Keynote Speakers

Edo Liberty

Victor Bahl

Microsoft Research

Victor Bahl is a technical fellow and the director of mobility & networking in Microsoft Research, with over 30 years of industry experience. He advises Microsoft’s CEO and senior leadership team on long-term vision/strategy in networked systems, edge and cloud infrastructures, mobile computing, wireless systems, and 5G. He leads a group that executes on this vision through research, incubations, technology transfers to product groups, industry partnerships, and associated engagement with governments and research institutes around the world. Dr. Bahl has delivered numerous foundational technologies to Azure, XBOX and Windows. Some seminal technologies he has developed include edge computing, white space networking, mesh networking, Wi-Fi virtualization, multi-radio systems, Wi-Fi hot-spots, and indoor localization. His contributions in dynamic spectrum access led to the United States FCC opening 180 MHz of spectrum for unlicensed use. He has published 125 papers with over 50,000 citations, he has been issued 165 patents, and has received numerous technical leadership awards incl. two test-of-time awards, three best paper awards, two U.S. FCC awards, two national transportation awards, two distinguished alumni awards, and four lifetime outstanding achievement awards from ACM and IEEE. He is the founder/co-founder of ACM SIGMOBILE, MobiSys, GetMobile and several other important conferences and journals. Dr. Bahl is a Fellow of ACM, IEEE, and AAAS

Keynote Title: Edge Computing for the (Telecom) Infrastructure

Abstract: I will explore the edge computing paradigm from the perceptive of a researcher who has worked on this since its inception over a decade ago. I will discuss the evolution of the intelligent edge, describe some real-world applications and products. I will describe the progress we have made, the lessons we have learned as we developed an edge-cloud live video analytics system called Rocket. Rocket is deployed in several pilots and is used to reduce traffic-related fatalities and improve urban mobility. I will take a peek into the future and predict how the telecom industries will be impact as the edge computing become part of it’s infrastructure. I will lay out some of technical and business challenges facing the large-scale adoption and the opportunities these challenges are creating.

Edo Liberty

Rick L. Stevens

Argonne National Laboratory

Professor Rick Stevens is internationally known for work in high-performance computing, collaboration and visualization technology, and for building computational tools and web infrastructures to support large-scale genome and metagenome analysis for basic science and infectious disease research. A current focus is the national initiatives for Exascale computing and Artificial Intelligence (AI). He is the Associate Laboratory Director at Argonne National Laboratory, and a Professor of Computer Science at the University of Chicago. In addition, he is the principle investigator of the NIH-NIAID funded PATRIC Bioinformatics Resource Center, the Exascale Computing Project (ECP) Exascale Deep Learning and Simulation Enabled Precision Medicine for Cancer project, and the predicitive models pilot of the DOE-NCI funded Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) project. Over the past twenty years, he and his colleagues have developed the SEED, RAST, MG- RAST, and ModelSEED genome analysis and bacterial modeling servers that have been used by tens of thousands of users to annotate and analyze more than 250,000 microbial genomes and metagenomic samples.

Edo Liberty

Edo Liberty

HyperCube Inc.

Edo is the founder of HyperCube, an early-stage startup in the machine learning and cloud computing space. He was a Director of Research at AWS and the head of Amazon AI Labs. He led the creation of Amazon SageMaker and its Elastic Algorithms suite. He was also the science director supporting Amazon Elastic Search, Kinesis, Glue, QuickSight, Personalize, Forecast, DeepRacer and other AWS services. Prior to that, he managed Yahoo’s independent research lab in New York and its scalable Machine Learning Platforms group. Edo also co-founded an automatic video content recognition startup which was later acquired by Vizio. Edo Liberty received his B.Sc. in Physics and Computer Science from Tel Aviv University and his PhD in Computer Science from Yale University, where he was also a postdoctoral fellow in Applied Mathematics. As an adjunct professor at Tel Aviv University, Edo taught advanced data mining algorithms. He is the author of more than 75 academic papers and patents on topics such as machine learning, data mining, streaming algorithms, and optimization. His publications include award-winning breakthroughs on streaming matrix approximation and fast dimension reduction. He is a frequent program committee member and invited keynote speakers at international academic and developer conferences.

Keynote Title: Benefits and Challenges of combining Deep Learning and Search

Abstract: Deep Learning has fundamentally changed Information Retrieval. Traditional search retrieves text documents based on text queries. Today, however, companies want to search for images, videos, customers, jobs, shopping catalog items, friends, places, and many more. For such searches, Deep Learning models provide the most accurate results. Unfortunately, deploying and serving machine learning models at massive scale is still a herculean effort even for highly tech-heavy companies. This talk will survey some of those challenges. We will also introduce a new cloud-managed service by HyperCube which serves such real-time workloads.

Edo Liberty

Kristin Lauter

Microsoft Research

Kristin Lauter is a Principal Researcher and Partner Research Manager for the Cryptography and Privacy Group at Microsoft Research. She serves on the Senior Leadership Team for the MSR Redmond Lab, and also leads a new Urban Innovation team. Her work focuses on ensuring privacy and security for data, communication, and e-commerce though development and implementation of strong encryption techniques. She helped to develop Microsoft’s Elliptic Curve Cryptography (ECC) solutions, which shipped in Windows starting with Windows Vista in 2005, and is now deployed across the industry worldwide. She worked on standardization of ECC through IEEE and ietf, and currently leads a consortium which she co-founded to standardize Homomorphic Encryption (HE). She is also known for her work in Post-Quantum Cryptography (PQC), for introducing supersingular isogeny graphs as a hard problem into cryptography in 2005 (a PQC candidate in the NIST PQC competition). She served as President of the Association for Women in Mathematics (AWM) from 2015 –2017. She is a Fellow of the American Mathematical Society, the AWM, and the 2018-2020 Polya Lecturer for the Mathematical Association of America.

Keynote Title: Private AI: Machine Learning on Encrypted Data

Abstract: As the world adopts Artificial Intelligence, the privacy risks are many. AI can improve our lives, but may leak or misuse our private data. Private AI is based on Homomorphic Encryption (HE), a new encryption paradigm which allows the cloud to operate on private data in encrypted form, without ever decrypting it, enabling private training and private prediction. This talk will explain Homomorphic Encryption and show demos of HE in action.

Edo Liberty

John M. Cioffi

Stanford University

Illinois-BSEE: 1978, Stanford-PhDEE: 1984, Prof. EE, Stanford, 1986-present, now emeritus. Founder Amati 1991 (1997 purchased by TI); Chairman and CEO ASSIA Inc. Cioffi's specific interests are in the area of high-performance digital transmission. Awards include IEEE AG Bell (2010) and Kirchmayer (2014) Medals; Member Internet (2014) and Consumer-Electronics (2018) Halls of Fame; Marconi Fellow (2006); Member, US National (2001) and UK Royal (2009) Engineering Academies. 600+ papers and 100+ heavily licensed patents.

Keynote Title: Wi-Fi-ve-G: Convergence or Contention?

Abstract: Are Wi-Fi and Five-G converging? Wireless internet access has its data-use volume dominated by Wi-Fi in unlicensed spectra. Predominately, unlicensed-spectra use empowers over-the-top applications and their service from any of the billion(s) of locations that terminate wireline internet service in a Wi-Fi access point. Contention protocols attempt to arbitrate Wi-Fi spectrum use, while LTE/5G systems instead leverage licensed cellular infrastructure to plan real-time use to avoid contention. 5G systems sometimes may also be permitted to operate opportunistically in unlicensed spectra in addition to their nominal licensed-spectra operation. This talk provides some insights on how they can converge productively.