Who will be speaking at Data Day Texas?

The following speakers are confirmed for Data Day Texas 2017. We will be announcing the final 25 speakers over the next few weeks. Don't wait to get your ticket. Take advantage of the advance registration discount.

A list of the NLP Day Speakers can be found here.

A list of the Graph Day Speakers can be found here.

KEYNOTE - Emil Eifrem (SF Bay) @emileifrem

Emil Eifrem (Linkedin) sketched what today is known as the property graph model on a flight to Mumbai in 2000. This sketch grew into the Neo4j project (wikipedia) which, since its initial release in 2007, has been the most known and most widely implemented graph database. Emil is not only co-founder of the Neo4j project, but also co-founder and CEO of Neo Technology - a global organization with offices in San Mateo, Sweden, UK, Germany, and France. It is safe to say that there is no greater evangelist for the graph database space than Emil, and Data Day is honored to have him give the keynote for Data Data TX 2017 - the year of the graph.

John Akred (SF Bay) @BigDataAnalysis

John Akred is the Founder and CTO of Silicon Valley Data Science. In the business world, John Akred likes to help organizations become more data driven. He has over 15 years of experience in machine learning, predictive modeling, and analytical system architecture. His focus is on the intersection of data science tools and techniques; data transport, processing and storage technologies; and the data management strategy and practices that can unlock data driven capabilities for an organization. A frequent speaker at the O'Reilly Strata Conferences, John is host of the perennially popular workshop: Building A Data Platform.
John will also be hosting office hours at Data Day Texas.

Laine Campbell (Santa Cruz) @lainevcampbell

Laine Campbell specializes in database architecture and operations, particularly small to medium data at scale. She is currently authoring the Database Reliability Engineering book at O'Reilly with Charity Majors. Most recently, Laine was the interim CTO at OrderWithMe. Prior, she was founded and led PalominoDB, then Blackbird for 8 years, where her team of DBAs supported many of the most exciting database infrastructures in the industry. Before that, she designed, built and supported the Travelocity databases for 8 years while building and leading the global database services practice. Laine has supported such organizations as Obama for America, Zappos, Chegg, LiveJournal, Disney Mobile, and Adobe. She is an avid advocate for underserved populations in tech, an unabashed ops geek and a lover of open source.
Laine will be holding the following session: Database Reliability Engineering.
While at Data Day, Laine will be holding office hours and signing copies of her upcoming O'Reilly book: Database Reliability Engineering.

Paul Dix (NYC)

Paul Dix is cofounder and CTO of InfluxData, the company behind InfluxDB, the open source time series database. He has helped build software for startups, large companies and organizations like Microsoft, Google, McAfee, Thomson Reuters, and Air Force Space Command. He is the series editor for the Addison Wesley Data and Analytics Series. In 2010 Paul wrote the book Service Oriented Design with Ruby and Rails for Addison Wesley's Professional Ruby series. In 2009 he started the NYC Machine Learning Meetup, which has over 9,000 members. Paul holds a degree in computer science from Columbia University.

Joey Echeverria (SF Bay) @fwiffo

Joey Echeverria is the platform technical lead at Rocana, where he builds applications for scaling IT operations built on the Apache Hadoop platform. Joey is a committer on the Kite SDK, an Apache-licensed data API for the Hadoop ecosystem. Joey was previously a software engineer at Cloudera, where contributed to several ASF projects including Apache Flume, Apache Sqoop, Apache Hadoop, and Apache HBase. Joey is also a coauthor of Hadoop Security, published by O'Reilly Media.


Tim Gasper (Austin) @TimGasper

Tim Gasper is cofounder of Ponos, an IoT-connected, big data hydroponics farming solution that helps you grow fresh vegetables, fruit, and herbs in your own home with a fully automated, indoor smart farm. He is also Director of Product Marketing at Bitfusion, GPU virtualization company for easier, more scalable deep learning. Tim has over eight years of big data, IoT, and enterprise content product management and product marketing experience. He is also a writer and speaker on entrepreneurship, the lean startup methodology, and big data analytics. Previously, Tim was global portfolio manager for CSC Big Data and Analytics, where he was responsible for the overall strategy, roadmap, partnerships, and technology mix for the big data and analytics product portfolio; vice president of product at Infochimps (acquired by CSC), where he led product development for its market-leading open data marketplace and big data platform as a service; and cofounder of Keepstream, a social media analytics and curation company..


Nicholas Gaylord (SF Bay) @texastacos

Nicholas Gaylord is Senior Data Scientist at CrowdFlower, where he helps build out their new machine learning offering, CrowdFlower AI. CrowdFlower AI allows data scientists to construct, monitor, and improve machine learning models using data collected at scale from human contributors via the CrowdFlower platform, in a tightly integrated human-in-the-loop active learning environment. Prior to CrowdFlower, Nick was a data scientist at SF text analytics startup Idibon. He has a PhD from the University of Texas at Austin, where his research focused on human language comprehension and the construction of datasets for NLP applications. In his spare time he fixes bikes and collaborates on work applying cognitive science principles to the public health domain.

(NEW) Pierre Gutierrez (Paris) @prrgutierrez

Pierre Gutierrez is a senior data scientist at the red-hot Paris startup, Dataiku. As a data science expert and consultant, Pierre has worked in diverse sectors such as e-business, retail, insurance or telcos. He has experience in various topics such as fraud detection, bot detection, recommender systems, or churn prediction. Pierre is an experienced Kaggle competitor, and has written about several of his experiences. Pierre will be speaking about transfer learning applications. While at Data Day, Pierre and his colleagues will also be demonstrating the Dataiku collaborative data science platform - Dataiku DSS.


Pierre will be holding the following session: Pragmatic Deep Learning for image labelling. An application to a travel recommendation engine.

(NEW) Brendan Herger (SF Bay) @hergertarian

Brendan Herger leads the Center for Machine Learning at Capital One, where he helps to rethink the way Capital One recruits, hires and empowers Machine Learning practitioners. His experience includes optimizing models for sub-millisecond streaming deployment, leading advanced research projects, and helping teams to balances elegant solutions and highly optimized algorithms..



Juliet Hougland (SF Bay) @JulietHougland

Juliet Hougland is a data scientist at Cloudera, and contributor/committer/maintainer for the Sparkling Pandas project. Her commercial applications of data science include developing predictive maintenance models for oil and gas pipelines at Deep Signal, and designing/building a platform for real-time model application, data storage, and model building at WibiData. Juliet was the technical editor for Learning Spark by Karau et al. and Advanced Analytics with Spark by Ryza et al. She holds an M.S. in applied mathematics from the University of Colorado, Boulder and graduated Phi Beta Kappa from Reed College with a BA in math-physics..

Juliet will be holding the following session: How to Observe: Lessons from Epidemiologists, Actuaries and Charlatans.

Holden Karau (San Francisco) @holdenkarau

Holden Karau is a software development engineer and is active in open source. She a co-author of Learning Spark & Fast Data Processing with Spark and has taught intro Spark workshops. Prior to IBM she worked on a variety of big data, search, and classification problems at Alpine, DataBricks, Google, Foursquare, and Amazon. She graduated from the University of Waterloo with a Bachelors of Mathematics in Computer Science. Outside of computers she enjoys dancing & playing with fire.
Holden will be holding the following session: Extending Spark Machine Learning - Adding your own algorithms & tools.
Check out the recent Global Data Geeks interview with Holden Karau.
While at Data Day, Holden will be holding office hours and signing copies of her O'Reilly book: High Performance Spark.

Alex Korbonits (Seattle) @korbonits

Alex Korbonits is a Data Scientist at Remitly, Inc., where he works extensively on feature extraction and putting machine learning models into production. Outside of work, he loves Kaggle competitions, is diving deep into topological data analysis, and is exploring machine learning on GPUs. Alex is a graduate of the University of Chicago with degrees in Mathematics and Economics.
Alex Korbonit's session: Distilling dark knowledge from neural networks.



Dor Laor (Sunnyville, CA) @dorlaor

Dor Laor is the CEO of ScyllaDB, the company behind the open source Cassandra-compatible database of the same name. Previously, Dor was part of the founding team of the KVM hypervisor under Qumranet that was acquired by Red Hat. At Red Hat Dor was managing the KVM and Xen development for several years. Dor holds an MSc from the Technion and a Phd in snowboarding.



(NEW) - Patrick McFadin (SF Bay)

Patrick McFadin is regarded as one of the foremost experts of Apache Cassandra and data modeling techniques. As the Chief Evangelist for Apache Cassandra and consultant for DataStax, he has helped build some of the largest deployments in the world. Previous to DataStax, he was Chief Architect at Hobsons, an education services company. There, he spoke often on web application design and performance.
Twitter: @patrickmcfadin


Ryan Mitchell (Somerville, MA) @Kludgist

Ryan Mitchell (Linkedin) is a senior software engineer at HedgeServ , She received her master's in software engineering from Harvard University, Extension School, and a bachelor's in Engineering at Olin College of Engineering. Prior to joining HedgeServ, Ryan was a Software Engineer building web scrapers and bots at Abine Inc. Ryan is the author of two books about web scraping: Web Scraping with Python (O’Reilly, 2015), and Instant Instant Web Scraping with Java (Packt, 2013), as well as an upcoming O’Reilly video series: Web Crawling with Python.
In addition to speaking at past Data Day events in both Seattle and Austin, Ryan gives talks and runs workshops around the country, including an upcoming 8 week web development course through the Boston Public Library this fall.

Jonathon Morgan (Austin) @jonathonmorgan

Jonathon Morgan (Linkedin) is Founder and CEO at New Knowledge. a company building technologies to understand and predict human behavior. As part of his ongoing work applying quantitative methods to combating violent extremism, he served as an advisor to the White House and State Department, co-authored the ISIS Twitter Census for the Brookings Institution, and develops new technology with DARPA. Jonathon is also the co-host of Partially Derivative, an unrealistically popular podcast about data science and drinking.
Jonathon will be giving the following presentation: Truth is Dead


(NEW) - Stephen O'Sullivan (SF Bay) @steveos

Stephen O'Sullivan is the VP of Engineering at Silicon Valley Data Science, where he leads data architecture and infrastructure. A veteran of WalmartLabs, Sun and Yahoo! with over 20 years of experience creating scalable, high-availability, data and applications solutions, Stephen is leading expert on big data architecture and Hadoop.
Stephen will also be hosting office hours at Data Day Texas.


(NEW) - Nelson Ray (SF Bay)

Nelson Ray manages the Risk Science group at Opendoor in San Francisco. His team is responsible for pricing the fee for Opendoor's home buying service and for optimizing resale strategy using a variety of machine learning models and experimental techniques. Prior to joining Opendoor, Nelson was a data scientist at Google and a software engineer at Metamarkets. He holds a BS in mathematics and an MS and PhD in statistics from Stanford University.
Nelson will be giving the following presentation: When A/B Testing Fails: A Case Study in Real Estate


Melissa Santos (Portland) @ansate

Melissa Santos has over a decade of experience working with data, from ETLs and reporting to Hadoop clusters and marketing analytics. In her previous role as Engineering Manager of Etsy, she led her team from being a Hadoop Infrastructure team that was constantly fixing problems and cleaning up messes, to declaring themselves to be a Data Platform team, expanding into investigating new tools, teaching coworkers about big data, and consulting with other teams about how to meet their data needs. Favorite past projects include implementing a beta-binomial model in SAS, creating neighborhood boundaries from Flickr and OpenStreetMap data, using principal components analysis to detect spam emails, and teaching coworkers to write Scalding jobs. Melissa's professional goal is to make data more accessible to all parts of the business, and to businesses of every size. She has a PhD in Applied Math and is currently the (sole) Data Scientist for Big Cartel.
Melissa will be giving the following presentation: Distances, Similarities, and Scores: Practical Model Examples

Eric Tschetter (San Francisco)@zedruid

Eric Tschetter Eric Tschetter started the Druid project, an open source, real-time analytical data store. Eric currently works as a distinguished engineer at Yahoo, where he endeavors to speed up analytics with a mix of data science and traditional BI. Eric previously worked with diabetes data at Tidepool, a nonprofit, was the VP of engineering and lead architect at Metamarkets, and has held senior engineering positions at Ning and LinkedIn. He holds bachelor’s degrees in computer science and Japanese from the University of Texas at Austin and an MS in computer science from the University of Tokyo.
Eric will be giving the following presentation: Sampling is always Bad, approximate the Good way with Sketches


Michelle Casbon (San Antonio) @texasmichelle

Michelle Casbon is Director of Data Science at Qordoba. Previously, she was a Senior Data Science Engineer at Idibon, where she contributed to the goal of bringing language technologies to all the world’s languages. Michelle's development experience spans a decade across various industries, including media, investment banking, healthcare, retail, and geospatial services. Michelle completed a Masters at the University of Cambridge, focusing on NLP, speech recognition, speech synthesis, and machine translation. She loves working with open source technologies and has had a blast contributing to the Apache Spark project. Holding technical conversations and learning from the people she meets is her favorite part of Data Day.
Michelle will be giving the following presentation: Untangling the Ball of Strings: Machine Learning for Localization
Check out our interview with Michelle Casbon.

NLP Day Speakers

(NEW) - Sanghamitra Deb (SF Bay) @sangha_deb

Sanghamitra Deb is a Data Scientist at Accenture Technology Laboratory. As a data scientist at a Accenture she has worked on a wide variety of problems related data modeling, architecture and visual story telling. She has also worked in multiple data roles in different projects. Her primary focus is application of Natural Language Processing and Machine Learning to enterprise data. She is active in Data Science outreach and believes in applying analytics to a range of domains such as pharma, HR, customer support, market research, etc. Prior to being data scientist she was an astrophysicist who studied the structure of the universe by modeling galaxy clusters.
Sanghamitra will be holding the following session: Creating Knowledgebases from text in absence of training data.

Jason Kessler (Seattle) @ jasonkessler

Jason Kessler is a data scientist at CDK Global, where he analyses language use and consumer behavior in the online auto-shopping ecosystem. Prior to joining CDK, Jason was the founding data scientist at PlaceIQ and worked as a research scientist for JD Power and Associates. He has published peer-reviewed papers on algorithms and corpora for sentiment and belief analysis, and has sat on program committees and reviewed for several AI and NLP conferences. Most recently, he has delivered talks on the identification of persuasive and influential language language to the 2015 Sentiment Symposium and Data Day Seattle 2016.

Stefan Krawczyk (San Francisco) @stefkrawczyk

Stefan Krawczyk loves the stimulus of working at the intersection of design, engineering, and data. He spent formative years at Stanford, LinkedIn, Nextdoor & Idibon, working on everything from growth engineering, product engineering, data engineering, to recommendation systems, NLP, data science and business intelligence. At Stitch Fix he’s leading development of the algorithm development platform.
Stefan Krawczyk will be appearing as part of NLP Day Texas.


Rob McDaniel (Seattle)

Rob McDaniel is a data scientist at LiveStories, a Seattle-based startup developing a storytelling and analysis platform for the public sector. He enjoys working on semantic text analysis, data mining and classification problems. Previously, he has developed clustering and classification models for product and job description taxonomies, created a prototype bias-detection algorithm for news articles, and built entity extraction pipelines. At LiveStories, Rob is creating a public data graph by mining semantic networks between open data on the web, and providing a platform to answer natural language queries about them on a wide variety of public issues, such as health and education.

Rob will be holding the following session: Bootstrapping a corpus: how to build a rich topic library from a handful of words.

Gabor Melli (San Francisco) @gmelli

Gabor Melli is the Director of Data Science at OpenGov where he leads their initiatives to automate knowledge-intensive text-rich processes. This work largely involves the training of predictive models for classification, sequence labeling, and estimation for tasks such as named entity recognition and disambiguation in user generated text using techniques and tools such as: CRFs, SVMs, HMMs, Logistic, LDA, NLTK, Spark, Python, R, and AWS' EC2/S3/EMR. He has led and delivered large-scale data-driven initiatives at organizations ranging from Microsoft, AT&T, T-Mobile, ICBC, Washington Mutual, and Wal*Mart to start-ups such as Datasage, Meals.com, PredictionWorks, VigLink and now at OpenGov.
Gabor holds a PhD in Computing Science from Simon Fraser University in the topic of document to ontology interlinking. He has been active in the data science community for over twenty years and is the recipient ACM SIGKDD's Service Award in 2013. His current research interest include iterative semantic semi-supervised text analysis and automated business process optimization.
Gabor Melli will be appearing as part of NLP Day Texas.


Jonathan Mugan (Austin) @jmugan

Jonathan Mugan (Linkedin) is Co-Founder and CEO at DeepGrammar. Dr. Mugan specializes in artificial intelligence and machine learning. His current research focuses in the area of deep learning, where he seeks to allow computers to acquire abstract representations that enable them to capture subtleties of meaning. Dr. Mugan received his Ph.D. in Computer Science from the University of Texas at Austin. His thesis was centered in developmental robotics, which is an area of research that seeks to understand how robots can learn about the world in the same way that human children do. Dr. Mugan also held a post-doctoral position at Carnegie Mellon University, where he worked at the intersection of machine learning and human-computer interaction. He is also the author of The Curiosity Cycle: Preparing Your Child for the Ongoing Technological Explosion.
Jonathan will be holding the following NLP Day session: How to Progress from NLP to Artificial Intelligence.

(NEW) Jacob Su Wang (Austin)

Jacob Su Wang works as a data scientist at OJO Labs. Inc., an Austin-based artificial intelligence startup, and is currently a second-year graduate student at the Department of Linguistics at the University of Texas at Austin, where he specializes in Computational Linguistics. Jacob now serves as a research assistant for Dr. Katrin Erk at UT, working on distributional semantics and Bayesian Hierarchical Models, with which he explores how humans can learn and use words appropriately with very little experiential exposure.
Before working at OJO, Jacob studied general linguistics (CS minor) and applied linguistics at the University at Buffalo (SUNY) and Yunnan University (China), before graduating with two M.A.s in linguistics. He also holds a B.S. in Informatics.
Jacob will be holding the following session: Exploring Modeling Methods in Named Entity Recognition.

Graph Day Speakers

Graph Day will be held on the first floor of the conference facility, concurrent with Data Day Texas. Your Data Day Texas ticket gets you into all of the Graph Day sessions. Below is a list of the Graph Day speakers confirmed so far. For a list of confirmed sessions, visit the Graph Day Sessions page.

(NEW) - Dave Bechberger (Houston)

Dave Bechberger is an Architect at Expero, a custom software development company building innovative solutions for domain experts across a variety of industries, from geophysicists to supply chain planners. He has spent 2016 building graph solutions for a variety of customers, and come to know the good, the bad, and the ugly of this technology platform.
Dave Bechberger will present the following talk: Moving Your Data To Graph.


Ryan Boyd (SF Bay)

Ryan Body (Linkedin) is a SF-based software engineer focused on helping developers understand the power of graph databases. Previously he was a product manager for architectural software, built applications and web hosting environments for higher education, and worked in developer relations for twenty products during his 8 years at Google. He enjoys cycling, sailing, skydiving, and many other adventures when not in front of his computer.



Arnaud De Moissac (Paris)

Arnaud De Moissac (Linkedin) is co-founder of DCbrain, an enterprise scale IoT startup, focused on delivering real time intelligence to multi physical network (energy, cooling, ...) by modeling flows. Arnaud has 10 years of experience in telco and IT networks, and hold several patents. He also worked during 5 years in the energy efficiency area. He holds two masters degree, in electrical engineering and IT architecture
Arnaud De Moissacr will be appearing as part of Graph Day 2017.


(NEW) - Alex Dimakis (Austin) @alexb80

Alex Dimakis (linkedin) is an Associate Professor in the Dept. of Electrical and Computer Engineering at the University of Texas. He is also a member of the Wireless Networking and Communications Group and the Computer Science Graduate Studies Committee. Alex's interests include information theory, coding theory, and machine learning.
Alex's recent publications include: Beyond Triangles: A Distributed Framework for Estimating 3-profiles of Large Graphs and Batch Codes through Dense Graphs with High Girth. For a list of publications, view Alex's homepage at UT.
Alex Dimakis will be appearing as part of Graph Day 2017.

Luca Garulli (London, UK) @lgarulli

Luca Garulli is the CEO and Founder of OrientDB, and the original author of OrientDB. Luca started working with storage algorithms in 1998 and created the first production-ready version of OrientDB in early 2010 after 17 years of experience working with other DBMSs. Luca is a member of the Sun Microsystems JDO 1.0 and 2.0 Expert Groups that wrote the JDO standard. He has also published various tech articles in Technet, Computer Programming, IoProgrammer, and Week.it magazines.
Luca Garulli will be presenting the following session: Graph Databases: What's Next?.



Dr. Denise Koessler Gosnell (Charleston) @DeniseKGosnell

Dr. Denise Gosnell, a driving member of the PokitDok Data Science team since 2014, has brought her research in applied graph theory to help architect the graph database while also serving as an analytics thought leader. Her work with the Data Science team aims to extract insight from the trenches of hidden data in healthcare and build products to bring the industry into the 21st century. She has represented PokitDok's Data Science Team at numerous conferences including, PyData, KDD (Knowledge Discovery & Data Mining) and the inaugural GraphDay.
Prior to PokitDok, Dr. Gosnell earned her Ph.D. in Computer Science from the University of Tennessee. Her research on how our online interactions leave behind unique identifiers that form a “social fingerprint” led to presentations at major conferences from San Diego to London and drew the interest of such tech industry giants as Microsoft Research and Apple. Additionally, she was a leader in addressing the underrepresentation of women in her field and founded a branch of Sheryl Sandberg's Lean In Circles.

Denise Gosnell will present the following talk: Graphs vs. Tables: Ready, Fight!..

(NEW) - Borislav Iordanov (Hollywood, Florida) @ bolerio

Borislav Iordanov Borislav Iordanov is currently the VP of Engineering at Grakn Labs, an open source knowledge graph. He is also an entrepreneur and independent researcher. Under his leadership, he has lead a number of a commercial and open-source projects, including founding the innovative, one of a kind NoSQL database HyperGraphDB. Over a period of an 8 year involvement in e-government at Miami-Dade County, several of his initiatives led to nationwide recognition: Best Integrator from the Center for Digital Government for semantic publishing and search; Florida Sterling Innovations Award for PKBI, a content management tool blending text with a formal ontology for contextualized multi-channel delivery; NACo Achievement Award from the National Association of Counties for the Economic Service Bot, an autonomous virtual agent for self-servicing of new local small businesses; finally, the ontology-driven OpenCiRM platform powering the Miami-Dade 311 call center, architected by Mr. Iordanov and implemented under his lead, achieved recognition as semi-finalist in the 2015 Innovations in American Governments Awards Program from the Harvard Kennedy School Ash Center.
Borislav Iordanov will be presenting the following session: Large Scale Graph Analytics Through Graql.


Kisung Kim @kskim_kim

Kisung Kim is CTO of Bitnine Global Inc. Kisung Kim is a chief architect and developer of Agens Graph, which is a new graph database based on PostgreSQL. Before joining Bitnine he worked for 5 years in Tmaxsoft for developing relational database engine in Korea.
Kisung Kim will present the following talk: Graph Database Implementation on PostgreSQL.



(NEW) - Chris LaCava @uxchrislacava

Chris LaCava has spent the past two decades defining, designing and building software for a variety of industry verticals. He has experience as a usability engineer, interaction designer, front-end developer as well as product manager for both consulting and product-oriented organizations. Chris leads Expero's efforts in defining visualization for graph datasets.
Chris LaCava will present the following talk: Meaningful User Experience with Graph Data.


Corey Lanum (Boston) @corey_lanum

Corey Lanum, has a distinguished background in graph visualization. Over the last 15 years he has managed technical and business relationships with dozens of the largest defense and intelligence agencies in North America, in addition to working with many security and anti-fraud organizations in private industry. Prior to joining Cambridge Intelligence as their US Manager, Corey was helping the customers of i2 (now IBM) and SS8 to solve their most complex graph data challenges. Corey is the author the Learning Graph Visualization from Manning Publications.
Corey will present the following talk: Graphs in time and space: A visual example/a>.

William Lyon (SFBay) @lyonwj

William Lyon is a software developer at Neo4j, the open source graph database. As an engineer on the Developer Relations team, he works primarily on integrating Neo4j with other technologies, building demo apps, helping other developers build applications with Neo4j, and writing documentation. Prior to joining Neo, William worked as a software developer for several startups in the real estate software, quantitative finance, and predictive API fields. William holds a Masters degree in Computer Science from the University of Montana. You can find him online at lyonwj.com
William will be presenting the following session: Neo4j Graph Database Workshop For The Data Scientist Using Python. (90 minutes).

(NEW) - Alaa Mahmoud (Boston)

Alaa Mahmoud is a full-stack software developer with more than 25 years of experience, about 20 of those years are with IBM. He started his career focusing on software i18n. He moved on to work on various technologies such as web development, e-commerce and Customer Analytics software. Currently, Alaa is the dev lead for a team that's putting a Tinkerpop 3 based database on the cloud (IBM Graph). Alaa is also a master inventor with several granted patents. Check out Alaa's recent interview on Linux.com
Alaa will be presenting the following session: Building a Graph Database in the Cloud: challenges and advantages.


(NEW) - David Mizell (Austin)

David Mizell is a technical project lead at Cray, Inc. He started out his career doing parallel computing research, primarily at the Information Sciences Institute in Los Angeles. When the funding for that dried up, he moved to Seattle and Boeing. There he worked on Augmented Reality and Virtual Reality systems, doing some of the earliest prototyping of Augmented Reality systems and wearable computers. When the funding for that dried up, he joined Cray and resumed parallel computing research. Having finally found a stable source of research funding, he promptly worked himself out of it by prototyping a graph database system that Cray decided to productize. He now leads the development of Cray’s graph database product, the Cray Graph Engine. Currently he’s based in Cray’s Austin office.
David Mizell will be presenting the following session: LEBM: Making a Thoroughly Nasty Graph Database Benchmark.


Mo Patel (Austin) @mopatel

Mo Patel is a Senior Data Scientist at Think Big, A Teradata Company. Mo mentors clients across Americas on topics of Machine Learning, Data Science, Data Engineering and Artificial Intelligence. These mentoring engagements range from helping clients build large scale streaming analytics solution for deriving business value from sensor data to helping clients reduce customer churn and improve product stickiness via graph analytics. Mo is constantly evaluating the rapidly changing landscape of analytic libraries, tools, methods and frameworks in order to separate hype from reality for his clients. Current research interests are Sensor Data, Low-Latency Analytics, Deep Learning and Artificial Intelligence.
Mo has a Masters in Computer Science from Brandeis University, Bachelors in Math & Computer Science from College of the Holy Cross and MBA from Georgetown University. Mo is a Boston native, living in Austin and loves snow sports (not in Austin) and in order to maintain that addiction exercises and spends time outdoors (in Austin).
Mo Patel will be appearing as part of Graph Day 2017.

Josh Perryman (Bryan / College Station) @joshperryman

Josh Perryman likes to play with data. Oftentimes this is implementing proprietary algorithms closer to the data for performance or scale. Sometimes it is ad-hoc investigation and analysis, a sort of exploratory querying. A few times he’s been able to leverage his experience with data engines for dramatic performance improvements. But the real joy is designing a schema for both functionality and performance, one which increases the productivity of other developers and enables a technology to solve new problems or deliver new value to the business.
But technology isn't just data, and he does more than just play with data. He’s worked with high performance computing (HPC) environments, taking computations from hours to minutes or seconds. He has built visualizations which deliver new insights into complex data domains. He’s managed technology personnel, both directly and indirectly, to deliver technology solutions. He’s have put together more types of technology components, software and hardware, than can be counted, because one of his fortes is solving problems by building sustainable systems.
Josh Perryman will be offering a Friday afternoon workshop: Hands-on Introduction to the Gremlin Graph Query Language. Registration is at Eventbrite.

Jason Plurad (Raleigh-Durham) @pluradj

Jason Plurad is a software developer on IBM's Open Technologies team. He is a committer on Apache TinkerPop, an open source graph computing framework. Jason engages in full stack development (including front end, web tier, NoSQL databases, and big data analytics) and promotes adoption of open source technologies into enterprise applications, service, and solutions. He has spoken previously at IBM conferences (Innovate, Insight) and Triangle Hadoop Users Group meetups.



(NEW) - Haikal Pribadi (London) @ haikalpribadi

Haikal Pribadi is the Founder of GRAKN.AI, a distributed knowledge graph. His interest in AI began in at the Monash Intelligent Systems Lab, where he created an open source driver for the Parallax Eddie Robot which allows user interaction through gesture and speech and was then adopted by NASA for research. He graduated top of his class in Computer Science at Monash University and obtained a masters degree in AI at the University of Cambridge on a full scholarship. Haikal then joined Quintiq as the youngest Algorithm Expert behind their Optimisation Technology R&D that helped schedulings of world’s largest companies. He now works on Grakn and Graql, the graph query language for deep network data.
Haikal Pribadi will be presenting the following session: How to Work with Large and Complex Graphs.


Juan Sequeda (Austin) @juansequeda

Dr. Juan Sequeda is the co-founder of Capsenta and the developer of Ultrawrap, a system that virtualizes relational databases as graph data sources. His research interests are on the intersection of Logic and Data and in particular between the Semantic Web and Relational Databases for data integration. Juan holds a Ph.D. in Computer Science from the University of Texas at Austin. Capsenta is a spin-off from his PhD research. Juan is the recipient of the NSF Graduate Research Fellowship, Best Student Paper at the 2014 International Semantic Web Conference, and 2nd Place in the 2013 Semantic Web Challenge for his work on ConstituteProject.org. Juan is on the editorial board of the Journal of Web Semantics and has been an invited expert member and standards editor for the World Wide Web Consortium (W3C) Relational Database to RDF Graph working group.
Juan Sequeda will be appearing as part of Graph Day 2017.
Check out our recent interview with Juan Sequeda.

(NEW) - Gergely Svigruha

Gergely Svigruha is a software engineer / data analyst at Lynx Analytics. He has participated in both the development and application of Lynx Analytics’ Big Data graph platform. He deployed Lynx’s software for telecommunication and banking clients across South East Asia. He developed a specialty in social network analysis while working on demography estimation and churn prediction models. Prior to Lynx he worked as a software engineer for Google in Munich.
Gergely Svigruha will be presenting the following session: Demography Estimation on a Large Telco Graph – a Case Study.

(NEW) - Andrew Therriault (Boston) @therriaultphd

Andrew Therriault was named as the City of Boston's first Chief Data Officer in 2016. His team uses data science to address some of the city's most challenging problems, from homelessness and addiction to food-borne illness and traffic safety. An expert on predictive modeling, quantitative research, and data integration, Therriault previously served as Director of Data Science for the Democratic National Committee and as editor of Data and Democracy: How Political Data Science Is Shaping the 2016 Elections (O'Reilly Media). He received his PhD in political science from New York University in 2011 and completed a postdoctoral research fellowship at Vanderbilt.
Andrew will be presenting the following session: Saving the World with Data.



(NEW) - Ted Wilmes @trwilmes

Ted Wilmes is passionate about learning complex systems top to bottom and he enjoys applying this knowledge to help customers with their data architecture and performance tuning needs. Over the past few years he has been involved in the rapidly growing graph database space and is an active committer and PMC member on the Apache TinkerPop project.
Ted Wilmes will be presenting the following session: Implementing Network Algorithms in TinkerPop's GraphComputer.





Chris Moody of Stitch Fix taking the audience in the weeds with recent NLP techniques at DDTX16.


Spark contributor Holden Karau packs the room at DDTX16.