Memorial Day holiday, no classes.
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Updates will be posted on this page, as well as emailed to the EE student mail list.
As always, use your best judgement and consider your own and others' well-being at all times.
Memorial Day holiday, no classes.
- Evan, Peter, and the GSEE
Creating realistic virtual humans has traditionally been considered a research problem in Computer Animation primarily for entertainment applications. With the recent breakthrough in collaborative robots and deep reinforcement learning, accurately modeling human movements and behaviors has become a common challenge also faced by researchers in robotics and artificial intelligence. In this talk, I will first discuss our recent work on developing efficient computational tools for simulating and controlling human movements. By learning a differentiable kinematic constraints from the real world human motion data, we enable existing multi-body physics engines to simulate more humanlike motion. In a similar vein, we learn task-agnostic boundary conditions and energy functions from anatomically realistic neuromuscular models, effectively defining a new action space better reflecting the physiological constraints of the human body. The second part of the talk will focus on two different yet highly relevant problems: how to teach robots to move like humans and how to teach robots to interact with humans. While Computer Animation research has shown that it is possible to teach a virtual human to mimic real athletes' movements, the current techniques still struggle to reliably transfer a basic locomotion control policy to robot hardware in the real world. We developed a series of sim-to-real transfer methods to address the intertwined issue of system identification and policy learning for challenging locomotion tasks. Finally, I will showcase our effort on teaching robot to physically interact with humans in the scenarios of robot-assisted dressing and walking assistance.
Every Friday, Zoom link available upon request via eamil to firstname.lastname@example.org.
SEE YOU THERE!
In linear optical quantum computing qubits do not fundamentally interact, and yet via measurement complex entanglement can be constructed to implement quantum error corrected computation via topological codes. As a hardware platform for quantum computation linear optics offers unique flexibility in the options for building up topological error correcting schemes. Some interesting examples are the long range connectivity which is straightforward in a photonic architecture, and the ability to move qubits around in temporal as well as spatial dimensions. I will give an overview of quantum computing with silicon photonics and demonstrate how these physical features of the photonic approach can inspire novel schemes for fault tolerance.
Particle accelerators represent an indispensable tool in science, healthcare, and industry. However, the size and cost of conventional radio-frequency accelerators limits the utility and reach of this technology. Dielectric laser accelerators (DLAs) provide a compact and cost-effective solution to this problem by driving accelerator nanostructures with visible or near-infrared (NIR) pulsed lasers, resulting in a factor of 10,000x reduction in scale. Current implementations of DLAs rely on free-space lasers directly incident on the accelerating structures, limiting the scalability of this technology due to the need of bulky optics and precise mechanical alignment. Therefore, integration with an inherently scalable architecture, such as photonic integrated circuits, is paramount to the development of an MeV-scale DLA for applications.
In this talk, I will present the demonstration of a waveguide-integrated DLA, designed using a photonic inverse design approach. I will first review the operation of DLAs and describe how one can formulate a figure-of-merit for the optimization of these structures. I will then briefly introduce the inverse design framework that allows for efficient free-form optimization of these structures, enabling search of a design-space that goes far beyond that of the tuning of a few geometric parameters. I will discuss the approaches we take to couple light to these devices before presenting the results of our single-stage on-chip integrated accelerator. I will conclude with the directions we are taking to reach higher on-chip acceleration gradients and energy-gain, including utilizing foundry fabrication for multi-stage accelerators.
Over the past few decades, silicon photonics has revolutionized photonic integrated circuits by leveraging the semiconductor CMOS manufacturing infrastructure for low cost, high performance devices and systems. However, key fundamental challenges of the field remain unsolved: packaging the devices with optical fibers and generating light on chip.
We developed a novel approach for fiber packaging based on fusing the fiber and chip together. Connecting a silicon photonic chip across long distances requires attaching optical fibers to the chip. In practice, the packaging of optical fibers to photonic devices is time consuming, lossy, and expensive. This process is usually done by gluing the fiber and chip together using optical adhesives. By fusion splicing the chip and fiber together we have demonstrated losses as low as 1dB for single fibers and 2.5dB for an array of four fibers.
Imagine a laser as thick as an atom that is compatible with silicon photonics. Silicon based materials are passive. Since silicon is an indirect band gap material it is a poor light emitter. To generate light on a silicon photonic integrated circuit, you need to integrate active materials, which are usually not compatible with CMOS, with the device. Two-dimensional materials are excellent candidates for light sources, modulators, and detectors; and they are compatible with CMOS electronic manufacturing in the back end. We recently demonstrated the first fully on-chip 2D laser. Due to their thickness and transfer process, we envision electronic-photonic devices with many optical layers, each with their own lasers, modulators, and detectors based on 2D materials. Our recent demonstration completes the set of active devices completely based on 2D materials.
Understanding the neural basis of brain function and dysfunction requires developing multimodal methods to record and stimulate neural activity in the brain with high spatiotemporal resolution. We have been designing high-density opto-electrical devices to enable bi-directional (read/write) interfacing with the brain for long-term chronic studies.
One of the challenges of optical techniques for structural and functional recording and imaging is the scattering and absorption of light, limiting light-based methods to superficial layers of tissue. To overcome this challenge, implantable photonic waveguides such as optical fibers or graded-index (GRIN) lenses have been used. The prohibitive size and rigidity of these optical implants cause damage to the brain tissue and vasculature. In this talk, I will discuss our research on developing next generation optical neural interfaces that are microfabricated on flexible materials to minimize damage to the tissue.
First, I will discuss a compact flexible photonic platform based on biocompatible polymers, Parylene C and PDMS, for high-resolution light delivery into the tissue in a minimally-invasive way. This photonic platform can be monolithically integrated with implantable electrical neural interfaces.
I will also discuss our recent work on developing a novel complementary method for confining and steering light in the tissue using ultrasound. I will show that ultrasound waves can sculpt virtual optical waveguides in the tissue to define and steer the trajectory of light, thus obviating the need for implanting invasive physical devices in the brain.
These novel neurophotonic techniques will enable a whole gamut of applications from fundamental science studies to designing next generation neural prostheses.
Situational awareness of computer networks presents many challenges including but not limited to the volume of the data and the dynamic and evolving nature of the problem space. For example, at the perimeter of a corporate enterprise computer network, it is common to see terabytes of network traffic each day, containing millions of unique IP addresses and connection records that number in the hundreds of millions. Celeste will provide an overview and discuss recent trends facing computer security researchers and practitioners. She will describe recent work at Lawrence Livermore National Laboratory to enable analysis of computer networks and encourage an interactive discussion to foster new ideas to address these challenges.
"When: the Scientific Secrets of Perfect Timing" by Daniel H. Pink
Instant New York Times Bestseller
#1 Wall Street Journal Business Bestseller
Instant Washington Post Bestseller
Daniel H. Pink unlocks the scientific secrets to good timing to help you flourish at work, at school, and at home. Everyone knows that timing is everything. But we don't know much about timing itself. Our lives are a never-ending stream of "when" decisions: when to start a business, schedule a class, get serious about a person. Yet we make those decisions based on intuition and guesswork. Timing, it's often assumed, is an art. In "When: The Scientific Secrets of Perfect Timing", Pink shows that timing is really a science.
Drawing on a rich trove of research from psychology, biology, and economics, Pink reveals how best to live, work, and succeed. How can we use the hidden patterns of the day to build the ideal schedule? Why do certain breaks dramatically improve student test scores? How can we turn a stumbling beginning into a fresh start? Why should we avoid going to the hospital in the afternoon? Why is singing in time with other people as good for you as exercise? And what is the ideal time to quit a job, switch careers, or get married? In "When", Pink distills cutting-edge research and data on timing and synthesizes them into a fascinating, readable narrative packed with irresistible stories and practical takeaways that give readers compelling insights into how we can live richer, more engaged lives.