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I will first discuss the particular requirements for intra-operative imaging and visualization. I will then present some of our latest results in intra-operative multimodal robotic imaging and its translation to clinical applications. I will then discuss the impact of research advancement in machine learning on medical imaging and computer assisted intervention. I will finally present some applications of virtual and augmented reality in the medical domain.

Starting by the current deployment of AR and VR technology within medical education, I discuss its current and future impact on surgical education and training. I will then review the first deployment of augmented reality into operating rooms in the last two decades and present some of our latest achievements in this field see also: www. Deep learning algorithms offer a powerful means to automatically analyze the content of biomedical images.

However, many biological samples of interest are difficult to resolve with a standard optical microscope. Either they are too large to fit within the microscope's field-of-view, or too thick, or are quickly moving around. In this talk, I will discuss our recent work in addressing these challenges by using deep learning algorithms to design new experimental strategies for microscopic imaging. Specifically, we use deep neural networks to jointly optimize the physical parameters of our computational microscopes - their illumination settings, lens layouts and data transfer pipelines, for example - for specific tasks.

Handbooks are an essential requirement for understanding and using many artifacts found in our daily life.

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We use handbooks to understand how things work and how to maintain them. Most handbooks still exist on paper relying on graphical illustrations and accompanying textual explanations to convey the relevant information to the reader. With the success of video sharing platforms a large body of video tutorials available for nearly every aspect of life became available. Video tutorials can often expand printed handbooks with the demonstrations of actions required to solve certain tasks. However, interpreting printed manuals and video tutorials often requires a certain mental effort since users have to match printed images or video frames with the physical object in their environment.

Augmented Reality AR has been demonstrated to be effective of presenting information traditionally provided in printed handbooks and video tutorials.

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However, creating interactive illustrative graphics for AR is costly and requires specially trained authors. In this this talk, I will present research towards the automation of the authoring process of AR handbooks by interactively retargeting conventional, two-dimensional image and video data into three-dimensional AR handbooks. In addition, I will present interaction, visualization and rendering techniques tailored for AR handbooks.

Claude Shannon was an American mathematician, electrical engineer, and cryptographer known as "the father of information theory". Shannon founded information theory and is perhaps equally well known for founding both digital computer and digital circuit design theory. Shannon also laid the foundations of cryptography and did basic work on code breaking and secure telecommunications. Many network middleboxes perform deep packet inspection DPI , a set of useful tasks which examine packet payloads.

These tasks include intrusion detection IDS , exfiltration detection, and parental filtering. However, a long-standing issue is that once packets are sent over HTTPS, middleboxes can no longer accomplish their tasks because the payloads are encrypted. Hence, one is faced with the choice of only one of two desirable properties: the functionality of middleboxes and the privacy of encryption. We propose BlindBox, the first system that simultaneously provides both of these properties.

The approach of BlindBox is to perform the deep-packet inspection directly on the encrypted traffic.

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BlindBox realizes this approach through a new protocol and new encryption schemes. We demonstrate that BlindBox enables applications such as IDS, exfiltration detection and parental filtering, and supports real rulesets from both open-source and industrial DPI systems. Moreover, its core encryption scheme is orders of magnitude faster than existing relevant cryptographic schemes. Indoor localization holds great promise to enable applications like location-based advertising, indoor navigation, inventory monitoring and management. SpotFi is an accurate indoor localization system that can be deployed on commodity WiFi infrastructure.

SpotFi only uses information that is already exposed by WiFi chips and does not require any hardware or firmware changes, yet achieves the same accuracy as state-of-the-art localization systems. We then talk about BackFi, a novel communication system that enables high throughput, long range communication between very low power backscatter IoT sensors and WiFi APs using ambient WiFi transmissions as the excitation signal.

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We show via prototypes and experiments that it is possible to achieve communication rates of up to 5 Mbps at a range of 1 m and 1 Mbps at a range of 5 meters. Such performance is an order to three orders of magnitude better than the best known prior WiFi backscatter system. Given a large cohort of "similar" cases Z1,. This raises some fundamental questions: when not to borrow? This paper establishes the first analytical formula for optimal nonlinear shrinkage of largedimensional covariance matrices.

We further show how to use conditional independence structure to speed up computations. Rapid and precise measurements are and always have been of interest in science and technology partly because of their numerous practical applications. Since their development, frequency comb-based methods have revolutionized optical measurements.

They simultaneously provide high resolution, high sensitivity, and rapid acquisition times.


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These methods are being developed for use in many fields, from atomic and molecular spectroscopy, to precision metrology, to spectral LIDAR and even atmospheric monitoring. However they cannot address the issues of inhomogeneously broadened transitions or sample heterogeneity. This is especially important for remote chemical sensing applications.

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In this talk I will discuss a novel optical method, that I recently developed, which overcomes these limitations. I will demonstrate its capabilities for probing extremely weak fundamental processes as well as its applications for rapid and high resolution chemical sensing. Lomsadze, B. Smith and S. Nature Photonics 12, , Lomsadze and S. Science , , B. Optics letters 42, , Buildings account for the largest share of U. Clearly, any program to greatly reduce greenhouse gas emissions must include buildings.

This talk will explore the opportunities and challenges to greatly reducing greenhouse gas emissions in the building sector, using as a case study a recent solar retrofit of an existing house that rendered it "zero-carbon. Inspired by the success of the first TPU for neural network inference, Google developed multiple generations of machine learning supercomputers for neural network training that allow near linear scaling of ML workloads running on TPUv2 and TPUv3 processors. TPUs extend research frontiers and benefit a growing number of Google services. The parent company, Acorn, was down a very dark financial alley, and the remnants of the design team were cast out to fend for themselves, equipped with about 18 months of financial rations from Apple, and a really rather odd microprocessor design.

When Dave Jaggar joined ARM a few months later, with the ink not quite dry on his Master's Thesis, he thought perhaps he'd made a dreadful mistake. Over the next 8 years he worked out a little bit about computer architecture, in the same way that a 17th century surgeon understands anatomy, then he was made the first ARM Fellow, so he promptly retired back to New Zealand to raise his children. As it's the 25th anniversary of his quite successful Thumb compressed instruction set, and his children have all left home, he's been told it's about time he explained himself.


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The current electronics industry has been completely dominated by Si-based devices due to its exceptionally low materials cost. Unfortunately, the extremely high cost of non-Si semiconductor materials prohibits the progress in this field. These single-crystalline films are easily released from the slippery graphene surface and the graphene-coated substrates can be infinitely reused to generate single-crystalline films. Thus, the remote epitaxy technique can cost-efficiently produce freestanding single-crystalline films. This allows unprecedented functionality of flexible device functionality required for current ubiquitous electronics.

In addition, we have recently demonstrated a manufacturing method to manipulate wafer-scale 2D materials with atomic precision to form monolayer-by-monolayer stacks of wafer-scale 2D material heterostructures [3]. Lastly, I will discuss about an ultimate alternative computing solution that does not follow the conventional von Neuman method. As Moore's law approaches its physical limits, brain-inspired neuromorphic computing has recently emerged as a promising alternative because of its compatibility with AI.

In the neuromorphic computing system, resistive random access memory RRAM can be used as an artificial synapse for weight elements in neural network algorithms. RRAM typically utilizes a defective amorphous solid as a switching medium. However, due to the random nature of amorphous phase, it has been challenging to precisely control weights in artificial synapses, thus resulting in poor learning accuracy. Our team recently demonstrated single-crystalline-based artificial synapses that show precise control of synaptic weights, promising superior online learning accuracy of I will discuss about how we design the materials and devices for this new neuromorphic hardware.

Further scaling of complementary metal-oxide-semiconductor CMOS dimensions will soon lead to a tremendous rise in power consumption while limited gain in the performance of integrated circuits. In this talk, I will present nanoscale electronic and photonic devices based on two-dimensional 2D materials and ferroelectric materials. In particular, I will discuss the logic devices, RF devices, photodetectors, plasmonic devices, and tunneling devices based on graphene and transition metal dichalcogenides.

I will also present our recent results on non-volatile memories and ferroelectric tunneling junctions FTJs based on ferroelectric hafnium oxide and 2D ferroelectric indium selenides. The field of AI was motivated originally by the objective of automating tasks performed by humans. While advances in machine learning have enabled impressive capabilities such as self-driving vehicles, more cognitive tasks such as planning and design have resisted full automation because of the vast amounts of knowledge and commonsense reasoning that they require.

This talk describes a line of research aimed at developing AI systems that are designed to augment rather than replace human capabilities, leveraging automated planning, machine learning, and natural language understanding technologies. It also presents several successful applications of the research in deployed systems. From the beginning of recording history, mapping the world has been critical to human growth and exploration.

Today, mapping the world in 3D is equally critical to the future of AR and how we all will experience the world around us. To usher Solar 2.

This talk is divided in three parts. The first part discusses the system's and project relevant metrics which constitute the bottom line for customers. It also sets the stage for the importance of a multi-dimensional advancement of solar module technology as apposed to conventional incremental improvements in cost and efficiency areas only.

The second part discusses Solar 1.

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The final part of the talk delves into potential disruptive ideas both related to dramatic efficiency improvement and system's level smartness, which will drive the next wave in advancement, the Solar 2. Quantum computing holds the promise to transform many industries, by rendering some of todays intractable problems feasible. To do so, quantum computers are built upon fundamentally different rules from standard computers, harnessing the bizarre but beautiful quantum mechanical laws that underpin the behavior of atoms and molecules. This will transform cryptography, material and chemical design, among other key areas.

I will attempt to demystify some key aspects of quantum computing, highlight some of the key industrial applications, and will outline Microsoft's full-stack approach to overcome the challenges to build scalable quantum computers. Skip to: Skip to content Skip to navigation. EE Electrical Engineering.