DataWorks Summit in Washington, DC

Cathy O’Neil is the author of the New York Times bestselling Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, which was also a semifinalist for the National Book Award. She is a columnist for Bloomberg View and founded the company ORCAA, an algorithmic auditing company.

She earned a Ph.D. in math from Harvard, was a postdoctoral fellow in the MIT math department, and a professor at Barnard College where she published a number of research papers in arithmetic algebraic geometry. She then switched over to the private sector, working as a quantitative analyst for the hedge fund D.E. Shaw in the middle of the credit crisis, and then for RiskMetrics, a risk software company that assesses risk for the holdings of hedge funds and banks. She left finance in 2011 and started working as a data scientist in the New York start-up scene, building models that predicted people’s purchases and clicks.

Cathy wrote Doing Data Science in 2013 and launched the Lede Program in Data Journalism at Columbia in 2014. She is a columnist for Bloomberg View.

• Big Data Algorithms: For Whom Do They Work?

As chief marketing officer, Mick leads Cloudera’s worldwide marketing efforts, including advertising, brand, communications, demand, partner, solutions, and web. Mick has had a successful 25-year career in enterprise and cloud software. Prior to joining Cloudera in 2016, he served as CMO of sales acceleration and machine learning company InsideSales.com. Under Mick’s leadership, InsideSales pioneered a shift to data-driven marketing and sales that has served as a model for organizations around the globe. Previous to InsideSales, Mick served as global vice president of marketing and strategy at Citrix, where he led the company’s push into the high-growth desktop virtualization market. Before Citrix, Mick managed executive marketing at Microsoft and held numerous leadership positions at IBM Software. Mick is an advisory board member for InsideSales and a contributing author on Inc.com. He is also an accomplished public speaker who has shared his insightful messages about the business impact of technology with audiences around the world. Mick graduated from the Georgia Institute of Technology, with a bachelor’s of science degree in management.

• Unlocking the Power of Data: From the Edge to AI

Nick Psaki is the Principal, Office of the CTO for Pure Storage Federal and is based in the Washington, DC area. Nick is Pure Storage's senior technical resource for Federal customers, providing deep technical knowledge of flash storage system architectures that enable business and technological transformation for government enterprises.

A 20-year veteran of the United States Army, Nick has extensive experience in designing, developing, deploying and operating information systems for data analysis, sensor integration, and large-scale server virtualization. He was the Intelligence Architectures Chief for the Army G2 (Intelligence), and the Technology and Integration Director for Army G2 Futures Directorate. He has served in multiple peacekeeping and combat operations ranging from the Balkans in the 1990s (Operation Able Sentry VI and Operation Joint Endeavor/Joint Guard) to Iraq and Afghanistan in the post-9/11 era. For the past several years, Nick has been focused on ways in which new and emerging technologies can enable more rapid and cost-efficient analysis of ever-growing bodies of data.

Nick's Thought Leadership/Public Examples and links:
https://www.fedinsider.com/government-data/
https://federalnewsnetwork.com/federal-insights/2018/12/big-data-data-analytics-call-for-new-backup-and-recovery-strategies/
https://www.governmentciomedia.com/sponsor-highlight-pure-storage
https://www.govexec.com/feature/architecture-for-the-future-viewcast/

• Data HUB: A Modern Architecture for Analytics & AI/ML

Hilary is general manager, machine learning, at Cloudera. She was the founder and CEO of Fast Forward Labs, an applied machine learning research company that Cloudera acquired in 2017. She also serves as data scientist in residence at Accel Partners, a leading global venture capital firm. Previously, Hilary was chief scientist at bitly. She co-hosts DataGotham, a conference for New York's home-grown data community, and co-founded HackNY, a non-profit that helps engineering students find opportunities in New York's creative technical economy. She is on the board of the Anita Borg Institute and an advisor to several companies, including Sparkfun Electronics and Wonder. Hilary served on Mayor Bloomberg’s Technology Advisory Board and is a member of the Brooklyn hacker collective NYC Resistor.

• Building an Enterprise AI Factory

Dr. Alex Xiaoyang Yang is the CTO and Chief Architect of IBM China Development Laboratory.
He has extensive experience with big data analytics in FSS, Transportation, and Telecom.

• Implementing a "City-Brain" with Progressively Extracted Moving Objects Data from City-wide Traffic and Surveillance Video Streams

Kamil is a technology leader in the large scale data warehousing and analytics space. He is CTO of Starburst, the enterprise Presto company. Prior to co-founding Starburst, Kamil was the Chief Architect at the Teradata Center for Hadoop in Boston, focusing on the open source SQL engine Presto. Previously, he was the co-founder and chief software architect of Hadapt, the first SQL-on-Hadoop company, acquired by Teradata in 2014.
Kamil began his journey with Hadoop and modern MPP SQL architectures about 10 years ago during a doctoral program at Yale University where he co-invented HadoopDB, the original foundation of Hadapt’s technology.

Kamil holds an M.S. in Computer Science from Wroclaw University of Technology and as well as M.S. and an M.Phil. in Computer Science from Yale University.

• Presto: Optimizing Performance of SQL-on-Anything Engine

Pradeep is a Senior Big Data Engineer at Hotels.com in London where he builds and manages cloud infrastructure and core services like Apiary. Pradeep has worked in the big data space for the last 7 years, building large scale platforms.

• Herding Elephants: Seamless Data Access in Multi-Cluster Clouds

Owen O'Malley is a co-founder and technical fellow at Hortonworks, a rapidly growing company (25 to 1,000 employees in 5 years), which develops the completely open source Hortonworks Data Platform (HDP). HDP includes Hadoop and the large ecosystem of big data tools that enterprises need for their data analytics. Owen has been working on Hadoop since the beginning of 2006 at Yahoo, was the first committer added to the project, and used Hadoop to set the Gray sort benchmark in 2008 and 2009. In the last 8 years, he has been the architect of MapReduce, Security, and now Hive. Recently he has been driving the development of the ORC file format and adding ACID transactions to Hive. Before working on Hadoop, he worked on Yahoo Search's WebMap project, which was the original motivation for Yahoo to work on Hadoop.  Prior to Yahoo, he wandered between testing (UCI), static analysis (Reasoning), configuration management (Sun), and software model checking (NASA). He received his PhD in Software Engineering from University of California, Irvine.

• Fast Access to your Complex Data: Avro, JSON, ORC, and Parquet
• Protect your Private Data in your Hadoop Clusters with ORC Column Encryption

Notable expert clinical information systems specialist offering 25-plus years of strategic leadership. Successful architect of healthcare data warehouses, clinical and business intelligence tools, big data ecosystems, and a health information exchange.

Excel at leading the development of long-term systems strategy for major medical organizations and executing plans to select innovative technology, implement systems, and leverage and maximize system functionality to enhance the health care delivery process.

Evangelist for the use of clinical technology to drive daily operations, analysis, and decisioning. Reputation for building consensus among medical, nursing and research leadership, clinical departments, and IT.

Scope of expertise encompasses designing technology-enabled processes, leading the clinical model for transformation, coordinating clinical workflow, ensuring the use of standardized data elements in clinical systems to meet clinical and research data warehouse requirements, leading teams through development and launch, and directing training.

Charles Boicey MS, RN-BC is the chief innovation officer for Clearsense, an outcomes-driven healthcare technology company based in Jacksonville, FL. Previously, Charles was the enterprise analytics architect for Stony Brook Medicine, where he developed the analytics infrastructure to serve the clinical, operational, quality, and research needs of the organization. He was a founding member of the team that developed the Health and Human Services award-winning application NowTrending to assist in the early detection of disease outbreaks by utilizing social media feeds. Charles is a former president of the American Nursing Informatics Association.

• Big Data Technologies in Support of a Medical School Data Science Institute

Data science expert and software system architect with expertise in machine-learning and big-data systems. Rich experiences of leading innovation projects and R&D activities to promote data science best practice within large organizations. Deep domain knowledge on various vertical use cases (e.g., Finance, Telco, Healthcare). Currently working pushing the cutting-edge application of AI at the intersection of high-performance database and IoT, focusing on unleashing the value of spatial-temporal data. I am also a frequent speaker at various technology conferences, including: O’Reilly Strata AI Conference, NVidia GPU Technology Conference, Hadoop Summit, DataWorks Summit, Amazon AWS re:Invent, Global Big Data Conference, Global AI Conference, World IoT Expo, Intel Partner Summit, presenting keynote talks and sharing technology leadership thoughts.

Received my Ph.D. from the Department of Computer and Information Science (CIS), University of Pennsylvania, under the advisory of Professor Insup Lee (ACM Fellow, IEEE Fellow). Published and presented research paper and posters at many top-tier conferences and journals, including: ACM Computing Surveys, ACSAC, CEAS, EuroSec, FGCS, HiCoNS, HSCC, IEEE Systems Journal, MASHUPS, PST, SSS, TRUST, and WiVeC. Served as reviewers for many highly reputable international journals and conferences.

• Building the AI Engine for Retail in the New Era

Surekha Saharan is a Druid Committer and Software Engineer at Imply. Previously, she has worked at cloud startup and Cisco Systems where she prototyped, architected and implemented large scale systems. She holds a MS in Computer Science from University of Southern California and BS in Computer Engineering from National Institute of Technology, India.

• Setting the Stage for Fast Analytics with Druid

Carolyn Duby is a Solutions Engineer and Cyber Security SME at Hortonworks, where she helps customers harness the power of their data with Apache open source platforms. Previously, she was the architect for cybersecurity event correlation at SecureWorks. A subject-matter expert in cybersecurity and data science, Carolyn is an active leader in the community and frequent speaker at Future of Data meetups in Boston, MA, and Providence, RI, and at conferences such as Strata Data Conference, Dataworks Summit, Open Data Science Conference and Global Data Science Conference. Carolyn holds an ScB (magna cum laude) and ScM from Brown University, both in computer science. She is lifelong learner and recently completed the Johns Hopkins University Coursera Data Science Specialization.

• Battling Botnets with Apache Metron
• How T-Mobile Tamed Metron

Kai Liu is a Senior Program Manager in AI and Research group of Microsoft. He has 8 years of experience in data driven engineering, big data platform and AI infrastructure for Office and Bing product families. He led his team to create a service health portal for SharePoint Online, inject a distributed log collection and storage system for Exchange Online, publish curated data sets, key business metrics, and enable sub-hour experimentations in Office 365.
Currently he is working on the next generation of Big Data and Deep Learning platform for Bing based on Open Source technologies.

• Free Servers to Build Big Data System on: Bing’s Approach

Highly efficient and results-oriented data scientist with strong quantitative skills, development experience and strong education background with a MSc (Imperial College London (World Rank within Top 10 QS)). Responsible self-starter with demonstrated experience in statistical programming language (R, Python, SAS) and programming language python for API’s. High ability holder on visualization with tools such as Tableau as well as good understanding of relational database such as SQL and oracle and non-relational database such as hbase, mongoDB and redis. Machine learning tools such as Hadoop, Spark, H2O, sparkling-water, pysparkling, SAS etc. as well as deep learning tools such as Keras, Tensorflow, Theano, MXnet, PyTorch. GPU cuda programming. Scaling data science. Expert in Predictive Modeling such as XGBoost, regression, Logit, Probit, GBM, RandomForest, Neural Network (generative model, GAN, VAE, RNN, CNN, word2vec etc.) , Naive Bays, K-nearest learn, PCA etc. (supervised learning, unsupervised learning, semi-supervised learning , reinforcement learning etc.) and also probabilistic modeling (PyMC3, Edward, Pyro) such as MCMC, HMC, NUTS, bayesian linear regression, variational models etc, Data mining skills such as parsing, nlp (natural language processing) and proficient in language modeling such as topic model, text clustering, word embedding, Word2Vec, Glove, text classification, RNN, Convolutional RNN etc. familiar with all the development environment such as Hadoop, Cloud (AWS, GCP, Azure) , GPU, Spark. etc.
Strong communication and relationship-building skills with diverse parties; fluent in English and Korean

• Hot Water Leak Detection Using Variational Autoencoder Model

Barbara Eckman is a Senior Principal Software Architect at Comcast and a recognized innovator in Big Data architecture and governance. She leads data discovery and lineage platform architecture for a division-wide initiative comprising streaming, transforming, storing, and analyzing Big Data. Barbara is also the Lead Metadata Architect for the Comcast Privacy Program, an initiative tackling the challenge of legislation like the California Consumer Privacy Act. Her prior experience includes scientific data and model integration at the Human Genome Project, Merck, GlaxoSmithKline, and IBM, where she served on the peer-elected IBM Academy of Technology.

• Taming an Ungoverned Legacy Data Lake and Extending Tag-based Authorization in a Heterogeneous Data Discovery Environment

Mayank Kejriwal is a research scientist at the University of Southern California's Information Sciences Institute (ISI), and a research assistant professor in the Department of Industrial and Systems Engineering. He received his Ph.D. from the University of Texas at Austin. His dissertation involved Web-scale data linking, and in addition to being published as a book, was recently recognized with an international Best Dissertation award in his field. His research is highly applied and sits at the intersection of knowledge graphs, social networks, Web semantics, network science, data integration and AI for social good. He has contributed to systems used by both DARPA and by law enforcement, and has active collaborations across academia and industry. He is currently co-authoring a textbook on knowledge graphs (MIT Press, 2018), and has delivered tutorials and demonstrations at numerous conferences and venues, including top academic venues such as KDD, AAAI, and ISWC, and industrial venues . He is currently serving as general chair of the ACM K-CAP conference in 2019, and is co-editing a special issue on knowledge graphs in the Semantic Web Journal. He was awarded a Key Scientific Challenges award in 2018 by the Allen Institute for Artificial Intelligence, and was recently named a Forbes Under 30 Scholar. He has also been nominated as a 2019 Forbes 30 Under 30 in the Science category.

• Applying Noisy Knowledge Graphs to Real Problems

Paul Gibeault has a B.S. degree in computer science from the University of Idaho and has spent most of his career developing software frameworks and tools to enable the automation of semiconductor equipment. He is currently a Big Data Solution Architect with the IT group at the third largest memory manufacturer in the world, Micron Technology, headquartered in Boise, Idaho. For the past five years he has focused on the design and implementation of an automated approach to create Micron’s Global Data Warehouse.

• Pipeline Builder: Micron’s Journey Automating the Global Data Warehouse

Product Management lead at Uber with a focus on Data Platforms and Infra. I manage Uber's Storage, Analytics, BI, and Machine Learning product lines.

https://www.brighttalk.com/webcast/15789/320149/data-as-reliable-as-running-water-analytics-machine-learning-at-uber

• Machine Learning at Uber: 2019 and Beyond

Lohit is part of Hadoop and Log Management team at Twitter. He has been concentrating on scaling Hadoop FileSystem, Hadoop Resource Manager, Log Ingestion and Processing pipelines at Twitter. Previously he has worked at few startups building scalable file systems and was also part of Hadoop team at Yahoo! when it was open sourced. He has Masters degree in Computer Science from Stony Brook University.

• Extending Twitter's Data Platform to Google Cloud

David is a Director of Solution Architecture at Streamlio, and also a contributor to the Apache NiFi, and Apache Pulsar projects. He was formerly the Practice Director at Hortonworks, where he was responsible for the development of best practices and solutions for the professional services team, with a focus on HDF-related technologies including Kafka, NiFi, and Storm. He is a co-author of “Practical Hive: A Guide to Hadoop’s Data Warehouse System”, and holds a B.S and Master’s Degree in Computer Science from Kent State University.

• Using Apache Pulsar to Provide Real-Time IoT Analytics on the Edge

Accomplished product owner with multiple years of professional experience working with leading-edge technologies supporting a large landscape of business cases. Proven problem solving skills, best management practices & result-oriented decision making capabilities

• Data Analytics and Stream Processing in Retail E-commerce

I am currently a Engineering Manager at Uber where I am a member of the Hadoop Platform team working on large scale data ingestion and dispersal pipelines and libraries leveraging Apache Spark. I was also previously the tech lead on the metrics team at Uber Maps building data pipelines to produce metrics to help analyze the quality of our mapping data. Before joining Uber, I worked at Twitter as an original member of the Core Storage team building Manhattan, a key/value store powering Twitter's use cases. I love learning anything about storage and data platforms and distributed systems at scale.

• Marmaray: Uber's Open-sourced Generic Hadoop Data Ingestion and Dispersal Framework

Leader of HDFS/ZooKeeper project at Xiaomi, focus on distributed filesystem. 6 years experience on large scale distributed storage system

• Scaling HDFS at Xiaomi

Sanjeev Koranga is leading the PayPal’s instrumentation and analytics platform team. He is responsible for making PayPal’s behavioral analytics self-serve & designing and developing systems for turning data into meaningful insights.

• Real-time Analytics at PayPal

Dave is an Enterprise Software Architect with over twenty-five years of technical leadership in the telecommunications, financial services, and healthcare domains. Dave’s diverse experience ranges from engineering event-based and rule processing systems at “PaaS” (Platform as a Service) scale to building an autonomous-agent workplace simulation engine. At Comcast, Dave is leading the end-to-end ingest, compute, and machine learning pipeline architectures for supporting Customer Experience Big Data applications.

• Event-Driven Messaging and Actions using Apache Flink and Apache NiFi

As VP of Industry Solutions, Cindy Maike is responsible for global industry solutions and customer engagement for Cloudera. She works with customers and partners leveraging analytics for current day business growth and exploring the use of new data sources to drive innovation in the evolving world of insurance. She has over 25 years of finance, consulting and advisory services experience in the insurance industry working with clients globally on their business strategy leveraging analytics and technology to further drive business results.

Cindy has deep industry knowledge in both claims and underwriting with a focus on the use of analytics and data to enhance business outcomes. She has held positions with the IBM Watson Solution Group, Carrier Insurance, Director of Strategy at ACORD, and was co-founder of Strategy Meets Action Research and Advisory Services. Cindy has also held and is a CPA.

She is passionate about solving business problems and eternally believes in process improvement and strongly believes that today's next generation of business intelligence in the form of advanced analytics will revolutionize the insurance industry. Cindy frequently speaks to business events on the value of business analytics, cognitive computing and the evolution of insurance in a connected world.

• Digital Shift in Insurance: How is the Industry Responding with the Influx of Big Data, Analytics and AI?

Nitin Khandelwal is working at Qubole as a Staff Engineer. He has worked in a different arena of projects like adding encrypted communication for ephemeral clusters nodes running in the cloud, providing Hive as a multi-tenant service, Autoscaling, etc. He has been contributing significantly in optimizing Tez engine for ETL workloads by adding features like workload-aware autoscaling, fault-tolerance, effective use of spot nodes, etc.
Previously, Nitin was working with Microsoft on VPN Site-to-site gateway service which forms the backbone of Microsoft Azure Stack's network.

Nitin has completed his Masters in Computer Science from IIIT-Hyderabad. His main areas of focus there were distributed computing, databases and networks.

• Scalable HiveServer2 as a Service

Dr. Zhong Wang is a career computational biologist and group leader for genome analysis at DOE Joint Genome Institute (JGI); he is also an adjunct professor at University of California at Merced. He received his Ph.D. in Cell Biology from Duke University in 2004. He did his postdoc in the Institute of Genome Science and Policy at Duke University before becoming a research scientist at Yale University in 2008. He joined DOE Joint Genome Institute in 2009 and established his independent research in transcriptomics, metagenomics, and big data analytics. Dr. Wang published over 30 high-quality papers including several on Science and Nature. More information about his research can be found at http://jgi.doe.gov/our-science/scientists-jgi/genome-analysis/

• Big Data Genomics: Clustering Billions of DNA Sequences with Apache Spark

Senior Technologist at American Water working on HDP & HDF.

• IoFMT – Internet of Fleet Management Things

Naveen is an Engineering Manager with 7+ Years of Data Engineering, Data Science & Analytics experience across Retail, Finance & Marketing industries. In his current role at WalmartLabs, Naveen leads Walmart's Customer Experience and Store Marketing engineering team and one of his key initiatives in the last few months has been to bring all the various data assets at Walmart under one single data lake platform. He has worked across various database technologies throughout his career and has been extensively working on the entire Hadoop stack at WalmartLabs. Over the past few years, he led several teams building end to end data and visualization platforms and also worked on evaluating and implementing multiple query acceleration and SQL on Hadoop layers such as Druid, LLAP, Spark, Kinetica, SAP HANA etc. to power Walmart's BI platforms.

Speaking & Presentation Experience:
@NWA IISE conference: Topic: 'Data Cafe: Enabling Real Time Insights Through Visualization'
@Bentonville Data Science Meetup: ' Data Cafe: Ask Me Anything - Bot Framework using NLP'

Naveen's work at WalmartLabs was featured on Forbes as one of the "The Most Practical Big Data Use Cases Of 2016" https://www.forbes.com/sites/bernardmarr/2016/08/25/the-most-practical-big-data-use-cases-of-2016/#1a1206531625

• Hive LLAP: A High Performance, Cost-effective Alternative to Traditional MPP Databases

Jeff is a software engineer and cloud architect. He is a committer and PMC on Apache OpenNLP. Jeff currently works on natural language processing pipeline projects and resides outside of Morgantown, WV.

• Improving Organizational Knowledge with Natural Language Processing Enriched Data Pipelines

Akshitha Ramachandran is a junior at Harvard University pursuing a joint degree in both Computer Science and Statistics. She was a founding member and Lead Engineer at Harvard Student Agencies - DEV, a start-up focused on developing mobile and web applications for third party clients. She is both a senior developer and board member at ProMazo, a campus organization partnering top students from leading universities with projects at leading companies ranging from Unilever to Whirlpool. She is on the board of the Harvard College Consulting Group, where as a Vice Director of Consulting she is responsible for the acquisition, organization and execution of eighteen client projects every semester. She directly manages 7 board members who collectively oversee more than 100 members of the organization. Additionally, Akshitha attends Hackathons and has been on the board of Harvard’s Women Engineers Code (WECode) conference.This past summer she spent time at Novetta expanding their Machine Learning practices, specifically in the Named Entity Resolution space. She has contributed to the company’s internal pipeline, designed a demo for them, and published some of her work (https://www.novetta.com/2018/09/named-entity-recognition-and-graph-visualization/ and https://www.novetta.com/2018/08/evaluating-solutions-for-named-entity-recognition/).

• Generating Network Insights Using Named Entity Recognition

Don Bosco Durai (Bosco) is a thought leader in enterprise security and is a committer in open source projects like Apache Ranger, Apache Ambari, and Apache HAWQ. He has also contributed towards the security for most of the Hadoop components. Bosco was the co-founder of XA Secure, which is the genesis of Apache Ranger. Bosco is currently the co-founder of Privacera where he is tackling the data security challenges in modern data architecture, like Big Data and Cloud, where large data set constantly moves between different environments, which can result major security breaches or compliance violation if not managed properly. Privacera automates discovery of sensitive data, does transparent encryption/anonymization, manages access policies and monitors access.

• Securing Data in Hybrid on-premise and Cloud Environments using Apache Ranger