SystemX

In this lecture, I will give an overview of hybrid and electric vehicle systems, battery technologies, the charging infrastructure, and grid integration. Electric vehicles aren't just an efficient way to move people and products - they are literally powering the transition to a clean energy economy. We will go into the details of Lithium-ion battery technology and the importance of designing a robust Battery Management Systems (BMS) to manage the charging and discharging of a battery while providing estimates on the health of the battery during its use.

IoT Applications and Devices are growing by folds, estimated over 20 billion devices connected by the end of 2020, protecting such application and devices is not and easy task keeping in mind that IoT as an ecosystem consists of four elements: 1) Sensors, 2) Communications/Networks, 3) Cloud 4) Applications and each comes with its security challenges

The implementation of AI systems into the mix can serve as a real turning point. New AI algorithms adapt over time, and make it easier to respond to cybersecurity risks. However, new generations of malware and cyber-attacks can be difficult to detect with conventional cybersecurity protocols. They evolve over time, so more dynamic approaches are necessary, this the job of the first line of defense: AI.

Developments in Blockchain have expanded beyond recordkeeping and cryptocurrencies. The integration of smart contract development in Blockchain platforms has ushered in a wider set of applications, including cybersecurity. The goal was to keep the cyber-criminals at bay (using AI), but in case they managed to get-in and infiltrate the network we need to initiate the second line of defense; Blockchain. By using Blockchain, transaction details are kept both transparent and secure. Blockchain's decentralized and distributed network also helps businesses to avoid a single point of failure, making it difficult for malicious parties to steal or tamper with business data.

In contrast to embodied intelligence, which is common in nature, the recent progress in AI has been disembodied. Animals display remarkable degrees of embodied intelligence by leveraging their evolved morphologies to learn complex tasks. In the first part of the talk, I will argue that intelligent behavior is a function of the brain, morphology, and the environment. However, the principles governing relations between environmental complexity, evolved morphology, and the learnability of intelligent control, remain elusive, partially due to the substantial challenge of performing large-scale in silico experiments on evolution and learning. To address this, I will introduce a new framework called DERL which enables us to evolve agents with diverse morphologies to learn hard locomotion and manipulation tasks in complex environments, and reveals insights into relations between environmental physics, embodied intelligence, and the evolution of rapid learning. In the second part of the talk, I will present our work which addresses another key limitation holding back progress in the field of embodied AI: lack of embodiment agnostic general purpose pre-trained sensorimotor controllers. I will showcase how we can learn a general purpose pre-trained controller which can generalize to unseen 3D robot morphologies and tasks.

The high demand for AI services in conjunction with a dramatic chip shortage along with technology leaps such as 5/6G networks, cybersecurity threats, and quantum algorithms have resurrected a R&D push for advanced information processing and computing capability. To address this demand and explore novel technology roadmaps, unique opportunities exist, for example, given by algorithmic parallelism of digital- analog mixed-signal non-van Neuman accelerators. Especially electronic-photonic ASIC compute paradigms hold promise to enable non-iterative O(1) runtime complexity, ps-short latency, and TOPS/W throughputs. This opens prospects for next-generation hardware both for AI cloud services but also for accelerating edge computing such as enabled by compact and efficient PIC-CMOS co-designs pushing the SWAP envelope. As both a professor and a co-founder of a venture, in this seminar I will share my latest insights on fundamental complexity scaling and algorithm-hardware homomorphism on the one hand, and device- circuit- and system-level realizations on the other. I will introduce a novel photonic RAM capable of zero-static power consumption suitable for AI edge applications and highlight our mixed-signal tensor core ASIC demonstration leveraging parallelism including software-stack. Beyond matrix-matrix multiplication acceleration, I will show a Convolution Theorem-based accelerator enabling 1000x1000 matrix-size convolutions at 100us latency, or about 10x faster than today's GPUs. At the device level I will share advanced optoelectronics and quantum matter including a 20Gbps ITO-based modulator being 1,000x more compact than Silicon and LN modulators, discuss strainoptronic detectors with high gain-bandwidth- product and a 100GHz fast VCSEL, and share a path for an electrically-driven quantum source. Finally, having solved the complex-signal convolution I will show a Montgomery Multiplier for a data-center RSA public-key cryptosystem, and conclude by highlighting our recent post-quantum secure-hash-algorithm (SHA) system accelerating blockchain operations.

As the benefits from Moore's Law diminish, future computing performance improvements must rely on specialized accelerators for applications in high performance computing, artificial intelligence, and traditional data processing. These challenging applications are characterized by terabyte sized models, data sparsity and irregular control flow. In this talk, we explain how Reconfigurable Dataflow Accelerators (RDAs) can be used to accelerate a broad set of data-intensive applications with these characteristics. SambaNova Systems is using RDA technology contained in Reconfigurable Dataflow Units (RDUs) to achieve record-setting performance on challenging machine learning tasks. We will describe how RDAs can also be used to accelerate database and HPC applications with irregular control and data flow using a new execution model called Dataflow threads.

Choreographers and roboticists both organize moving bodies in space, yet the platforms and practices they employ are seemingly dissimilar. This talk describes the emerging field of choreorobotics, from dancing robots to novel programming interfaces, and why the intersection of these artistic and engineering fields is rapidly expanding.

Day 1 - Monday, November 8 • (8:00am-1:00pm) Student Poster Sessions
Day 2 - Tuesday, November 9 • (9:00am-2:10pm) Plenary Talk by Department Chair, Focus Area Overviews, and Technical Sessions
Day 3 - Wednesday, November 10 • (9:15am-2:10pm) New Faculty Introductions, Focus Area Overviews, and Technical Sessions
Day 4 - Thursday, November 11 • (3:00pm-8:25pm) Focus Area Overviews and Technical Sessions

Two key trends are revolutionizing the way humans conduct spaceflight, namely, the miniaturization of satellites (e.g., micro- and nano-satellites) and the distribution of payload tasks among multiple coordinated units (e.g., formation-flying, on-orbit servicing, fractionation, swarms). The combination of these approaches promises breakthroughs in space science (e.g., imaging of earth-like planets, characterization of gravitational waves), remote sensing (e.g., synthetic aperture radar interferometry, aeronomy, gravimetry), and space exploration (e.g., lifetime extension, assembly of structures, space debris removal). Irrespective of the specific application, future miniature distributed space missions require a high level of autonomy to maintain and reconfigure the relative motion of the participating vehicles within the prescribed accuracy and range of operations. Especially on small spacecraft, these requirements are hard to meet due to the limited resources, and the chief goal of current research and development is to pave the way for the autonomous Guidance, Navigation, & Control (GN&C) of "self-driving nanosatellites". This presentation addresses the new miniature distributed space instruments and the related GN&C algorithms under development at the Stanford's Space Rendezvous laboratory.

TBA

Dr. Boneh is a Professor of Computer Science at Stanford University where he heads the applied cryptography group and co-directs the center for blockchain research (CBR). Dr. Boneh's research focuses on applications of cryptography to computer security. His work includes cryptosystems with novel properties, web security, cryptography for blockchains, and cryptanalysis. He is the author of over a 150 publications in the field and is a recipient of the 2014 ACM prize and the 2013 Godel prize. In 2016 Dr. Boneh was elected to the National Academy of Engineering.