Meet the Community
We're headed across the pond for our first H2O AI World London!
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 AI World London 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.
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.
Bio: Shanker Trivedi has 30+ years of experience in senior executive roles in the U.S., the U.K. and India. Shanker is currently Senior Vice President of Enterprise Business, for NVIDIA Worldwide Field Operations. He has led worldwide sales and business development for NVIDIA’s Datacenter and Professional Visualization products since 2009. His responsibility includes TESLA HPC and Hyperscale Datacenter servers, DGX AI Supercomputers, QUADRO graphics workstations, and CUDA, OpenACC, Deep Learning, and GRID virtualization software solutions. His objective is to exponentially grow NVIDIA’s enterprise revenues by focusing business development on lighthouse customers, expanding geographic sales coverage of large enterprises, strengthening partnerships with start-ups and application providers, and leveraging go-to-market partnerships with OEMs, CSPs, solution resellers and integrators in manufacturing, oil & gas, financial services, digital media, healthcare, government, and education verticals. Under his leadership, NVIDIA’s Enterprise revenue has grown to over $1.6 billion in FY17.
Prior to NVIDIA, Shanker was a member of the executive leadership team at Callidus Cloud between 2005‐08. During this period company revenues doubled to over $100m. Prior to Callidus, Shanker held various senior executive positions at Sun Microsystems between 1996-2005. As Vice President and General Manager, he doubled Sun’s revenue in the UK between 1998 and 2001 to over $1.3bn. At Sun, he also set up a new business, the Global Datacenter Solution Practice. Prior to Sun, Shanker held various sales, marketing, and general management positions at IBM (Europe), and ICL/Fujitsu and other companies in UK and India.
Shanker holds an M.B.A. (Gold Medal 1st rank) from IIM Calcutta and a M.S. in Mathematics and Computing from IIT Delhi.
October 29th, 2018
Coffee & Registration8:00am - 9:00am
Get Behind the Wheel with H2O Driverless AI Hands-On Training Part 19:00am - 10:30am
Break10:30am - 10:45am
Get Behind the Wheel with H2O Driverless AI Hands-On Training Part 210:45am - 12:00pm
Lunch12:00pm - 1:00pm
Deep dive into H2O-3 and Sparkling Water1:00pm - 3:00pm
October 30th, 2018
Coffee & Registration8:00am - 9:00am
Keynotes9:00am - 10:00am
Break10:00am - 10:15am
Lunch12:00pm - 1:00pm
Sessions1:00pm - 3:00pm
Break3:00pm - 3:15pm
Women and Inclusion in Data Science Panel3:15pm - 4:00pm
H2O Driverless AI Panel3:15pm - 4:00pm
Meet the Kaggle Grandmasters Panel4:00pm - 4:45pm
Closing Remarks4:45pm - 5:00pm
Reception5:00pm - 7:00pm
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.
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.
Bio: Marios Michailidis is now a Competitive Data Scientist at H2O.ai He holds a Bsc in accounting Finance from the University of Macedonia in Greece and an Msc in Risk Management from the University of Southampton. He has also nearly finished his PhD in machine learning at University College London (UCL) with a focus on ensemble modelling. 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, Uplift, 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. Here is a blog about Marios being ranked at the top in Kaggle and sharing his knowledge with tricks and ideas.
Finally, Marios’ likendin profile can be found here, with more information about what he is working on now or past projects.
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.
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.
Bio: Kevin Doyle is the lead architect of IBM Spectrum Conductor at IBM, where he works with customers to deploy and manage all workloads; especially Spark and deep learning workloads to on-premise clusters. Kevin has been working on distributed computing, grid, cloud, and big data for the past five years with a focus on the management and lifecycle of workloads.
Scaling out Driverless AI in Enterprise Data Centers with IBM Spectrum Conductor
This talk highlights the integration of Driverless AI with IBM Spectrum Conductor. The integration demonstrates how you can deploy, manage, and scale out to have multiple Driverless AI instances running within your cluster per user to help maximize the efficiency and security of the cluster. The integration includes failover for Driverless AI instances, so that users can continue to work without needing to find another host to start Driverless AI on. In addition, the integration of H2O Sparkling Water with IBM Spectrum Conductor as a notebook is highlighted; as well as the benefits of running H20 Sparkling water within the cluster to maximize your cluster utilization across different workloads.For both Driverless AI and H2O Sparkling Water, a demo will be provided and a future plan for the integrations is highlighted.
Leveraging H2O Machine Learning with KNIME Analytics Platform
Bio: Christian received a Master’s degree in Computer Science from the University of Konstanz. Having gained experience as a research software engineer at the University of Konstanz, where he developed frameworks and libraries in the fields of bioimage analysis and machine learning, Christian moved on to become a software engineer at KNIME. He now focuses on developing new functionalities and extensions for KNIME Analytics Platform. Some of his recent projects include deep learning integrations built upon Keras and Tensorflow, extensions for image analysis and active learning, and the integration of H2O Machine Learning and H2O Sparkling Water in KNIME Analytics Platform.
KNIME Analytics Platform is an easy to use and comprehensive open source data integration, analysis, and exploration platform, enabling data scientists to visually compose end to end data analysis workflows. The over 2,000 available modules ("nodes") cover each step of the analysis workflow, including blending heterogeneous data types, data transformation, wrangling and cleansing, advanced data visualization, or model training and deployment.
Many of these nodes are provided through open source integrations (why reinvent the wheel?). This provides seamless access to large open source projects such as Keras and Tensorflow for deep learning, Apache Spark for big data processing, Python and R for scripting, and more. These integrations can be used in combination with other KNIME nodes meaning that data scientists can freely select from a vast variety of options when tackling an analysis problem.
The integration of H2O in KNIME offers an extensive number of nodes and encapsulating functionalities of the H2O open source machine learning libraries, making it easy to use H2O algorithms from a KNIME workflow without touching any code - each of the H2O nodes looks and feels just like a normal KNIME node - and the data scientist benefits from the high performance libraries and proven quality of H2O during execution. For prototyping these algorithms are executed locally, however training and deployment can easily be scaled up using a Sparkling Water cluster.
In our talk we give a short introduction to KNIME Analytics Platform and then demonstrate how data scientists benefit from using KNIME Analytics Platform and H2O Machine Learning in combination by using a real world analysis example.
Bio: As principal data scientist at Travelport, Levi Brackman leads a team of data scientists that are putting ML model into production. Prior to Travelport, Levi spent most of his career in the start-up world. He founded and led an organization that created innovative educational software applications and solutions used by high schools and youth organizations in the USA and Australia. Levi earned a PhD in the quantitative social sciences under the supervision of one the world's leading educational psychologists. He earned master’s degree from University College London and is author of a business book published in eight languages that was a bestseller in multiple countries. A native of North London (UK) Levi is married and has five children and now lives in Broomfield, Colorado.
Session: Travelport is a leading travel commerce platform that has truly huge data and many complex needs in terms of processing, performance and latency. This talk will demonstrate how we were able to harness big data technologies, H2O and cloud integration to deploy AI at scale and at low latency. The talk to cover practical advice taken from our AI journey; you will learn the successful strategies and the pitfalls of near real-time retraining ML models with streaming data and using all opensource technologies.
Machine Learning at Booking.com with H2O
Bio: I am a data scientist at Booking.com where I am currently working on scalable machine learning solutions. Before that, I worked on partner facing product recommendations as well as building scalable business reports within Booking.com. I have a masters degree in theoretical mathematics from the University of Zagreb.
Tanya Berger Wolf
Driverless AI in-action in the Manufacturing Industry
Bio: Avkash Chauhan is tasked to transform Macnica Corporation's billion dollar business using Artificial Intelligence solutions for it global customers. Since joining Macnica, he is leading a team of AI solution developers and solution delivery engineers to assist their customers using AI technology and solutions to transform their business and have an edge over the competition. Avkash's career spans over 20 years as an engineer, entrepreneur and tech leader while working with enterprises and businesses worldwide.
Bio: Jo-fai (or Joe) is a Data Science Evangelist and Community Manager at H2O.ai. Before joining H2O, he was in the business intelligence team at Virgin Media in the UK where he developed data products to enable quick and smart business decisions. He also worked remotely for Domino Data Lab in the US as a data science evangelist promoting products via blogging and giving talks at meetups. Joe has a background in water engineering. Before his data science journey, he was an EngD research engineer at STREAM Industrial Doctorate Centre working on machine learning techniques for drainage design optimization. Prior to that, he was an asset management consultant specialized in data mining and constrained optimization for the utility sector in the UK and abroad. He also holds an MSc in Environmental Management and a BEng in Civil Engineering.
Bio: Ashrith Barthur is a Security Scientist at H2O currently working on algorithms that detect anomalous behavior in user activities, network traffic, attacks, financial fraud, and global money movement. He has a Ph.D. from Purdue University in the field of information security, specialized in Anomalous behavior in DNS protocol.
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.
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