lateral and vertical changes in cyclicity and its impact on the occurrence, distribution and geochemical composition of organic-rich and organic-lean facies in a basinal setting; 2. provide based on the results of the fieldwork an assessment of possible variations in production behaviour of unconventional reservoirs in rocks of similar origin. The candidate will perform, along with fieldwork, a variety of microscopic and geochemical analyses on systematically collected sample from different outcrops exposing the Upper Cretaceous-Eocene Rocks of Jordan, which has a great potential as an unconventional reservoir.

BAS/1/1399-01-01

Geology, Carbonate Geology, Sedimentology, Stratigraphy, Unconventional Source Rocks, Facies Analysis

1. The project will form a Masters Thesis of the proposed student. 2. The results will published in peer reviewed Journals. 3. The results will be presented in international conferences.

Energy Resources and Petroleum Engineering

Ali I. Al-Naimi Petroleum Engineering Research Center

Micritization under elevated temperature and pressure

Academic Program: Applied Mathematics and Computer Science

Pleistocene to Holocene sediment dynamics of the Al Wajh Bank slope (Red Sea)

Academic Program: Earth Science and Engineering

Expression, Purification, Characterization of Proteins for Biocatalysis

Academic Program: BioScience

Functionalization of Gas Vesicles

Academic Program: BioScience

Visible-light Photoredox Catalysis Transformations

Academic Program: Chemical Science

Tackling the challenges of OH-Laser Induced Fluorescence technique on detonation: numerical approach to improve experimental design

Academic Program: Mechanical Engineering

Context: Compared to classical constant volume or constant pressure thermodynamic cycles, the detonation regime of combustion could increase by 40% the efficiency of engines. In line with the Paris agreement, identifying more efficient combustion processes is one of the strategies to limit CO2 emissions that contribute to climate change. In parallel to its promising application to the energy production field, detonation studies have also regained interest for safety applications, due to the last nuclear accident in Fukushima. Thus, two aspects can be distinguished: for transportation, researchers are focused on obtaining and controlling a self-sustained detonation in a specific engine (PDE or RDE), while for industrial safety, researchers are focused on identifying the detonation limits and the quenching mechanism of detonation to prevent them. While the measurement of temperature and chemical species is of current practice in conventional combustion process (flames, engines, etc…), the experimental characterization of detonation relies on the determination of the detonation velocity, global pressure, and density gradient structure. These information are limited to validate numerical simulations and to be confident in the phenomenological comprehension extracted from it. While planar laser-induced fluorescence of hydroxyl radical (OH-PLIF) is a powerful technique to characterize reaction fronts, previous studies have shown significant limitations of this technique for detonation visualization. Not only restricted to reaction front visualization, this technique is also of interest as it can give access to 2-D temperature measurements in detonations

BAS/1/1396-01-01

Mechanical engineering, chemical engineering, aerospace engineering

First, the student will have to become familiar with the principle of the OH-PLIF technique and the particularities associated with its usage on detonations, which has high pressure and temperature variations, high-speed flow (up to 2000m/s), etc… Second, the sensitivity analysis of the fluorescence signal will be conducted to identify the most sensitive parameters of the PLIF signal. Third, optimal operating conditions (≠ maximizing the fluorescence signal) will be identified and tested experimentally. Due to both the strong non-linearities between the PLIF signal intensity and each parameter involved, machine-learning approaches may be used to facilitate the identification of the optimal operating conditions

Mechanical Engineering

Clean Combustion Research Center

Temperature of hydrogen-air detonations: measurements by 2-color planar laser induced fluorescence of the hydroxyl radical

Academic Program: Mechanical Engineering

Compared to classical constant volume or constant pressure thermodynamic cycles, the detonation regime of combustion could increase by 40% the efficiency of engines. For a long time restricted to military applications, due to the global energetic issue, the civil applications of detonations have received in increasing interest during the last decade. One of the main challenges in this research field is to obtain a self-sustained detonation for practical fuel-oxidizer mixtures (e.g. kerosene-air), in a setup with typical dimensions comparable to those of a commercial gas turbine. While the quantitative characterization of flames in terms of temperature and chemical species is of current practice, the experimental study of detonation properties is mainly restricted to the determination of the detonation velocity, global pressure, and density gradient structure. Information such as the temperature or density of hydroxyl radical fields in a detonation front have never been measured. However, to better understand the detonation mechanisms and to help in validating detonation models and numerical simulations, these data are crucial. Objectives: In this context, the main objective of the project is to adapt a non-intrusive thermometry technique broadly used in the combustion community, the 2-color planar laser induced fluorescence on OH, to the characterization of an H2 – air detonation. There are many challenges to obtain reliable temperature measurements of a detonation front, including single shot measurements, synchronization, spectroscopic properties of OH in the condition of the detonation front, etc.

Mechanical Engineering, Combustion, Fluid Mechanics

First, the student will learn the 2-color PLIF technique on OH in a well characterized configuration: a stable flat flame stabilized over a McKenna burner. During this preliminary step, the uncertainty of the measurements, averaged and single shot, will be characterized. Second, the system will be implemented on a 2D detonation test rig, equipped with optical access for laser diagnostics. One of the main challenges will be the synchronization of the PLIF system with the detonation front arrival in the measurement area. Indeed, the detonation front propagates at a speed of about 2000 m/s, and the jitter between two events in the arrival of the measurement area can be as large as 1 ms. Synchronization will require time of flight measurements and analysis of the detonation propagation front. Finally, post processing of the OH PLIF images will be performed in order to determine the temperature fields. Due to the complexity of the detonation setup and combined laser diagnostics, the experimental part of this study will be performed by two persons: the intern student and an experienced researcher (senior PhD student or post-doc).

Mechanical Engineering

Clean Combustion Research Center

Gradient compression for distributed training of machine learning models

Academic Program: Computer Science

Towards a Principled Understanding of Deep Learning

Academic Program: Computer Science

Federated Learning

Academic Program: Computer Science

Topics in Machine Learning and Optimization

Academic Program: Applied Mathematics and Computer Science

Nanovisualization

Academic Program: Computer Science

During the research internship students will learn about the nanovisualization technology which combines computer graphics and visualization for nano-structures in life sciences and biotechnology. Nanovisualization poses several new technological challenges that are not reflected in the state of the art computer graphics and 3D visualization as of today. The underlying domain requires new techniques for multi-scale, multi-instance, dense, three-dimensional models which we never subject of technological advances in 3D graphics before. These scenes are of gigantic sizes and unmatched complexity. Therefore the task in nanovisualization is to thoroughly revisit all technological aspects of rendering, visualization, navigation, user interaction, and modeling in order to offer algorithmic solutions that address new requirements associated with the nano and microscopic scales.Throughout their stay, students will be working in team with researchers on specific assignment for a particular scientific work or solving a technical challenge in the field of computer graphics and visualization. Nanovisualization is one of the key components in creating, studying, and understanding scale-wise small (but complex) systems. As such it will become a key technology in the upcoming industrial revolution that will be heavily associated with the nano scale.The benefit for the students is to get familiar with nanovisualization research field, which is worldwide uniquely offered at KAUST. They will be integrated in working on a very important problems so far untouched in graphics and visualization that are very relevant for many societal challenges from the health, food, and energy sectors.

computer science, applied mathematics, physics

ivan.viola@kaust.edu.sa

Nanovisualization

Students should work on an internship project and should implement a clearly specified task. It is expected that students are familiar with computer graphics and visualization and can document advanced skills in graphics programming

Computer Science

Computer, Electrical and Mathematical Sciences and Engineering