Events

Apr 4 - Apr 10, 2021

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  Discriminant Analysis and Support Vector Regression in High Dimensions: Sharp Performance Analysis and Optimal Designs

  Houssem Sifaou, Ph.D., Electrical and Computer Engineering

  Apr 8, 11:00 - 13:00

  KAUST

  Machine learning is emerging as a powerful tool to data science and is being applied in almost all subjects. In many applications, the number of features is comparable or even larger than the number of samples, and both grow large. This setting is usually named the high-dimensional regime. In this regime, new challenges and questions arise when it comes to the application of machine learning. In this work, we conduct a high-dimensional performance analysis of some popular classification and regression techniques. In a first part, discriminant analysis classifiers are considered. A major challenge towards the use of these classifiers in practice is that they depend on the inverse of covariance matrices that need to be estimated from training data. Several estimators for the inverse of the covariance matrices can be used. The most common ones are estimators based on the regularization approach. The main advantage of such estimators is their resilience to the sampling noise, making them suitable to high-dimensional settings. In this thesis, we propose new estimators that are shown to yield better performance.
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  Continuous-time optimal control on discrete spaces. Applications to inventory management in commerce and finance - Session 1

  Olivier Guéant, Professor, Applied Mathematics at Université Paris 1 Panthéon-Sorbonne, France

  Apr 6, 15:00 - 18:00

  KAUST

  This 6-hour course covers the theory of optimal control in the case of discrete spaces / graphs. In the first part, we present the dynamic programming principle and the resulting Bellman equations. Bellman equations, which turn out to be a system of backward ordinary differential equations (ODE), are then thoroughly studied: in addition to existence and uniqueness results obtained through classical ODE tools and comparison principles, the long-term behavior of optimal control problems is studied using comparison principles and semi-group tools. The second part of the course focuses on a special case of optimal control problems on graphs for which closed-form solutions can be derived. The link with inventory management problems will be presented in details (in particular the link with the resolution of the Avellaneda-Stoikov problem, a classical problem in finance).
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  Challenges of Differentially Private Empirical Risk Minimization

  Di Wang, Assistant Professor, Computer Science

  Apr 5, 12:00 - 13:00

  KAUST

  Recent research showed that most of the existing machine learning algorithms are vulnerable to various privacy attacks. An effective way for defending these attacks is to enforce differential privacy during the learning process. As a rigorous scheme for privacy preserving, Differential Privacy (DP) has now become a standard for private data analysis. Despite its rapid development in theory, DP's adoption to the machine learning community remains slow due to various challenges from the data, the privacy models and the learning tasks. In this talk, I will give a brief introduction on DP and use the Empirical Risk Minimization (ERM) problem as an example and show how to overcome these challenges in DP model. Particularly, I will first talk about how to overcome the high dimensionality challenge from the data for Sparse Linear Regression in the local DP (LDP) model. Then, I will discuss the challenge from the non-interactive LDP model and show a series of results to reduce the exponential sample complexity of ERM. Next, I will present techniques on achieving DP for ERM with non-convex loss functions. Finally, I will discuss some future research along these directions.
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  Blue LED material beyond Blue for Micro-LED Displays

  Kazuhiro Ohkawa, Professor, Electrical and Computer Engineering

  Apr 4, 12:00 - 13:00

  KAUST

  LED material Displays

  Energy is an indispensable part of our lives. We are challenging energy-saving novel light emitters and clean-energy generation systems at Energy Conversion Devices and Materials (ECO Devices) Laboratory at KAUST. The former is based on MOCVD technology, material science, and device technology. The latter is the nitride photocatalyst invented by Ohkawa. The development of highly-efficient InGaN-based blue LEDs was the topic of the 2014 Nobel Prize in Physics. InGaN-based green LEDs were realized after improving the quality of higher-In-content InGaN. The three primary colors in light are RGB. The current red LEDs are based on InGaP as the active region. If we realize red LEDs by InGaN, we can fabricate the monolithic RGB LEDs in a wafer. Such RGB integration will be a breakthrough for micro-LED displays that are the next generation after the OLED displays. In this seminar, the science of MOCVD, the growth of high-In-content InGaN, and the state-of-the-art InGaN-based red LEDs will be introduced.

Mar 28 - Apr 3, 2021

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  Safe autonomy with imperfect information

  Necmiye Ozay, Associate Professor, University of Michigan

  Apr 1, 22:00 - 22:45

  KAUST

  Featured Sessions

  RobotoKAUST safe autonomy invariance verification

  For more information please visit the website
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  Safe, Interaction-Aware Decision Making and Control for Robot Autonomy

  Marco Pavone, Associate Professor, Aeronautics and Astronautics, Stanford University

  Apr 1, 21:15 - 22:15

  KAUST

  Featured Sessions

  RobotoKAUST human-robot interactions decision making autonomous driving

  For more information please visit the website
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  Certification of Autonomous Vehicles: A Regulator-Oriented Approach

  Huan Xu, Assistant Professor, University of Maryland

  Apr 1, 20:30 - 21:15

  KAUST

  Featured Sessions

  RobotoKAUST Aerospace autonomy Certification regulations

  For more information please visit the website
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  Efficient Reachability for Safe Autonomous Systems: A Mixed Monotone Approach

  Sam Coogan, Assistant Professor, Georgia Institute of Technology

  Apr 1, 19:45 - 20:30

  KAUST

  Featured Sessions

  RobotoKAUST safe autonomy reachability invariance

  For more information please visit the website
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  The challenging path to creating fully autonomous and controllable microrobots

  Prof. Néstor O. Pérez-Arancibia, Autonomous Microrobotic Systems Laboratory, University of Southern California (USC)

  Apr 1, 18:45 - 19:30

  KAUST

  Featured Sessions

  RobotoKAUST microrobots autonomy Power Catalytic Artificial Muscles Flight Control Crawling Control

  For more information please visit the website
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  An Egocentric Wearable Camera for Assistive Technologies

  Mohammed Kutbi, Assistant Professor, Saudi Electronic University

  Apr 1, 18:00 - 18:45

  KAUST

  Featured Sessions

  RobotoKAUST Assistive Technology Egocentric Camera Wheelchair

  For more information please visit the website
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  Designing And Modelling Soft Active Artificial Muscles “Geometric and Material Nonlinearities”

  Marwa Eldiwiny, PhD Student, IEEE RAS Org

  Apr 1, 17:15 - 18:00

  KAUST

  Featured Sessions

  RobotoKAUST FEMSimulation SoftActiveMaterial Geometricandmaterial nonlinearities Controller design

  For more information please visit the website
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  The Robots are Coming – to your Farm

  Girish Chowdhary, Associate Professor, UIUC

  Apr 1, 16:15 - 17:00

  KAUST

  Featured Sessions

  RobotoKAUST robotics agriculture artificial intelligence

  For more information please visit the website
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  Wireless Magnetic Sensors to Empower the Next Technological Revolution

  Abdullah Almansouri, PhD Student, Electrical and Computer Engineering, KAUST

  Apr 1, 16:00 - 17:00

  KAUST

  The next technological revolution, Industry 4.0, is envisioned as a digitally connected ecosystem where machines and gadgets are driven by artificial intelligence. By 2025, more than 75 billion devices are projected to serve this revolution. Many of which are to be integrated into the fabrics of everyday life in the form of smart wireless sensors. Still, two major challenges should be addressed to realize truly wireless and wearable sensors. First, the sensors should be flexible and stretchable, allowing for comfortable wearing. Second, the electronics should scavenge the energy it requires entirely from the environment, thus, eliminating the need for batteries, which are bulky, create ecological problems, etc. By addressing these two challenges, this dissertation paves the way for truly wearable sensors.
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  On the Fundamental Challenges for Self-Driving Cars

  Emilio Frazzoli, Professor, Dynamic Systems and Control, ETH Zürich

  Apr 1, 15:30 - 16:15

  KAUST

  Featured Sessions

  RobotoKAUST autonomous vehicles Future Mobility

  For more information please visit the website
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  Distributed AI: Optimal algorithms for distributed stochastic non-convex optimization

  Usman A. Khan, Associate Professor, Tufts University

  Apr 1, 14:45 - 15:30

  KAUST

  Featured Sessions

  RobotoKAUST Multi-agent systems Nonconvex problems stochastic optimization

  For more information please visit the website
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  Swarms for People

  Sabine Hauert, Associate Professor, Bristol Robotics Laboratory, University of Bristol

  Apr 1, 14:00 - 14:45

  KAUST

  Featured Sessions

  RobotoKAUST

  For more information please visit the website
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  Levering AI for Unmanned Aerial Systems: Deployment Strategies

  Anis Koubaa, Professor, Prince Sultan University

  Apr 1, 13:15 - 14:00

  KAUST

  Featured Sessions

  RobotoKAUST

  For more information please visit the website
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  From one to many, coordination problems of multiple mobile robots

  Lucia Pallottino, Associate Professor, University of Pisa

  Apr 1, 12:30 - 13:15

  KAUST

  Featured Sessions

  RobotoKAUST

  For more information please visit the website
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  Waves Functional Materials - 2021-04-01

  Ying Wu, Professor, Applied Mathematics and Computational Sciences

  Apr 1, 12:00 - 13:00

  KAUST

  Wave functional materials are artificial materials that can control wave propagation as wish. In this talk, I will give a brief review on the progress of wave functional materials and reveal the secret behind the engineering of these materials to achieve desired properties. In particular, I will focus on our contributions on metamaterials and metasurfaces. I will introduce the development of effective medium, a powerful tool in modeling wave functional materials, followed by some illustrative examples demonstrating the intriguing properties, such as redirection, emission rate enhancement, wave steering and cloaking.
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  Multi-Robot Task Allocation Games in Dynamically Changing Environments with Application to Trash Collection

  Shinkyu Park, Assistant Professor, Electrical and Computer Engineering, KAUST

  Apr 1, 11:45 - 12:30

  KAUST

  Featured Sessions

  RobotoKAUST Multi-Robot Learning/Coordination Multi-Agent Decision Making game theory

  For more information please visit the website
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  Autonomous Vision-Based Navigation and Control for Robotic Space Objects

  Hesham Shageer, Assistant Professor, King Abdulaziz City for Science and Technology KACST

  Mar 31, 21:15 - 22:00

  KAUST

  Featured Sessions

  RobotoKAUST Autonomous Space Robotics Distributed Space Systems Navigation and Control Flying Robots

  For more information please visit the website
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  Optimization-Based Control of Autonomous Aerospace Systems

  Behcet Acikmese, Professor, William E. Boeing Department of Aeronautics and Astronautics, University of Washington, USA

  Mar 31, 20:30 - 21:15

  KAUST

  Featured Sessions

  RobotoKAUST

  For more information please visit the website
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  Xwing: the journey to deploying autonomous cargo aircraft

  Maxime Gariel, Chief Technology Officer, Xwing

  Mar 31, 19:45 - 20:30

  KAUST

  Featured Sessions

  RobotoKAUST autonomy automation Airspace Integration Xwing Cessna Caravan

  For more information please visit the website
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  Dynamic Explorations of a TiltWing Aircraft Transitioning from Conventional to Hovering Flight

  John Hauser, Professor, University of Colorado Boulder

  Mar 31, 19:00 - 19:45

  KAUST

  Featured Sessions

  RobotoKAUST Aircraft Maneuvering Slipstream Dynamic Pressure Distributed Electric Propulsion Nonlinear Maneuvering

  For more information please visit the website
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  Safe learning and control with L1 adaptation

  Naira Hovakimyan, Professor, Mechanical Science and Engineering, University of Illinois

  Mar 31, 18:15 - 19:00

  KAUST

  Featured Sessions

  RobotoKAUST

  For more information please visit the website
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  Core Challenges in Navigation in Human Environments

  Jean Oh, Senior Systems Scientist, Robotics Institute, Carnegie Mellon University

  Mar 31, 16:30 - 17:15

  KAUST

  Featured Sessions

  RobotoKAUST Social robot navigation motion planning motion prediction human-robot interactions

  For more information please visit the website
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  Transient Analysis of Electromagnetic and Acoustic Scattering using Second-kind Surface Integral Equations

  Rui Chen, PhD Student, Electrical and Computer Engineering, KAUST

  Mar 31, 16:00 - 18:00

  KAUST

  Time-domain methods are preferred over their frequency-domain counterparts for solving acoustic and electromagnetic scattering problems since they can produce wide-band data from a single simulation. Among the time-domain methods, time-domain surface integral equation solvers have recently found widespread use because they offer several benefits over differential equation solvers. This dissertation develops several second-kind surface integral equation solvers for analyzing transient acoustic scattering from rigid and penetrable objects and transient electromagnetic scattering from perfect electrically conducting and dielectric objects. For acoustically rigid, perfect electrically conducting, and dielectric scatterers, fully explicit marching-on-in-time schemes are developed for solving time domain Kirchhoff, magnetic field, and scalar potential integral equations, respectively.
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  Toward Improving the Internet of Things: Quality of Service and Fault Tolerance Perspectives

  Maha Al-Aslani, PhD Student, Computer Science, KAUST

  Mar 31, 16:00 - 17:00

  KAUST

  In this thesis defense, I will explore the unique characteristics of IoT traffic and examine IoT systems. The work is motivated by the new capabilities offered by modern Software Defined Networks (SDN) and blockchain technology. We evaluate IoT Quality of Service (QoS) in traditional networking. We obtain mathematical expressions to calculate end-to-end delay, and dropping. Then, we analyze IoT traffic load and propose an intelligent edge that can identify volumetric traffic and address them in real-time using an instantaneous detection method for IoT applications (IDIoT). This approach can easily detect a large surge and potential variation in traffic patterns for an IoT application, which may contribute to safer and more efficient operation of the overall system. Our results provide insight into the advantages of an intelligent edge serving as a detection mechanism.
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  Human Robot Interaction with Natural Language Logic: a Step Closer

  Emmanuel Roche, PhD, CEO of Clover.AI

  Mar 31, 15:45 - 16:30

  KAUST

  Featured Sessions

  RobotoKAUST

  For more information please visit the website
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  Using drones, fluid lensing, and network analysis to get a more comprehensive view of coral reef mapping in the Red Sea

  Colleen Campbell, PhD Student, Red Sea Research Center, KAUST

  Mar 31, 14:15 - 15:00

  KAUST

  Featured Sessions

  RobotoKAUST

  For more information please visit the website
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  Trajectory planning in uncertain transient currents: a stochastic optimization approach

  Ricardo M. Lima, Research Scientist, CEMSE, KAUST

  Mar 31, 13:30 - 14:15

  KAUST

  Featured Sessions

  RobotoKAUST

  For more information please visit the website
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  Enhancing visibility for reliable underwater visual SLAM

  Ayoung Kim, Associate Professor, Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology (KAIST)

  Mar 31, 12:45 - 13:30

  KAUST

  Featured Sessions

  RobotoKAUST

  For more information please visit the website
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  Challenges in Marine Autonomy

  Stefan B. Williams, Head of School of Aerospace, Mechanical and Mechatronic Engineering, University of Sydney

  Mar 31, 12:00 - 12:45

  KAUST

  Featured Sessions

  Autonomous Underwater Vehicles Simultaneous Localisation and Mapping machine learning

  For more information please visit the website
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  Numerical Methods for Mean Field Games- Session 2

  Mathieu Laurière, Postdoc, Operations Research and Financial Engineering, Princeton University, USA

  Mar 30, 14:30 - 17:30

  KAUST

  Mean field games and mean field control problems are frameworks to study Nash equilibria or social optima in games with a continuum of agents. These problems can be used to approximate competitive or cooperative situations with a large finite number of agents, and have found a broad range of applications, from economics to crowd motion, energy production and risk management. The solutions are typically characterized by a forward-backward system of partial differential equations (PDE) or stochastic differential equations (SDE).
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  Multi-Scale GPU Resource Management for Deep Learning

  Mosharaf Chowdhury, Morris Wellman, Assistant Professor of CSE at the University of Michigan, Ann Arbor

  Mar 29, 18:30 - 19:30

  KAUST

  GPUs have emerged as a popular choice for deep learning. To deal with ever-growing datasets, it is also common to use multiple GPUs in parallel for distributed deep learning. Although achieving cost-effectiveness in these clusters relies on efficient sharing, modern GPU hardware, deep learning frameworks, and cluster managers are not designed for efficient, fine-grained sharing of GPU resources. In this talk, I will present our recent works on efficient GPU resource management, both within a single GPU and across many GPUs in a cluster for hyperparameter tuning, training, and inference. The common thread across all our works is leveraging the interplay between short-term predictability and long-term unpredictability of deep learning workloads
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  Towards Robust and Accurate Navigation: Theory, Applications, and Future Directions

  Tareq Al-Naffouri, Professor, Electrical and Computer Engineering

  Mar 28, 12:00 - 13:00

  KAUST

  Towards Robust Navigation theory Applications Future Directions

  Navigation is an essential requirement for many applications (commercial, retail, military, scientific, ...etc) and in a variety of environments (in-doors, outdoors, space, underwater, and even underground). In this talk, I will overview some of my group's work in localization and navigation focusing on indoor and satellite positioning. The talk will demonstrate how the structure or constraints of the problem can help achieve very accurate localization (e.g. millimeter level indoors) that is robust to Doppler, multipath, and shadowing. The talk will also touch upon various related applications that the group is pursuing in smart health and smart cities. The talk will end with future directions for localization in extreme environments and in the TeraHertz spectrum where localization, environment sensing, and communication converge.

Mar 21 - Mar 27, 2021

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  The Convex Gaussian Min-Max Theorem: A Powerful Tool for the Analysis of Regularized Convex Optimization Problems

  Tareq Al-Naffouri, Professor, Electrical and Computer Engineering

  Mar 25, 12:00 - 13:00

  KAUST

  In modern large-scale inference problems, the dimension of the signal to be estimated is comparable or even larger than the number of available observations. Yet the signal of interest lies in some low-dimensional structure, due to sparsity, low-rankness, finite alphabet, ... etc. Non-smooth regularized convex optimization are powerful tools for the recovery of such structured signals from noisy linear measurements. Research has shifted recently to the performance analysis of these optimization tools and optimal turning of their hyper-parameters in high dimensional settings. One powerful performance analysis framework is the Convex Gaussian Min-max Theorem (CGMT). The CGMT is based on Gaussian process methods and is a strong and tight version of the classical Gordon comparison inequality. In this talk, we review the CGMT and illustrate its application to the error analysis of some convex regularized optimization problems.
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  International Seminar on Mathematical Models and Numerical Methods for Flow and Transport in Porous Media

  Speakers from KAUST, CEMSE, PSE, G-CSC, IBRAE and INM RAS

  Mar 25, 10:30 - Mar 26, 17:00

  KAUST

  numerical methods Mathematical modeling flow problems porous media

  This workshop is devoted to numerical simulation of groundwater flow and subsurface contamination transport, as well as related problems. The main topics are mathematical modeling of the processes in porous media and the numerical methods for discretization, solution of the discretized systems and numerical treatment of inverse problems. In particular, fractured porous media and partially saturated aquifers will be concerned.
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  Numerical Methods for Mean Field Games - Session 1

  Mathieu Laurière, Postdoc, Operations Research and Financial Engineering, Princeton University, USA

  Mar 23, 14:30 - 17:30

  KAUST

  Mean field games and mean field control problems are frameworks to study Nash equilibria or social optima in games with a continuum of agents. These problems can be used to approximate competitive or cooperative situations with a large finite number of agents, and have found a broad range of applications, from economics to crowd motion, energy production and risk management. The solutions are typically characterized by a forward-backward system of partial differential equations (PDE) or stochastic differential equations (SDE)
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  Automated Reasoning in Systems Engineering

  Laura Kovacs, Professor in Computer Science at the TU Wien

  Mar 22, 12:00 - 13:00

  KAUST

  In this talk I will present recent advancement in automated reasoning, in particular computer-supported theorem proving, for generating and proving software properties that prevent programmers from introducing errors while making changes in this software. When testing programs manipulating the computer memory, our initial results show our work is able to prove that over 80% of test cases are guaranteed to have the expected behavior.
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  Minimal-time Mean Field Games

  Samer Dweik, Postdoctoral Fellow, University of British Columbia

  Mar 22, 11:00 - 12:00

  KAUST

  In this talk, we study a mean field game inspired by crowd motion in which agents evolve in a domain and want to reach its boundary minimizing their travel time. Interactions between agents occur through their dynamic, which depends on the distribution of all agents. First, we provide a Lagrangian formulation for our mean field game and prove existence of equilibria, which are shown to satisfy a MFG system. The main result, which relies on the semi-concavity of the value function of this optimal control problem, states that an L^p initial distribution of agents gives rise to an L^p distribution of agents at each time t>0.
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  Advancing Visual Intelligence via Neural System Design

  Hengshuang Zhao, Postdoctoral Fellow, Oxford University

  Mar 21, 12:00 - 13:00

  KAUST

  Visual Intelligence Neural System design

  Building intelligent visual systems is essential for the next generation of artificial intelligence systems. It is a fundamental tool for many disciplines and beneficial to various potential applications such as autonomous driving, robotics, surveillance, augmented reality, to name a few. An accurate and efficient intelligent visual system has a deep understanding of the scene, objects, and humans. It can automatically understand the surrounding scenes. In general, 2D images and 3D point clouds are the two most common data representations in our daily life. Designing powerful image understanding and point cloud processing systems are two pillars of visual intelligence, enabling the artificial intelligence systems to understand and interact with the current status of the environment automatically. In this talk, I will first present our efforts in designing modern neural systems for 2D image understanding, including high-accuracy and high-efficiency semantic parsing structures, and unified panoptic parsing architecture. Then, we go one step further to design neural systems for processing complex 3D scenes, including semantic-level and instance-level understanding. Further, we show our latest works for unified 2D-3D reasoning frameworks, which are fully based on self-attention mechanisms. In the end, the challenges, up-to-date progress, and promising future directions for building advanced intelligent visual systems will be discussed.

Mar 14 - Mar 20, 2021

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  Multicomponent flows: overview of the models and results on the existence of global in time solutions - Part 2

  Ewelina Zatorska, Senior Lecturer, Applied and Numerical Analysis, Imperial College London, UK

  Mar 18, 14:00 - 16:00

  KAUST

  In this lecture I will present broader spectrum of complex, multicomponent flows. For example, the models of compressible mixtures describe multicomponent fluids that are mixed on the molecular level. They are different from the models of the multi-phase flows from the first lecture, because there is no division of volume occupied by different species. The existence of global in time weak solutions, and global in time strong solutions for such systems will be explained, and some open problems related to singular limits and weak-strong uniqueness of solutions will be mentioned. At the end of the lecture I will also present another model of two-phase flow describing the motion of compressible and incompressible medium with an interphase given by a condition on the density. I will explain how to prove the existence of solutions and give some applications in modelling of crowd evacuation.
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  On Discovering Nature’s Equations from Observations

  Jesper Tegner, Professor, BESE Division, KAUST

  Mar 18, 12:00 - 13:00

  KAUST

  In essence, science is about discovering regularities in Nature. It turns out that such regularities (laws) are written in the language of mathematics. In many cases, such laws are formulated and refined from fundamental “first principles.” Yet, in phenomenological areas such as biology, we have an abundance of data but lack “first principles.” Machine learning and deep learning, in particular, are remarkably successful in classification and prediction tasks. However, such systems, when trained on data, do not, as a rule, provide compact mathematical laws or fundamental first principles. Here we ask how we can identify interpretable compact mathematical laws from complex data-sets when we don’t have access to first principles. I will give an overview of this problem and provide some vignettes of our ongoing work in attacking this problem.
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  Fully nonlinear degenerate elliptic equations: qualitative properties of viscosity solutions - Session 3

  Martino Bardi, Professor, Mathematical Sciences, University of Padova, Italy

  Mar 17, 15:00 - 17:00

  KAUST

  I will start recalling the definitions and basic properties of viscosity solutions to fully nonlinear degenerate elliptic equations, in particular the comparison principles. The main goal of the course is discussing two properties of subsolutions: the Strong Maximum Principle (SMP), i.e., if a subsolution in an open connected set attains an interior maximum then it is constant, and the Liouville property, i.e., if a subsolution in the whole space is bounded form above then it is constant. They are standard results for classical solutions of linear elliptic PDEs, and many extensions are known, especially for divergence form equations. My goal is explaining how the viscosity methods allow to turn around the difficulties of non-smooth solutions, fully nonlinear equations, and their possible degeneracies.
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  Mathematical Modeling and Analysis of Emergent Phenomena

  Jan Haskovec, Research Scientist, AMCS, KAUST

  Mar 15, 12:00 - 13:00

  KAUST

  Emergence of nontrivial patterns via collective actions of many individual entities is an ever-present phenomenon in physics, biology and social sciences. It has numerous applications in engineering, for instance, in swarm robotics. I shall demonstrate how tools from mathematical modeling and analysis help us gain understanding of fundamental principles and mechanisms of emergence. I will present my recent results in consensus formation and flocking models, focusing on the effects of noise and delay on their dynamics. Moreover, I will introduce continuum modeling framework for biological network formation, where emergence takes place through the interaction of structure and medium. The models are formulated in terms of ordinary, stochastic and partial differential equations. I shall explain how mathematical analysis of the respective models contributes to the understanding of how individual rules generate and influence the patterns observed on the global scale. A particular example from biology is development of leaf venation as a result of auxin-PIN interaction in the plant tissue. Here our model supported the hypothesis that a-priori polarization of auxin transport does not play a decisive role in leaf venation.
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  mm-Sized Wireless Implantable Medical Devices Toward Clinical Diagnostics and Therapeutics

  Pyungwoo Yeon, Postdoctoral Fellow, Electrical Engineering, Stanford University

  Mar 14, 16:00 - 17:00

  KAUST

  Implantable and wearable technologies are rapidly emerging and showing great promise in various medical therapeutics and diagnostics. These advances from health monitoring to therapeutic applications reorganize many aspects of daily life. Since the invention of the first implantable cardiac pacemaker for patients with arrhythmia in 1958, many implantable medical devices (IMDs) such as implantable cardioverter defibrillators (ICDs) and implantable deep brain stimulators (iDBSs) have been developed and have treated millions of patients. These IMDs eventually need wireless powering and communication for 1) eliminating transcutaneous power/data interconnects that elevate the risk of infection and 2) removing bulky batteries to avoid the risk of repeated surgical intervention. They also need small form factors and soft materials to mitigate tissue fibrosis due to foreign body responses. In this talk, I will introduce a new wireless neural interfacing tool within a cubic millimeter that can potentially record large scale neuronal ensembles over large brain area. The discussion will be focused on its building pieces across a wide range of science and engineering disciplines toward translating those into a complete clinically viable IMD. Also, I will present my recent research on RF-to-ultrasound power relay for powering deep mm-scale implants across air/tissue or tissue/skull media, and an all-soft and wireless pressure sensor tags that aim to address the issues of surgical complexity, tethering effect, and foreign body response. Finally, I will conclude the talk by presenting my future research plans toward clinically viable wireless medical diagnostics and therapeutics.

Mar 7 - Mar 13, 2021

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  Programming curvature into flat sheets

  Mar 11, 12:00 - 13:00

  KAUST

  Small-scale cut and fold patterns imposed on sheet material enable its morphing into three-dimensional shapes. This manufacturing paradigm has received much attention in recent years and poses challenges in both fabrication and computation. It is intimately connected with the interpretation of patterned sheets as mechanical metamaterials, typically of negative Poisson ratio. We discuss a fundamental geometric question, namely the targeted programming of a shape morph from a flat sheet to a curved surface, or even between any two shapes. The solution draws on differential geometry, discrete differential geometry, geometry processing and geometric optimization.
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  Fully nonlinear degenerate elliptic equations: qualitative properties of viscosity solutions - Session 2

  Martino Bardi, Professor, Mathematical Sciences, University of Padova, Italy

  Mar 10, 15:00 - 17:00

  KAUST

  I will start recalling the definitions and basic properties of viscosity solutions to fully nonlinear degenerate elliptic equations, in particular the comparison principles. The main goal of the course is discussing two properties of subsolutions: the Strong Maximum Principle (SMP), i.e., if a subsolution in an open connected set attains an interior maximum then it is constant, and the Liouville property, i.e., if a subsolution in the whole space is bounded form above then it is constant. They are standard results for classical solutions of linear elliptic PDEs, and many extensions are known, especially for divergence form equations. My goal is explaining how the viscosity methods allow to turn around the difficulties of non-smooth solutions, fully nonlinear equations, and their possible degeneracies.
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  Generation of Orbital Angular Momentum (OAM) Modes with Spiral Phase Plate Integrated Laser Source

  Edgars Stegenburgs, Ph.D. Student, Electrical and Computer Engineering

  Mar 10, 12:00 - 14:00

  KAUST

  The objective of this work is to develop a near-infrared laser device capable of emitting orbital angular momentum (OAM) light. The prototyped device must be suitable for compact, energy-saving optical communication applications. Integrated OAM lasers would revolutionize high capacity data transmission over any telecommunication network environment as OAM light can be guided and transmitted through kilometers of optical fibers as well as propagated in free space and underwater.