Willem Jan Tempelaar

If you want robots to understand soft materials, then you should at least be able to track their deformation accurately. Pretty fun what can be done with a mix of machine learning and standard contour tracking algorithms. In case you wonder, this is pure RGB, no RGB-D based. To be continued. #robotics #eindhoven

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Our next Life in Quantum talk will be by Joost van der Heijden Product Manager at Quantum Machines .    His talk is titled "Dynamic qubit stabilization with real-time noise surveillance."    Here is the abstract:  A significant part of research in the field of quantum processors is focused on mitigating noise, either by improving materials, developing noise decoupling schemes, or designing intrinsically noise-insensitive qubits. In this seminar, I will discuss an alternative approach in which the noise is continuously monitored and the qubit control signals are adjusted accordingly. Quantum Machines’ dedicated pulse processor has enabled, and greatly simplified, the implementation of such on-the-fly Hamiltonian estimation protocols with real-time feedback on the qubit control sequence. These dynamic stabilization algorithms have been successfully demonstrated on singlet-triplet spin qubits. With one of this qubit’s control axes entirely governed by noise, caused by a fluctuating nuclear spin bath, I will show how our protocol not only improves the qubit coherence but also enables the full two-axis and real-time control over the qubit. We meet on Thursday May 2nd at 3pm. It's in Auditorium M, and all are welcome. #seminar #quantumcomputing #qubitcontrol

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A peek inside art objects🔎💻 An X-ray scanner, some small metal balls, and a newly developed algorithm. That is all you need to make a 3D model that enables you to look inside art objects without dismantling them. Thanks to the research of Francien Bossema (Centrum Wiskunde & Informatica and Leiden Institute of Advanced Computer Science - LIACS), museums can now use existing X-ray equipment as CT scanners, without having to buy such a costly and complicated device. The picture shows an example of the scans that can be made using Bossema's method 🖼📸 Read more about Bossema’s research ➡ https://lnkd.in/eTqcJQkg #museums #algorithm #LeidenScience #LIACS #CWI

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𝐒4𝐈𝐒 – Simulation 4 Industrial Systems – has no more secrets for Stijn Degryse, Emile Steyaert and Alexander Loquet after an intensive expert day at Siemens. 💪 Exploring multiple tools, including SIMIT and PLCSIM Advanced, they learned how these enable full-blown virtual commissioning. Excited to see their new skills come to life in upcoming projects for improved efficiency and #LessStress! 💡 #VirtualCommissioning #S4IS #DigitalTwin

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"" "This principle offers a new approach to SLOW DOWN LIGHT FIELDS and thereby ENHANCE their STRENGTH. Realizing this on a chip is particularly important for many applications," says AMOLF-group leader Ewold Verhagen. The researchers have published their findings in the journal Nature Photonics. Simultaneously, a research team from Pennsylvania State University has published an article in the SAME JOURNAL about how they demonstrated—INDEPENDANTLY from the Dutch team—an IDENTICAL EFFECT. Manipulating the flow of light in a material at small scales is beneficial for the development of nanophotonic chips. For electrons, such manipulation can be realized using magnetic fields; the LORENTZ FORCE steers the MOTION of ELECTRONS. However, this is IMPOSSIBLE for PHOTONS because they do not have charge. Researchers in the Photonic Forces group at AMOLF are looking for techniques and materials that would enable them to apply forces to photons that resemble the effects of magnetic fields. Electrons "We looked for inspiration at the way in which ELECTRONS behave in materials. In a conductor, electrons can in principle move FREELY, but an external magnetic field can stop this. The CIRCULAR movement caused by the MAGNETIC field conduction and as such ELECTRONS can only exist in the material if they have very SPECIFIC ENERGIES. These energy levels are called LANDAU levels, and they are characteristic for ELECTRONS in a MAGNETIC FIELD," says Verhagen. "But, in the two-dimensional material graphene—that consists of a single layer of CARBON ATOMS arranged in a CRYSTAL—these Landau levels can also be caused by a DIFFERENT mechanism than a magnetic field. In general, graphene is a good electronic conductor, but this changes when the crystal array is deformed, for instance by STRETCHING it like ELASTICS. "Such mechanical DEFORMATION STOPS CONDUCTING; the material turns into an insulator and consequently the electrons are bound to Landau levels. Hence, the deformation of graphene has a SIMILAR EFFECT on electrons in a MATERIAL as a MAGNETIC FIELD, even WITHOUT a MAGNET. We asked ourselves if a similar approach would also work for photons." "" ----- I can't believe it. They found it.... It's real?!!??? Magnetic fields evolve due to their relationship with electrons... My theory is literally Electron Magneto hydro dynamics, with Cylindrical Vortex/Vortical ring effects. The rings are able to resonate with each other when they are together. The specific frequencies is the RESONANCE frequency and directly connected to logarithmic/Fibonacci spirals. The zeta sequence are the fractions aka electromagnetic fractals that oscillate and grow, aka crystalline springularities I call then. The stretching is where torsion comes from, and supermassive black holes are Mobius strips where magnetic fields, like a magnetic disc in a hard drive. Voyager space craft just started transmitting normally again. It stopped in Nov when I had a revelation, and it started last week

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🛩️✨ Exciting update from my recent experiment at TU Delft! ✨🛩️ I'm thrilled to share some insights from a Particle Image Velocimetry (PIV) experiment I conducted at TU Delft, focusing on the aerodynamics of an airfoil at a 30º angle of attack. 🚀 🔬 We delved into the intricate flow patterns around the airfoil using advanced PIV techniques. PIV works by seeding the airflow with tiny particles and then using high-speed cameras to capture images of these particles as they move with the flow. By analyzing the displacement of particles between consecutive images, we can precisely map the velocity field around the airfoil. 📈 Our investigation uncovered intriguing insights into the aerodynamics of the airfoil at a 30º angle of attack. One notable discovery (and expected under this conditions) was the presence of unsteady interactions in the stall region. These unsteady phenomena play a crucial role in understanding the aerodynamic performance of the airfoil, especially during critical flight conditions. Further analysis of these interactions could enhance our understanding of very high angle of attack stall behavior and inform the design of more efficient airfoil profiles. Excited to share these findings and continue exploring the fascinating world of aerodynamics! 🚀✈️💨 #Aerodynamics #PIVExperiment #TU Delft #Research #Science #Engineering

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"Moore’s Law holds that the number of transistors on an integrated circuit doubles every two years or so. In essence, it means that chipmakers are always trying to shrink the #transistors on a #microchip in order to pack more of them in. The cadence has been increasingly hard to maintain now that transistor dimensions measure in a few #nanometers. In recent years ASML’s machines have kept #Moore’s Law from sputtering out. Today, they are the only ones in the world capable of producing circuitry at the density needed to keep #chipmakers roughly on track. It is the premise of Moore’s Law itself, Martin van den Brink said, that drives the industry forward, year after year. " https://lnkd.in/eXJQzVkf

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During my time at TU Delft as a graduate student, I specialized in image super-resolution research, focusing on enhancing MRI images for medical applications. This experience broadened my perspective on the potential applications of AI beyond predictive tasks. Transitioning from medical imaging to gaming, I was intrigued to find that techniques similar to those in my thesis were being employed in gaming graphics optimization by companies like AMD and NVIDIA. The convergence of AI-driven super-resolution techniques with gaming graphics optimization has revolutionized the gaming industry, particularly with the rise of handheld gaming consoles. Technologies like AMD's FidelityFX Super Resolution and NVIDIA's DLSS have been refined to deliver immersive gaming experiences without overtaxing hardware resources. This represents a significant advancement in overcoming hardware limitations to provide seamless, visually captivating gaming experiences. Overall, the utilization of AI in super-resolution techniques not only enhances gaming experiences but also showcases the transformative potential of AI across various sectors. As AI continues to evolve and become more widespread, it promises to revolutionize our collective experiences, transcending previous constraints imposed by hardware limitations. Images credit: https://lnkd.in/gmMKfVXj

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🎯Showcases for the industry with @Flanders Make at Advanced Engineering 2024! 🎯   Are you ready to dive into the latest technological advancements? Join us at ‘Showcases for the Industry’ on May 16 at Antwerp Expo.   During this free event, I will host a session about ‘Executable digital twins to measure to unmeasurable’ together with Daniel De Gregoriis.   Here, you will learn more about the Executable Digital Twin (xDT) to measure the unmeasurable. An xDT integrates the virtual with the real world, offering self-contained and adaptable virtual representations synced with real systems. The xDT can be embedded and deployed on these real systems, allowing for a seamless integration and vital engineering insights like stress distributions and operational loads. The xDT allows to replace costly and intrusive sensor setups with model-based estimation algorithms and therefore enables measuring the unmeasurable.   Register now and don't miss out via https://lnkd.in/eGq4H_yf   #AdvancedEngineering #Innovation #FlandersMake #Manufacturing #Technology #AE2024

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Besides my work at KPN through NAVARA, I like to work on my aerospace engineering research for the Delft University of Technology in my spare time. If you're curious about what my research is about, you're in luck, because some of the work I've done in collaboration with professor Marcias Martinez of Clarkson University just got published (open access, so anyone can read it) in the journal Sensors MDPI: https://lnkd.in/esV7S3gT

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🚀 Warehouse Automation Like Never Before! 🚀 I've never seen unloading like this and I'm curious what you think about Dextrous Robotics approach to logistics challenges. It's definitely an intriguing concept and I'd love to see how it performs in a real-world application. Insight into the solution: They managed 150 boxes per hour in a simulated container unloading scenario. They claim speeds of up to 900 boxes per hour. 🏎️💨 This solution is suitable for logistical operations, ensuring adaptability to customer needs. Precise and efficient, this solution addresses staffing and ergonomic issues. 🛠️ Credit: Dextrous Robotics But would it handle real-world conditions outside the lab? 🤔

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Curious about how our robotics solutions contribute to our 'From Silo to Truck' philosophy? In this article our Sales Manager Handling & Robotics, Thijs Meijnen, shares insights on the latest innovations and solutions that enhance efficiency, sustainability, and flexibility in the bakery process. Want to know more? Read the full article in Vaktijdschrift NBT Magazine. #RoyalKaak #Robotics #NBTMagazine #Innovation #Sustainability

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Bloomberg is part of what we like to refer to as MIMAC. “The West has lots of state-financed and state-influenced media, but it usually calls them "free" and other countries' media "state media," which is meant negatively. In the Military-Industrial-Media-Academic Complex, also known as MIMAC, the Media has become more important lately due to the explosion and globalization of media types and communication.” https://lnkd.in/emiK8C2H A core issue here is the role of the I in this acronym. Is ASML an active player in the (futile) attempts to keep China technologically backwards, or is it a victim, suffering from it.

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Researchers use ChatGPT to make a tomato picking robot A team of researchers at the Technical University in Delft, Netherlands and the Swiss technical university EPFL used ChatGPT to help them develop a tomato-picking robot. A study about the development of the robot was recently published in Nature Machine Intelligence.  ChatGPT played an essential role in the development process from the very beginning. To decide what kind of robot they should create, researchers asked ChatGPT questions about what the greatest challenges for humanity would be in the future, which led them to focus on issues with the food supply. The team picked tomatoes because ChatGPT taught them that tomatoes would be one of the most economically valuable to automate.  “We wanted ChatGPT to design not just a robot, but one that is actually useful,” Dr. Cosimo Della Santina, an assistant professor at TU Delft, said. During the design process, ChatGPT gave the team helpful suggestions, like making a gripper out of silicone or rubber so that robot doesn’t crush tomatoes, or using a Dynamixel motor to drive the robot. With ChatGPT handling much of the research for the robot, the engineering team found themselves performing more technical tasks to validate the AI’s knowledge.  In this way, the large language model, ChatGPT, acted as the researcher and engineer in the development process, and the human researchers acted as the manager, making them in charge of specifying the design objectives.  This is a less intense collaboration than the most extreme ChatGPT-collaboration scenario that the team came up with, where the language model provides all of the input to the robot design, and human engineers blindly follow it.  An extreme scenario like that isn’t currently possible, and the team behind this experiment doesn’t know if it will ever be realistic. In part, because working with large language models leaves companies commercializing robots with questions about plagiarism and intellectual property, and because large language models provide unverified information.  “In fact, LLM output can be misleading if it is not verified or validated. AI bots are designed to generate the ‘most probable’ answer to a question, so there is a risk of misinformation and bias in the robotic field,” Della Santina said. Even ChatGPT’s determination that tomatoes would be the most economically valuable crops to work with could be biased towards crops that are more covered in the data ChatGPT uses to make decisions.  Despite these concerns, the research team will continue to use the tomato-harvesting robot in their research and will continue to study the capabilities of large language models like ChatGPT. 

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For the past three years, my Ph.D. research has focused on robotic bilateral teleoperation. What once seemed like a distant future has now become our reality. Looking ahead, I anticipate that the next phase will be to consider the robotic body as an extension of ourselves. Key elements such as haptic feedback, tactile sensing, reduced communication latency, and the ability to learn how to learn like humans will be our journey. And what comes next? Perhaps verbal communication, decision generation, or even the decentralization of intelligence? The possibilities are wide open.

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collaboration is the key

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Exciting News! I recently defended my thesis and earned a 9, marking the final step in my Master’s degree. My research focused on the positive effects of adversarial training, and you can learn more by checking out the linked post below.I want to thank everybody who supported my on this journey. After four years studying computer science and two years delving into data science and AI, I am now exploring new opportunities. If you're aware of any exciting roles in #DataScience, #AI, or #MachineLearning, I'd love to connect and discuss the possibilities!

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“How can one avoid despondency if one thinks of the anomalous Zeeman effect” (W. Pauli) One of the biggest challenges in the early stages of atom physics. So simple in its phenomenology, yet it took so much effort from some of the brightest minds in the whole mankind to get to the real substance of it, to answer the Aristotelian “τί εστί; “ question. From my humble point of view, the beauty of natural science stands all here.

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On Wednesday July 10 at 4 p.m., Quinten Beirinckx from our Department of Physics and supervised by Jan Sijbers, Arnold J. den Dekker & Marleen Verhoye will publicly defend the PhD thesis "Technological breakthroughs towards motion-robust super-resolution quantitative magnetic resonance imaging for improved detection of brain diseases" at Campus Drie Eiken, Promotion aula Q.002. Everyone is cordially invited to attend this public defense. Magnetic resonance imaging (MRI) is one of the most widely used neuroimaging techniques, thanks to its exceptional soft tissue contrast and intrinsic safety for patients. Unfortunately, signal intensities in conventional MRI images are expressed in relative units that depend on scanner hardware and software. While this poses no issue for visual inspection of anatomy, it complicates the quantitative comparison of signal intensities within a scan, between successive scans, and among different subjects. In contrast, quantitative MRI (qMRI) generates quantitative maps of absolute biophysical tissue parameters by voxel-wise fitting a biophysical signal model to a series of contrast-weighted scans. Increasing evidence suggests that qMRI can detect and quantify subtle microscopic tissue damage, aiding in the early detection and accurate diagnosis of various neurodegenerative diseases such as Alzheimer's or multiple sclerosis. The impact of these diseases is growing in our rapidly aging society. However, current qMRI techniques require long scan times due to the need for multiple contrast-weighted scans with high-resolution and high signal-to-noise ratio (SNR). Long scan times increase the risk of motion artifacts, reduce patient throughput, and decrease patient comfort, hindering clinical adoption of qMRI. ​ ​ This work investigates model-based super-resolution reconstruction (SRR) for qMRI, to optimize the trade-off between spatial resolution, SNR, and scan time. SRR enables the reconstruction of a high-resolution scan or parameter map from a series of low-resolution MRI scans. As an additional innovation in this thesis, patient movement is jointly estimated, which is crucial to avoid motion artifacts in the reconstruction. The new SRR framework is extensively tested and compared with existing SRR methods, both in computer simulations and using real brain MRI data. Furthermore, the new framework uses Bayesian statistics to incorporate prior knowledge about noise and brain tissue characteristics into the reconstruction process. This allows for the reconstruction of a 3D high-resolution quantitative tissue parameter map from motion-affected low-resolution MRI scans. Application to real brain MRI shows that the proposed framework significantly improves the accuracy of tissue parameter quantification compared to methods using a separate motion correction step. Finally, the SRR framework is extended to perfusion MRI for improved quantification of cerebral blood flow (CBF), in combination with Arterial Spin Labeling (ASL).

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