Tuesday May 15, 2018 – Opening Keynote: Rebuilding Puerto Rico’s Grid: Eight Months and Counting
Maria Gallucci, Energy Journalism Fellow at The University of Texas at Austin
Maria Gallucci, a freelance science writer, is the 2017-2018 Energy Journalism Fellow at UT Austin.
She recently reported in-depth for IEEE Spectrum on the grueling effort to restore Puerto Rico’s power grid after Hurricane Maria. More than half a year later, the island is still recovering, and its electric and communications systems remain vulnerable to future hurricanes.
As UT’s Energy Journalism Fellow, Maria is also working on a non-fiction book about the clean energy transformation in the global shipping industry. Through interviews and high-seas travels, she’ll explore how entrepreneurs, innovators and engineers are striving to tackle this final frontier in the low-carbon economy.
Prior to the fellowship, Maria was a reporter for Mashable, InsideClimate News, International Business Times and the independent magazine Makeshift. She previously worked as a journalist in Mexico City and has reported extensively from Latin America.
Her work has also appeared in a variety of publications, including WIRED, Scientific American, Grist, Yale Environment 360, Associated Press, Bloomberg, The Guardian, the Spanish newspaper El País and German broadcaster Deutsche Welle.
Follow her on Twitter: @mariagallucci
Abstract – Maria Gallucci traveled to Puerto Rico to learn how this post-storm disaster unfolded and what the island can do to build back stronger. She met with PREPA engineers, U.S. linemen, resourceful solar power installers and frustrated residents who are navigating life without the lights on. The restoration of Puerto Rico’s power grid is a timely object lesson on the vulnerabilities of modern electrical networks and on the emerging technological options for minimizing those vulnerabilities. Power experts are now not just repairing Puerto Rico’s grid but doing so with an eye toward a future that is more reliable and resilient in the face of fierce storms with tremendous damage.
Wednesday May 16, 2018 – Morning Keynote: The 10 Steps to 5G Heaven
Geoff Hollingworth, Chief Marketing Officer of MobiledgeX, a Deutsche Telekom subsidiary focused on edge computing
Geoff is overall responsible for marketing at MobiledgeX Inc. MobiledgeX’s mission is to delight developers with global edge services which are easy, valuable, trusted and mobile first.
Previously in Ericsson, Geoff drove the global positioning, promotion and education of Ericsson’s approach to next generation infrastructure to support future 5G and IOT growth with the right economic.
Before, Geoff was embedded with AT&T in Silicon Valley, leading Ericsson’s innovation efforts towards the AT&T Foundry initiative. He has also held positions as Head of IP Services Strategy for North America and overseeing the Ericsson brand in North America, as well as other roles in software R&D and mobile network deployment. Joining Ericsson more than 20 years ago, Geoff has been based in London, Stockholm, Dallas and Silicon Valley. The only other place Geoff has worked is CERN.
He holds a First Class Honors Bachelors degree in Computing Science and has won the Computing Science Prize of Excellence from Aston University in Birmingham, United Kingdom.
“I am a marketing person first, software guy second and love creating passionate successful teams.”
Abstract – Coming soon…
Wednesday May 16, 2018 – Afternoon Keynote: Platform Approach for SDN Predictive Management Using AI and ML
David H. Lu, Vice President, D2 Platform & Systems Development for AT&T Labs
David Lu is currently responsible for development and engineering of AT&T next generation ECOMP platform and Open ECOMP (ONAP) to enable the AT&T network virtualization (SDN) and target OSS/BSS transformation including API, micro-services, policy control & orchestration, hyper-automation, and advanced data analytics. He leads an organization with more than 2,000 people across the globe.
David is a well-respected leader in large scale and real time software architecture and engineering, network performance and traffic management, work flow and policy controlled automation, large databases and big data implementation/mining/analytics, machine learning, artificial intelligence, software reliability and quality, and network operations process engineering. Examples of his achievements include large scale platforms he has led and engineered that process annually: 347 Trillion network performance events and 168 Billion alarms with 99.99%+ automation; 60 Million dispatches with 14.4 Billion automated manual steps; and over 90 Billion API transactions.
Since joining AT&T Bell Labs in 1987, he has served in various leadership positions at AT&T. He has led multiple extreme automation initiatives in AT&T that resulted in Multi-Billion Dollars savings in the past 15 years and won AT&T CIO 100 Awards in 2010. He holds 43 patents and has frequently appeared as a guest speaker at technical and leadership seminars and conferences throughout the world. He received numerous industry awards including the 2015 Chairman’s Award from IEEE Communication Society for Network and Systems Quality and Reliability and 2017 CIE AAEOY (Asian America Engineer of Year) Award. He has also been very active in community organizations and activities including AT&T APCA, DFW-CIE, and DFW Asian American Chamber of Commerce. He was recognized by AT&T APCA with the 2015 Corporate Leadership Award.
He was accepted to the world-renowned Shanghai Conservatory of Music and came to the U.S. to complete his college education. He has an undergraduate degree in music, majoring in cello performance and graduate degree in Computer Science.
Abstract – AI and ML are the latest hot buzz words not only from the top technology companies but also from businesses large or small around the world. AT&T has promoted the cause of AI/ML over the last 20 years in predictive network management. AT&T is upping its game in AI/ML analytics by partnering with the industry and open source communities with new AI/ML platforms like ACUMOS, as well as by using ONAP as a platform to provide a framework for easy integration. We recognized early on that one of the challenges in applying new ML is the conflict of aggressive prediction from AI/ML vs. network reliability. AT&T has implemented a “sandbox” to enable experts in operation to trial AI/ML rules with real time production data in an experimental environment first, then deploy them into production without code changes. This talk will describe the strategy and implementation with a quick video demo.