Meet the Community

We're headed back home to host our first H2O World San Francisco!

Join the greatest minds in AI and data science for this 2-day interactive event packed with deep-dive technical sessions, talks on real-world business use cases and a hands-on training. You'll discover the strategies and insights you need to optimize and transform your business and prepare for the wave of AI.

H2O World San Francisco is a must-attend event whether you're a newbie getting your toes wet, or an H2O power user. You'll get to network with industry trailblazers and peers that are shaping the future of AI and machine learning.

KeynoteSpeakers

SriSatish Ambati
SriSatish Ambati

Bio: SriSatish Ambati is the CEO and Co-Founder of H2O.ai – makers of H2O, the leading open source machine learning platform and Driverless AI, which speeds up data science workflows by automating feature engineering, model tuning, ensembling and model deployment.

Sri is known for envisioning killer apps in fast evolving spaces and assembling stellar teams towards productizing that vision. A regular speaker in the Big Data, NoSQL and Java circuit, Sri leaves a trail @srisatish.

Linkedin: https://www.linkedin.com/in/srisatishambati/

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Tanya Berger Wolf
Tanya Berger Wolf
AI and Humans Combatting Extinction Together

Abstract: Photographs, taken by field scientists, tourists, automated cameras, and incidental photographers, are the most abundant source of data on wildlife today. Wildbook, a project of tech for conservation non-profit Wild Me, is an autonomous computational system that starts from massive collections of images and, by detecting various species of animals and identifying individuals, combined with sophisticated data management, turns them into high resolution information database, enabling scientific inquiry, conservation, and citizen science. We have built Wildbooks for over 20 species of animals, including whales (flukebook.org), sharks (whaleshark.org), giraffes (giraffespotter.org), and, with H2O.ai's help, working on elephants. In January 2016, Wildbook enabled the first ever full species (the endangered Grevy's zebra) census using photographs taken by ordinary citizens in Kenya.The resulting numbers are now the official species census used by IUCN Red List and we repeated the effort in 2018, becoming the first certified census from an outside organization accepted by the Kenyan government. Wildbook is becoming the data foundation for wildlife science, conservation, and policy. Read more: Fast Company(TM) article

Bio: Berger-Wolf is a Professor of Computer Science at UIC, where she heads the Computational Population Biology Lab, and a co-founder of machine learning for wildlife conservation tech Wildbook, a project of WildMe.org, which she directs. Berger-Wolf holds a Ph.D. from the University of Illinois at Urbana-Champaign. She has received numerous awards for her research and mentoring, including the US National Science Foundation CAREER Award, Association for Women in Science Chicago Innovator Award, and the UIC Mentor of the Year Award.

Linkedin: https://www.linkedin.com/in/tanyabw/

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Gary Rapsey
Dan Rubenstein

Abstract: Photographs, taken by field scientists, tourists, automated cameras, and incidental photographers, are the most abundant source of data on wildlife today. Wildbook, a project of tech for conservation non-profit Wild Me, is an autonomous computational system that starts from massive collections of images and, by detecting various species of animals and identifying individuals, combined with sophisticated data management, turns them into high resolution information database, enabling scientific inquiry, conservation, and citizen science. We have built Wildbooks for over 20 species of animals, including whales (flukebook.org), sharks (whaleshark.org), giraffes (giraffespotter.org), and, with H2O.ai's help, working on elephants. In January 2016, Wildbook enabled the first ever full species (the endangered Grevy's zebra) census using photographs taken by ordinary citizens in Kenya.The resulting numbers are now the official species census used by IUCN Red List and we repeated the effort in 2018, becoming the first certified census from an outside organization accepted by the Kenyan government. Wildbook is becoming the data foundation for wildlife science, conservation, and policy. Read more: Fast Company(TM) article

Linkedin: https://www.linkedin.com/in/daniel-rubenstein-4676714/

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Dean Stoecker
Dean Stoecker

Bio:Dean Stoecker is Chairman and Chief Executive Officer, and a founding partner of Alteryx, revolutionizing business through data science and analytics. Dean's leadership and motivational skills, along with his ability to create, communicate and realize a vision, are a driving force behind bringing back the thrill of solving to analysts and data scientists across the globe.

Linkedin: https://www.linkedin.com/in/dean-stoecker-298010a/

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SessionSpeakers

Erin Ledell
Erin Ledell Chief Machine Learning Scientist, H2O.ai
Erin Ledell

Bio: .Erin is the Chief Machine Learning Scientist at H2O.ai. Erin has a Ph.D. in Biostatistics with a Designated Emphasis in Computational Science and Engineering from University of California, Berkeley. Her research focuses on automatic machine learning, ensemble machine learning and statistical computing. She also holds a B.S. and M.A. in Mathematics.

Before joining H2O.ai, she was the Principal Data Scientist at Wise.io (acquired by GE Digital in 2016) and Marvin Mobile Security (acquired by Veracode in 2012), and the founder of DataScientific, Inc.

Linkedin: https://www.linkedin.com/in/erin-ledell/

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Arno Candel
Arno Candel CTO, H2O.ai
Arno Candel

Bio: Arno Candel is the Chief Technology Officer at H2O.ai. He is the main committer of H2O-3 and Driverless AI and has been designing and implementing high-performance machine-learning algorithms since 2012. Previously, he spent a decade in supercomputing at ETH and SLAC and collaborated with CERN on next-generation particle accelerators.

Arno holds a PhD and Masters summa cum laude in Physics from ETH Zurich, Switzerland. He was named “2014 Big Data All-Star” by Fortune Magazine and featured by ETH GLOBE in 2015. Follow him on Twitter: @ArnoCandel.

Linkedin: https://www.linkedin.com/in/candel/

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Marios Michalidis
Marios Michalidis Kaggle Grandmaster, Competitive Data Scientist, H2O.ai
Marios Michalidis

Bio: Marios Michailidis is a Competitive Data Scientist at H2O.ai. He holds a Bsc in accounting Finance from the University of Macedonia in Greece, an Msc in Risk Management from the University of Southampton and a PhD in machine learning at from UCL . He has worked in both marketing and credit sectors in the UK Market and has led many analytics’ projects with various themes including: acquisition, retention, recommenders, fraud detection, portfolio optimization and more. He is the creator of KazAnova, a freeware GUI for credit scoring and data mining 100% made in Java as well as is the creator of StackNet Meta-Modelling Framework. In his spare time he loves competing on data science challenges and was ranked 1st out of 500,000 members in the popular Kaggle.com data competition platform. He currently ranks 3rd.

Linkedin: https://www.linkedin.com/in/mariosmichailidis/

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Branden Mmurray
Branden Murray Kaggle Grandmaster, Customer Data Scientist, H2O.ai
Branden Murray

Bio: Kaggle Grandmaster Branden is a customer data scientist at H2O.ai and holds a B.S. in Finance from the San Diego State University. Among his favorite hobbies is participating in predictive analytics competitions primarily on Kaggle.com. Currently, he is ranked 58th among Grandmasters globally and has stood in the top 10% 8 times among all the competitions he participated on Kaggle. Branden is on the team of data scientists from H2O.ai behind PwC’s Audit Innovation of the Year title. They have collectively developed PwC’s Audit.ai - a revolutionary bot that does what humans can’t. Its AI analyses billions of different data points in seconds and applies judgement to detect anomalies in general ledger transactions.

Linkedin: https://www.linkedin.com/in/bmurr26/

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Sudalai Rajkumar
Sudalai Rajkumar Kaggle Grandmaster, Data Scientist, H2O.ai
Sudalai Rajkumar

Bio: Sudalai Rajkumar (aka SRK) is a Senior Data Scientist at H2O.ai Inc, building Driverless AI, an automated machine learning platform. Prior to this, he was with Freshworks, Tiger Analytics and Global Analytics. He has more than 8 years of experience in the DS / ML field and solved a lot of interesting data science problems for various customers across the globe. Apart from his day job, he takes part in various data science competitions to enhance his knowledge and has won several of them. He is a Kaggle Grandmaster in Competitions & Kernels section. He is ranked #1 on Analytics Vidhya platform as well.

Linkedin: https://www.linkedin.com/in/sudalairajkumar/

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Mathias Mueller
Mathias Mueller Kaggle Grandmaster, Data Scientist, H2O.ai
Mathias Mueller

Bio: A Kaggle Grandmaster and a Data Scientist at H2O.ai, Mathias Müller holds an AI and ML focused diploma (eq. M.Sc.) in computer science from Humboldt University in Berlin. During his studies, he keenly worked on computer vision in the context of bio-inspired visual navigation of autonomous flying quadrocopters. Prior to H2O.ai, he as a machine learning engineer for FSD Fahrzeugsystemdaten GmbH in the automotive sector. His stint with Kaggle was a chance encounter as he stumbled upon the data competition platform while looking for a more ML-focused platform as compared to TopCoder. This is where he entered his first predictive modeling competition and climbed up the ladder to be a Grandmaster. He is an active contributor to XGBoost and is working on Driverless AI with H2O.ai.

Linkedin: https://www.linkedin.com/in/muellermat/

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Dmitry Larko
Dmitry Larko Kaggle Grandmaster, Senior Data Scientist, H2O.ai
Dmitry Larko

Bio: Senior Data Scientist at H2O.ai, Dmitry Larko also is a former #25 Kaggle Grandmaster and loves to use his machine learning and data science skills in Kaggle Competitions and predictive analytics software development. He has more than 15 years of experience in information technology. Post his masters in computer information systems from Krasnoyarsk State Technical University (KSTU), he started his career in data warehousing and business intelligence and gradually moved to big data and data science. He holds a lot of experience in predictive analytics in a wide array of domains and tasks. Prior to H2O.ai, Dmitry held the position of SAP BW Developer at Chevron, Data Scientist at EPAM, and that of Lead Software Engineer with the Russian Federation.

Linkedin: https://www.linkedin.com/in/dlarko/

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Martin Stein
Martin Stein Chief Analytics Officer, G5
Martin Stein
Driving Marketing Performance with H2O Driverless AI

Linkedin: https://www.linkedin.com/in/steinmartin/

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Tess Posner
Tess Gilman Posner CEO, AI4ALL
Tess Gilman Posner
Diverse and Inclusive AI

Artificial intelligence could contribute an additional 1.2% to annual gross domestic product growth over the next decade, according to a recent McKinsey report. The report also predicts that about 70% of companies will adopt at least one form of AI by 2030. As AI goes full steam ahead, it's critical to ask the right questions while still in early stages: who is building and shaping this important technology? Research shows that the AI field doesn’t adequately reflect the broader population, which suggests that globally, we’re missing out on the value that diverse teams bring to AI development, implementation, and research. For example, in the US only 13% of AI CEOs are women, and only 2.6% of tenure-track engineering faculty identify as African American and only 3.6% identify as Hispanic. When diverse voices are left out of AI, the reliability and fairness of AI systems come into question.

Bio: Tess Posner is the CEO of AI4ALL, where she works to make artificial intelligence more diverse and inclusive and to ensure that AI is developed responsibly. Previously, she was Managing Director of TechHire, a national initiative launched out of the White House to increase diversity in the tech economy. Tess’s work has been featured by the Wall Street Journal, the Atlantic, Business Insider, TechCrunch, and Fast Company and funded by top national foundations and influencers including Melinda Gates, Jensen Huang, Google.org, JPMorgan Chase Foundation, Autodesk and the Robin Hood Foundation.

Linkedin: https://www.linkedin.com/in/tessposner/

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Patrick Hall
Patrick Hall Senior Director - Products, H2O.ai
Patrick Hall
Human-Friendly Machine Learning

This presentation illustrates how to combine innovations from several sub-disciplines of machine learning research to train understandable, fair, trustable, and accurate predictive modeling systems. Techniques from research into fair models, directly interpretable Bayesian or constrained machine learning models, and post-hoc explanations can be used to train transparent, fair, and accurate models and make nearly every aspect of their behavior understandable and accountable to human users. Additional techniques from fairness research can be used to check for sociological bias in model predictions and to preprocess data and post-process predictions to ensure the fairness of predictive models. Finally, applying new testing and debugging techniques, often inspired by best practices in software engineering, can increase the trustworthiness of model predictions on unseen data. Together these techniques create a new and truly human-friendly type of machine learning suitable for use in business- and life-critical decision support.

Patrick Hall is senior director for data science products at H2O.ai where he focuses mainly on model interpretability. Patrick is also currently an adjunct professor in the Department of Decision Sciences at George Washington University, where he teaches graduate classes in data mining and machine learning. Prior to joining H2O.ai, Patrick held global customer facing roles and research and development roles at SAS Institute.

Linkedin: https://www.linkedin.com/in/jpatrickhall/

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Vivant Shen
Vivant Shen Lead Data Scientist, Lending Works
Vivant Shen

Vivant has studied economics and has obtained two masters in finance and risk sectors. She has spent several years in the financial sector and peer-to-peer lending focusing on credit risk modelling, fraud detection and building scorecards. She is also a Kaggle Master since 2016.

Linkedin: https://www.linkedin.com/in/vivant-shen-3b86813b/

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Bojan Tunguz
Bojan Tunguz Kaggle Grandmaster, Data Scientist, H2O.ai
Bojan Tunguz

Bojan was born in Sarajevo, Bosnia & Herzegovina, which my family fled for Croatia during the war. He came to the US as a high school exchange student, and managed to realize his dream of studying Physics. He has worked in academia for a few years, but for various personal and professional reasons decided to leave it. A few years ago he stumbled upon the wonderful world of Data Science and Machine Learning, and felt like he discovered his second vocation in life. Some of you may know him through Kaggle, where he's currently ranked in top 20 for competition, and in top 10 for kernels and discussions. He has a wonderful wife and three amazing little boys that keep him constantly busy and amused. He is a voracious reader, passionate about tinkering with all sorts of tools and gadgets, love digital photography, and really enjoys hiking in the woods.

Linkedin: https://www.linkedin.com/in/tunguz/

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Navrina Singh
Navrina Singh Principal Product Lead, Microsoft AI
Navrina Singh

Navrina Singh is Principal Product Lead in Microsoft Cloud & AI, where she is focused on building conversational AI products for Business Application Group. Prior to this, Navrina was the Director Business Development for Artificial Intelligence responsible for business development, strategy and partnerships to forge new businesses for Microsoft leveraging Artificial Intelligence technologies. Before joining Microsoft in 2016, Navrina spent 12 years at Qualcomm Incorporated, where she held multiple roles across engineering, product management and strategy. In her last role at Qualcomm, Navrina was the head of Qualcomm Innovation responsible for the vision and execution of the technology incubator (Qualcomm ImpaQt) focused on building emerging technologies and delivering strategic partnerships in Artificial Intelligence, Internet of Things and Mobile.

Navrina is a Young Global Leader with World Economic Forum (WEF), for her work in disruptive technologies, catalyzing startup ecosystems and a keen focus on cognitive diversity and Inclusion. Navrina was also a member of the WEF Global Future Council on AI and Robotics, exploring how developments in these fields could impact industry, governments and society in the future. Navrina currently serves on the industry advisory board of the University of Wisconsin-Madison College of Electrical Engineering. Navrina holds a MS in Electrical Engineering from the University of Wisconsin-Madison, an MBA from the University of Southern California and a BS in Electronics & Telecommunications from College of Engineering, Pune India.

Linkedin: https://www.linkedin.com/in/navrina/

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Megan Kurka
Megan Kurka Customer Data Scientist, H2O.ai
Megan Kurka
Auto-Doc with H2O Driverless AI

H2O Driverless AI is H2O.ai's flagship platform for automatic machine learning. It fully automates the data science workflow including some of the most challenging tasks in applied data science such as feature engineering, model tuning, model optimization, and model deployment. Driverless AI turns Kaggle Grandmaster recipes into a full functioning platform that delivers "an expert data scientist in a box" from training to deployment. Driverless AI with Auto Doc is the next logical step of the data science workflow by taking the final step of automatically documenting and explaining the processes used by the platform. Auto Doc frees up the user from the time consuming task of documenting and summarizing their workflow while building machine learning models. The resulting documentation provides users with insight into machine learning workflow created by Driverless AI including details about the data used, the validation schema selected, model and feature tuning, and the final model created. With this capability in Driverless AI, users can focus on model insights and results.

Megan is a Customer Data Scientist at H2O. Prior to working at H2O, she worked as a Data Scientist building products driven by machine learning for B2B customers. She has experience working with customers across multiple industries, identifying common problems, and designing robust and automated solutions.

Linkedin: https://www.linkedin.com/in/megan-kurka-36336569/

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Jakub Hava
Jakub Hava Senior Software Engineer, H2O.ai
Jakub Hava

Bio: Jakub (or “Kuba” as we call him) completed his Bachelor’s Degree in Computer Science and Master’s Degree in Software Systems at Charles University in Prague. As a bachelor’s thesis, Kuba wrote a small platform for distributed computing of any types of tasks. During his master’s degree studies, he developed a cluster monitoring tool for JVM based languages which makes debugging and reasoning the performance of distributed systems easier using a concept called distributed stack traces. Kuba enjoys dealing with problems and learning new programming languages. At H2O.ai, Kuba works on Sparkling Water. Aside from programming, Kuba enjoys exploring new cultures and bouldering. He’s also a big fan of tea preparation and the associated ceremony.

Linkedin: https://www.linkedin.com/in/havaj/

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Eva Prakash
Eva Prakash Alumni Chapter Lead, AI4ALL
Eva Prakash

Bio: Eva Prakash is a Stanford AI4ALL 2016 alum and Alumni Chapter Lead. AI is so fascinating to her—it doesn’t just power voice assistants or recommend Netflix shows, it is the most transformative technology of our time and is revolutionizing every major industry! Since AI is making key decisions about our lives, Eva wants to help ensure it is developed by a diverse community of female technologists, so that its assessments are truly all-inclusive and not simply male-dominated. Eva is the author of the young adult fiction book Alan Purring, which tells the story of a young Latina who crafts an AI-powered catbot named Alan Purring. She also delivered a TEDx talk titled "Why Diversity Matters for the Future of AI".

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Agenda

February 4th, 2019
8:00am

Coffee & Registration

8:00am - 9:00am
9:00am

Get Behind the Wheel with H2O Driverless AI Hands-On Training Part 1

9:00am - 10:30am
10:30am

Break

10:30am - 10:45am
10:45am

Get Behind the Wheel with H2O Driverless AI Hands-On Training Part 2

10:45am - 12:00pm
12:00pm

Lunch

12:00pm - 1:00pm
1:00pm

Deep dive into H2O-3 and Sparkling Water

1:00pm - 4:00pm
4:00pm

Performance

4:00pm - 5:00pm
5:00pm

Reception

5:00pm - 6:00pm
February 5th, 2019
8:00am

Coffee & Registration

8:00am - 9:00am
9:00am

Keynotes

9:00am - 10:00am
10:00am

Break

10:00am - 10:15am
10:15am

Keynotes

10:15am - 12:00pm
12:00pm

Lunch

12:00pm - 1:00pm

Business Track

Technical Track

H2O Track

1:00pm

Sessions

1:00pm - 3:00pm
3:00pm

Break

3:00pm - 3:15pm
3:15pm

Women and Inclusion in Tech Panel

3:15pm - 4:00pm
3:15pm

H2O Driverless AI Panel

3:15pm - 4:00pm
4:00pm

Meet the Kaggle Grandmasters Panel

4:00pm - 4:45pm
4:45pm

Closing Remarks

4:45pm - 5:00pm
5:00pm

Reception

5:00pm - 7:00pm
Training

Training

This will be a hands-on training of our groundbreaking products, H2O Driverless AI, H2O-3 and Sparkling Water. Join your fellow data scientists, developers and engineers in this technical deep-dive of H2O.

Don't forget to bring your laptop and power cord!

Want to get a head start and get behind the wheel of H2O Driverless AI? Request a free trial here.

Hilton

Venue

Hilton San Francisco Union Square is in the heart of San Francisco, walking distance from Westfield San Francisco Centre and Union Square. This hotel is close to Lombard Street and Pier 39.

FAQ

Who attends this event?

Designed for data scientists, data engineers and business leaders, H2O World San Francisco offers something for everyone no matter your skill set or background.

I’d like to speak at H2O World San Francisco, do you accept speakers?

While we don’t have an official call for papers, we are open to abstract submissions.

Please send your abstract title, abstract and bio to events@h2o.ai.

Are there ID or minimum age requirements to enter the event?

Please ensure you have a government-issued ID to enter the event. We will have a reception on Day 2 which will require those only 21 years old and above to attend as alcohol will be served.

What are my transportation and parking options for getting to and from the event?

From SFO Airport, take Highway 101 north and exit at 7th street. Turn right on Folsom Street, then left on 5th street. Cross Market Street and turn left on Ellis Street to Mason Street. Our garage entrance is on Ellis Street between Mason and Taylor Streets.

The hotel location is within walking distance to transportation hubs, cable cars, shopping and popular city attractions including Union Square and Moscone Convention Center. A few other location highlights:

•One block from Powell Street Station for BART and MUNI transit lines
•Only 13 miles from San Francisco International Airport (SFO) and 13 miles from Metropolitan Oakland International Airport (OAK)
•Walking distance to the Cable Cars

Please follow the H2O World San Francisco signage inside the hotel which will guide you to our registration area.

What must I bring to the event?

Please bring your laptop and charger. We'll have power stations throughout the venue.

Do I have to bring my printed ticket to the event?

No, please bring your government issued ID - that's how we'll verify your ticket.

Is my registration/ticket transferrable?

We understand things change. So, if you have to transfer your ticket to a friend or colleague, we can do that for you. No change-fee. No hassle. No sweat. You can contact us at events@h2o.ai.

Still haven't found what you are looking for?

Contact us at events@h2o.ai with any questions related to the event. Please share your ideas about topics or speakers that make you excited.

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Check out our previous H2O World’s

Chicago
Chicago 2016
New York ai
New York 2016
Texas
Dallas 2016
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