Industry & Government Track Invited Talks

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CALL FOR: Industry and Government Invited Talks

Scaling web applications like recommendation systems, search and computational advertising is challenging. Such systems have to make astronomical number of decisions every day on what to serve users when they are visiting the website and/or using the mobile app. Machine learning and statistical modeling approaches that can obtain insights by continuously processing large amounts of data emitted at very high frequency by these applications have emerged as the method of choice. However, there are three challenges to scale such methods : a) scientific b)infrastructure and c) organizational. I will provide an overview of these challenges and the strategies we have adopted at LinkedIn to address those. Throughout, I will illustrate with examples from real­world applications at LinkedIn

Deepak Agarwal is a big data analyst with 15 years of experience developing and deploying state­of­the­art machine learning and statistical methods for improving the relevance of web applications. He has worked in various positions: chief scientist of large projects, led small and highly technical teams and is also experienced in managing large teams. Deepak currently leads a team that is responsible for all machine learning and optimization efforts at LinkedIn. He is a Fellow of the American Statistical Association, Member Board of Directors for SIGKDD, program chair of KDD in the past, associate editor of two top­tier journals in Statistics, regularly serves on senior program committees of top­tier conferences like KDD, NIPS, CIKM, ICDM, SIGIR, WSDM.

Financial services and healthcare companies could be the biggest beneficiaries of big data. Their real­time decision engines can be vastly improved by leveraging the latest advances in big data analytics. However, these companies are challenged in leveraging Open Software Systems (OSS). This presentation covers how, in collaboration with financial services and healthcare institutions, we built an OSS project to deliver a real­time decisioning engine for their respective applications. I will address two key issues. First, I will describe the strategy behind our hiring process to attract millennial big data developers and the results of this endeavor. Second, I will recount the collaboration effort that we had with our large clients and the various milestones we achieved during that process. I will explain the goals regarding big data analysis that our large clients presented to us and how we accomplished those goals. In particular, I will discuss how we leveraged open source to deliver a real­time decisioning software product called Kamanja to these institutions. An advantage of developing applications in Kamanja is that it is already integrated with Hadoop, Kafka for real­time data streaming, HBase and Cassandra for NoSQL data storage. I will talk about how these companies benefited from Kamanja and some of challenges we had in the design of this software. I will provide quantifiable improvements in key metrics driven by Kamanja and interesting, unsolved problems/challenges that need to be addressed for faster and wider adoption of OSS by these companies.

Bassel Ojjeh heads ligaDATA, where he is responsible for the strategic and technological development of an online open­source Big Data learning engine called Kamanja.

Prior to LigaDATA, Ojjeh served as a Senior Vice President of Data Technologies & Products at Yahoo! after the company acquired his Seattle­based data startup, DMX Group. At Yahoo!, his group was responsible for building data products that drive audience engagement and advertising revenues. These products consumed some of the largest data sets in the world, generated by the half a billion users of Yahoo!

Before founding the DMX Group, Ojjeh co­founded digiMine (now Audience Science), where he and his co­founders pioneered behavioral targeting.

Before founding digiMine, Bassel was Group Program Manager in the Internet Business division at Microsoft, where he drove key initiatives in the areas of data warehousing, data mining, personalization and predictive analytics. He started his career as a developer at Fox Software, which was later acquired by Microsoft for $1.5 billion.

Bassel Ojjeh is a Hall of Fame inductee at Bowling Green State University. He also serves on the Board of Directors of the International University of Science and Technology in Syria, which he co­founded.

Financial services and healthcare companies could be the biggest beneficiaries of big data. Their real­time decision engines can be vastly improved by leveraging the latest advances in big data analytics. However, these companies are challenged in leveraging Open Software Systems (OSS). This presentation covers how, in collaboration with financial services and healthcare institutions, we built an OSS project to deliver a real­time decisioning engine for their respective applications. I will address two key issues. First, I will describe the strategy behind our hiring process to attract millennial big data developers and the results of this endeavor. Second, I will recount the collaboration effort that we had with our large clients and the various milestones we achieved during that process. I will explain the goals regarding big data analysis that our large clients presented to us and how we accomplished those goals. In particular, I will discuss how we leveraged open source to deliver a real­time decisioning software product called Kamanja to these institutions. An advantage of developing applications in Kamanja is that it is already integrated with Hadoop, Kafka for real­time data streaming, HBase and Cassandra for NoSQL data storage. I will talk about how these companies benefited from Kamanja and some of challenges we had in the design of this software. I will provide quantifiable improvements in key metrics driven by Kamanja and interesting, unsolved problems/challenges that need to be addressed for faster and wider adoption of OSS by these companies.

Greg Makowski is the Director of Data Science at ligaDATA, where he drives the data mining direction of the open source product, Kamanja, is an evangelist, and consults with customers.

Greg has been deploying data mining models since 1992, covering a variety of vertical markets and applications, including financial services, fraud, web behavior, banner advertising, retail supply chain and customer relationship management. He prototyped the embedded data mining for three enterprise apps, 3 SaaS apps and 3 web-time machine learning scoring systems. He has built up an analytic team and production system providing fraud monitoring for $80 billion of consumer transactions per year.

Greg has also been involved in a local chapter of the ACM, www.SFbayACM.org, organizing data science speakers, the Data Science Camp since 2009, business development, hackathons and our YouTube channel of 50+ talks.

Several exciting trends are driving the birth of the intelligent cloud. The vast majority of world’s data is now connected data resident in the cloud. The majority of world’s new software is now connected software, also resident in or using the cloud. New cloud based Machine Learning as a Service platforms help transform data into intelligence and build cloud­hosted intelligent APIs for connected software applications. Face analysis, computer vision, text analysis, speech recognition, and more traditional analytics such as churn prediction, recommendations, anomaly detection, forecasting, and clustering are all available now as cloud APIs, and far more are being created at a rapid pace. Cloud hosted marketplaces for crowdsourcing intelligent APIs have been launched. In this talk I will review what these trends mean for the future of data science and show examples of revolutionary applications that you can build using cloud platforms.

Joseph Sirosh is the Corporate VP for Machine Learning at Microsoft in the Cloud & Enterprise Group. His team is building the next generation of cloud Machine Learning and Information Management services for transforming data into intelligence. Prior to joining Microsoft in 2013, he was the Vice President of the Global Inventory Platform at Amazon, and also conceived and built the development team for the Amazon Machine Learning service. Prior to joining Amazon in 2004, he was the VP of R&D at FICO. Joseph holds a PhD in Computer Science from the University of Texas at Austin, and a Bachelors in CS from Indian Institute of Technology, Chennai.

Computers are making more and more decisions for us, and increasingly so in areas that require human judgment. There is a palpable increase in machine intelligence across the touch points of our lives, driven by the proliferation of data feeding into intelligent algorithms capable of learning useful patterns and acting on them. A natural question to ask is how we should be thinking about the role of computers in managing our money. Should we trust our money to a robot? In an era of big data and machines to make sense of it all, do machines have an inherent advantage over humans? There is a surge of interest in Artificial Intelligence for financial prediction. Should we pay attention? Or is this an area where human judgment and input is always essential?

Vasant Dhar is Professor, Stern School of Business and Center for Data Science at New York University, and Founder of SCT Capital Management. He created the Adaptive Quant Trading (AQT) program, a data­driven learning machine that trades the world’s most liquid futures contracts systematically. Dhar has written over 100 research articles and dozens of opinion editorials in media including the Financial Times, Wall Street Journal, Forbes, and Wired Magazine. He is Editor­in­Chief of the Big Data journal.

Is my marketing working, how much is marketing helping the business and which campaigns and channels are effective? The key challenge for the Chief Marketing Officer is to tie investment in marketing to business results. In an increasingly complex marketing environment – marketing organizations are being called upon to prove and optimize the return on marketing investment across different paid earned and owned marketing channels. In this talk we will show how data science and optimization techniques can be applied to cross channel data to attribute marketing effectiveness, drive media planning and real­time optimization of campaigns. Using terabytes of multi­channel data we answer questions such as what is the impact of different marketing campaigns on our business, how should we allocate our marketing dollars between different channels and when should I spend them and how do we execute our marketing campaigns based on the synergies of the different channels.

Anil Kamath, Fellow and VP of Technology at Adobe, is a web and technology entrepreneur. At Adobe, he is responsible for data driven algorithms for the Adobe Marketing cloud. He was founder and primary architect of Efficient Frontier, a leading digital ad buying platform, until its acquisition by Adobe. Prior to that Anil, founded an ecommerce company call eBoodle that was acquired by Shopzilla. He has held leadership positions at Shopzilla and DE Shaw and received a PhD in Computer Science from Stanford University and a B.Tech in Computer Science from IIT Bombay.

As Hadoop and the surrounding projects & vendors mature, their impact on the data management sector is growing. Amr will talk about his views on how that impact will change over the next five years. How central will Hadoop be to the data center of 2020? What industries will benefit most? Which technologies are at risk of displacement or encroachment?

Dr. Amr Awadallah, Cofounder/CTO, Cloudera, Inc. Before co-founding Cloudera in 2008, Amr (@awadallah) was an Entrepreneur-in-Residence at Accel Partners. Prior to joining Accel he served as Vice President of Product Intelligence Engineering at Yahoo!, and ran one of the very first organizations to use Hadoop for data analysis and business intelligence. Amr joined Yahoo after they acquired his first startup, VivaSmart, in July of 2000. Amr holds a Bachelor’s and Master’s degrees in Electrical Engineering from Cairo University, Egypt, and a Doctorate in Electrical Engineering from Stanford University.

In 2008, Rocket Fuel's founders saw a gap in the digital advertising market. None of the existing players were building autonomous systems based on big data and artificial intelligence, but instead they were offering fairly simple technology and relying on human campaign managers to drive success. Five years later in 2013, Rocket Fuel had the best technology IPO of the year on NASDAQ, reported $240 million in revenue, and was ranked by accounting firm Deloitte as the #1 fastest-growing technology company in North America. Along the way we learned that it's okay to be bold in our expectations of what is possible with fully autonomous systems, we learned that mainstream customers will buy advanced technology if it's delivered in a familiar way, and we also learned that it's incredibly difficult to debug the complex "robot psychology" when a number of complex autonomous systems interact. We also had excellent luck and timing: as we were building the company, real-time ad impression-level auctions with machine-to-machine buying and selling became commonplace, and marketers became increasingly focused on delivering better results for their company and delivering better personalized and relevant digital experiences for their customers. The case study presentation will present a fast-paced overview of the business and technology context for Rocket Fuel at inception and at present, key learnings and decisions, and the road ahead.

George is Chairman and Founder of Rocket Fuel Inc., a smart digital marketing software company that he founded and led as CEO to over 1000 employees and $400 million revenue. Rocket Fuel's software self-optimizes ad campaigns and marketing programs, to drive better results for the business and more relevant digital experiences to customers. The secret sauce is its $100 million investment in artificial intelligence and big data, and Rocket Fuel's moment scoring engine that considers all relevant information just as an ad or message is being delivered. As of Q1 2015, Rocket Fuel powered 96 of the top 100 US advertisers (the "AdAge 100"), plus an increasing number of top global advertisers. Rocket Fuel's DSP (media buying demand-side platform) and DMP (data management platform) have been rated top products in their categories by Forrester and Gartner.

Prior to Rocket Fuel, George led groups at IBM, E.piphany, salesforce.com, and most recently Yahoo!, where he managed behavioral targeting, recommendations, and click fraud. The combined IPO's of E.piphany, salesforce.com, and Rocket Fuel created over $50 billion in peak value for shareholders.

As a kid, George was overly influenced by Star Trek, which led to a short-lived interest in model rocketry (eyebrows grew back after the explosion) and a lifelong interest in Artificial Intelligence. George earned BS, MS, and PhD degrees in Computer Science from Stanford, specializing in AI. During his graduate studies, he won a National Science Foundation fellowship and worked on autonomous spacecraft at NASA, earning his "rocket scientist" credentials.

It is extremely important in many application domains to have accurate models of user behavior. Data mining allows user models to be constructed based on vast available data automatically. User modeling has found applications in mobile APP recommendations, social networking, financial product marketing and customer service in telecommunications. Successful user modeling should be aware of several critical issues: who are the target users? How should the solutions be updated when new data come in? How should user feedback be handled? What are the ‘pain’ points of users? In this talk, I will discuss my own experience on user modeling with big data. I will draw examples from telecommunications and the Internet industry, contrasting and highlighting some lessons learned in these industries.

Qiang Yang is the New Bright University Named Professor of Engineering and Chair Professor at Hong Kong University of Science and Technology, where he is the Head of the Department of Computer Science and Engineering. He was the founding head of the Huawei Noah’s Ark Lab (2012-2015). He is currently the Technical Advisor to WeChat. His research interests are data mining, machine learning and artificial intelligence. He is a fellow of AAAI, IEEE, IAPR and AAAS, and ACM Distinguished Scientist. He received his PhD degree in Computer Science from University of Maryland, College Park in 1989, and had been a faculty member at University of Waterloo and Simon Fraser University in Canada. He had been the founding Editor in Chief of ACM Transactions on Intelligent Systems and Technology (ACM TIST) between 2009 and 2014, and is the founding Editor in Chief of IEEE Transactions on Big Data. He has been conference and program chairs for international conferences such as ACM KDD 2010 and 2012, ACM IUI 2010, IEEE Big Data 2013, ACM RecSys 2013 and International Joint Conference on Artificial Intelligence (IJCAI) in 2015.

DARPA has been investing in data science and building open source tools for applications ranging from counter threat finance, through radar operations and cancer research, to anti-human trafficking. This presentation will cover recent work at DARPA, experience building real-world applications for defense and law enforcement to analyze data, and the future of computer science as an enabler for content discovery, information extraction, relevance determination, and information visualization. The talk will be a mix of background, detailed examples, and software demonstration. It will cover the importance of anchoring in applications, minimization of design-to-testing time, development with users-in-the-loop, error tolerance of machine learning, design for diverse user populations, and the necessity of open source software integration. It will conclude by covering a few next directions for special projects at Microsoft.

Chris White is a Principal Researcher at Microsoft working on special projects. He was recently a Program Manager at DARPA developing advanced technologies for data science, where he created DARPA's leading programs XDATA, Memex, and the Open Catalog as part of the President's Big Data Initiative. His work has been applied to domains including countering human trafficking and counter terrorism, where it has been featured on 60 minutes, CNN, the Wall Street Journal, TEDx, and Google’s Solve for X. He previously served DARPA as the Agency's country lead in Afghanistan. Secretary of Defense Leon Panetta recognized DARPA and his efforts in Afghanistan with a Joint Meritorious Unit Award for support in a combat environment. Prior to DARPA he was a fellow at Harvard’s School of Engineering and Applied Sciences and holds a PhD in electrical engineering from the Johns Hopkins University.

Visa is the payments technology that forms the backbone of the world’s financial systems by handling more than 7 trillion dollars of payments annually and our data reflects how the world spends money. We will describe technical achievements we have made in the area of fraud and cover some open challenges in data science.

Waqar Hasan joined Visa in 2014 and currently serves as Senior Vice President of Data. He is responsible for Visa’s data platform and data-driven products targeted at banks, merchants and consumers in areas like risk and fraud management, loyalty and business intelligence.

Prior to Visa, he was the founder and CEO of InsightsOne, a big data predictive analytics startup, from 2010-2014. At InsightsOne, Hasan formed a company backed by premier venture capital and sold product to Fortune 1000 customers. He led the company through its merger and integration with Apigee. InsightsOne helped make business and consumer interactions both relevant and profitable through cloud-based and on-premise predictive analytics and big data solutions. The combined company (NASDAQ: APIC) had a successful IPO in April 2015.

Prior to Apigee, Hasan was Vice President of Engineering for Data Systems at Yahoo!, where he built and managed Yahoo!’s data platform from 2004 to 2009. He oversaw systems that analyzed data from 500 million consumers, and which remains one of the largest-scale systems in the world, and affect nearly all of Yahoo!’s revenue streams in addition to substantially increasing monetization and consumer engagement.

Before joining Yahoo!, Hasan founded the startup DB Wizards, providing performance accelerators for ERP applications, was an architect at database software provider Informix and a researcher at HP Labs and IBM Almaden.

Waqar received his PhD in Computer Science from Stanford University and a BS in Computer Science from the Indian Institute of Technology, Kanpur. He has published over 20 papers and is a recipient of the ACM SIGMOD Test of Time award.

Dr. Min Wang joined Visa as the Senior Vice President of Visa Research in May 2015. Visa Research is a newly created organization as part of the company’s continued effort to expand technology research capabilities globally. Visa Research engages with the company’s technology and product teams, business partners, academics and governments, to explore and develop technologies that are critical to the payments industry. In her role, Wang leads the research on data analytics, security and the future of payments.

Prior to Visa, Wang was part of Google Research where she was a Senior Staff Research Scientist and research manager focused on knowledge integration and inferencing at Google’s headquarters in Mountain View, California. Before Google, Wang was Director of HP Labs China in Beijing, China, where she was also named an HP Distinguished Technologist. Wang also held a senior research role as the manager of the Unified Data Analytics Department at IBM’s Thomas J. Watson Research Center in Hawthorne, New York.

Wang has received several distinguished research awards for her work on data management. In 2009, Wang received the ACM SIGMOD Test of Time Award for her 1999 SIGMOD paper, "Approximate Computation of Multidimensional Aggregates of Sparse Data Using Wavelets.”

Wang received her PhD in Computer Science from Duke University and BS and MS degrees, both in Computer Science, from Tsinghua University, Beijing, China.

Julie was appointed as the Chief Analytics Officer at Insurance Australia Group (IAG) in July 2014 and is responsible for Group Information & Analytics and Reinsurance. The Information & Analytics team is focused on the creation of new information assets and the delivery of actionable analytics insights across the Group including customer, digital, risk and operational. Reinsurance concentrates on the design and implementation of the Group’s reinsurance protections including oversight of the Group’s captive reinsurance operations in Australia, Singapore and Labuan.

Prior to her current role, Julie was Chief Risk Officer in our Direct Insurance business (now Personal Insurance) on a 12-month secondment, which included leadership of a Group-wide program aimed at improving our analytics capabilities. Earlier in her career at IAG, Julie was Group General Manager, Reinsurance for four years originally joining the Group in 2005 as Chief Underwriting Manager Australia, Reinsurance.

In addition to her Group responsibilities, Julie leads the Working Party for the Australian Business Roundtable for Disaster Resilience and Safer Communities. The Roundtable aims to working constructively with governments in the national interest to prioritise public policy and funding to improve the nation’s resilience against future natural hazards. In 2015, the Roundtable through its research became the first private sector partnership to be awarded a Certificate of Distinction at the United Nations Sasakawa Awards for Disaster Reduction. This initiative has also been endorsed by the United Nations EPSI Board UNEP FI Principles for Sustainable Insurance Initiative to develop globally, lead by IAG.

Before joining IAG, Julie held senior roles at Gen Re Australia, part of the Berkshire Hathaway Group as well as other reinsurance organisations and has extensive international experience including time spent in France, Monaco, London and Japan.

Julie holds a Masters of Applied Finance and is a Fellow of ANZIIF.

Bill Simpson-Young is Director of Engineering and Technology Development at NICTA, Australia’s largest research centre in information and communications technology. At NICTA, Bill leads a group of software engineers and user experience designers working on 30 projects building novel software technologies including geospatial and vision processing technologies. Bill directs the software development of the Terria platform for federated spatial exploration which is the underlying platform of many new Internet-based spatial services including the Australian Government’s National Map (http://nationalmap.gov.au) service, the Australian Renewable Energy Mapping Infrastructure (http://nationalmap.gov.au/renewables) and the UN Environment Programme’s Global Risk Map (http://globalriskmap.nicta.com.au). He also directs the development of the popular Doarama (http://doarama.com), an Internet-based 3D visualisation engine for geolocated activities (such as aerial sports and drone operations).

Bill has over 25 years of experience in software research and development at Canon’s Australian R&D Centre (where he led the Video Processing Technology Division), Unisys, CSIRO and NICTA including leading teams to develop several technologies now used globally.

He teaches a Masters course on “Understanding IT Innovation” at the University of Sydney.