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Monday, December 4
 

8:30am

8:30am

Hackathon
Monday December 4, 2017 8:30am - 5:00pm
Bohle Computer History Museum

9:30am

Keynote - SriSatish Ambati - CEO H2O.ai
Monday December 4, 2017 9:30am - 10:30am
Maryam-Curie Stage Computer History Museum

10:32am

Keynote - Jim McHugh - VP NVIDIA
Monday December 4, 2017 10:32am - 11:02am
Maryam-Curie Stage Computer History Museum

11:04am

Keynote - Stephen Boyd - Professor, Stanford University
Monday December 4, 2017 11:04am - 11:49am
Maryam-Curie Stage Computer History Museum

12:00pm

Lunch
Monday December 4, 2017 12:00pm - 1:00pm
Computer History Museum

1:00pm

Drive Away Fraudsters With Driverless AI - Venkatesh R. - PayPal
Venkatesh is a senior data scientist at PayPal where he is working on building state-of-the-art tools for payment fraud detection. He has over 20+ years experience in designing, developing and leading teams to build scalable server side software. In addition to being an expert in big-data technologies, Venkatesh holds a Ph.D. degree in Computer Science with specialization in Machine Learning and Natural Language Processing (NLP) and had worked on various problems in the areas of Anti-Spam, Phishing Detection, and Face Recognition.

Monday December 4, 2017 1:00pm - 1:28pm
Maryam-Curie Stage Computer History Museum

1:00pm

Crowdsourcing, computer vision, and data science for conservation - Tanya Berger-Wolf - IBEIS.org
Dr. Tanya Berger-Wolf is a Professor of Computer Science at the University of Illinois at Chicago, where she heads the Computational Population Biology Lab. As a computational ecologist, her research is at the unique intersection of computer science, wildlife biology, and social sciences. Berger-Wolf is also a co-founder of the conservation software non-profit Wildbook, which enables wildlife research and conservation from crowdsourced photographs with computer vision and AI. Berger-Wolf holds a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign. She received numerous awards for her research and mentoring, including NSF CAREER and AWIS Chicago Innovator Award.

Monday December 4, 2017 1:00pm - 1:28pm
Srinivasa Ramanujan Stage Computer History Museum

1:00pm

Driverless AI - Introduction and a Look Under the Hood + Hands-On Labs - Arno Candel - H2O.ai
Arno Candel, is the Chief Technology Officer of H2O, a distributed and scalable open-source machine learning platform. He is also the main author of H2O’s Deep Learning. Before joining H2O, Arno was a founding Senior MTS at Skytree where he designed and implemented high-performance machine learning algorithms. He has over a decade of experience in HPC with C++/MPI and had access to the world’s largest supercomputers as a Staff Scientist at SLAC National Accelerator Laboratory where he participated in US DOE scientific computing initiatives 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 has authored dozens of scientific papers and is a sought-after conference speaker. Arno was named “2014 Big Data All-Star” by Fortune Magazine. Follow him on Twitter: @ArnoCandel.

Monday December 4, 2017 1:00pm - 2:00pm
Paul Erdos Stage Computer History Museum

1:30pm

Credit Trends and Machine Learning - Michele Raneri - Experian
Michele Raneri is the Vice President of Analytics and Business Development at Experian.  In this role, she manages teams of analysts and consultants who use quantitative analytics to demonstrate value of Experian’s Consumer, Commercial and Affinity solutions.  Key areas of responsibilities are scoring, segmentation, portfolio benchmarking, and thought leadership.

Monday December 4, 2017 1:30pm - 1:58pm
Maryam-Curie Stage Computer History Museum

1:30pm

Repurposing data to solve emerging business problems - Arturo Castellanos - CUNY
Arturo Castellanos is an Assistant Professor in the Zicklin School of Business at Baruch College (CUNY). His focus is on helping organizations implement data-driven strategies to create competitive advantage. His research interests are in systems analysis and design (UGC and data quality), machine learning, and blockchain. He teaches courses on Business Analytics, Data Warehousing, and Information Systems. He has a PhD in Information Systems from Florida International University.

Monday December 4, 2017 1:30pm - 1:58pm
Srinivasa Ramanujan Stage Computer History Museum

2:00pm

Afternoon Session
Monday December 4, 2017 2:00pm - 2:28pm
Maryam-Curie Stage Computer History Museum

2:00pm

Anti-Money Laundering - Ashrith Barthur - H2O.ai
Ashrith is the security scientist designing anomalous detection algorithms at H2O. He recently graduated from the Center of Education and Research in Information Assurance and Security (CERIAS) at Purdue University with a PhD in Information security. He is specialized in anomaly detection on networks under the guidance of Dr. William S. Cleveland. He tries to break into anything that has an operating system, sometimes into things that don’t. He has been christened as “The Only Human Network Packet Sniffer” by his advisors. When he is not working he swims and bikes long distances.

Monday December 4, 2017 2:00pm - 2:28pm
Srinivasa Ramanujan Stage Computer History Museum

2:02pm

Automatic Machine Learning + Hands-on Labs on H2O3 - Erin Ledell - H2O.ai
Erin is a Statistician and Machine Learning Scientist at H2O.ai. She is the main author of H2O Ensemble. Before joining H2O, she was the Principal Data Scientist at Wise.io and Marvin Mobile Security (acquired by Veracode in 2012) and the founder of DataScientific, Inc. Erin received her Ph.D. in Biostatistics with a Designated Emphasis in Computational Science and Engineering from University of California, Berkeley. Her research focuses on ensemble machine learning, learning from imbalanced binary-outcome data, influence curve based variance estimation and statistical computing. She also holds a B.S. and M.A. in Mathematics.

Monday December 4, 2017 2:02pm - 3:00pm
Paul Erdos Stage Computer History Museum

2:30pm

Equifax Ignite - More Data. Better Insights. Faster Implementation - David Ferber & Pinaki Ghosh - Equifax
Pinaki has over 20 years of industry experience of which 17 years at Equifax building data management and real-time decisoning platforms with strong background in software development, IT and data management. This includes building cutting edge Big Data Platforms which provides high speed access to differentiated data for building rich and actionable insights for Equifax and its clients. Pinaki is passionate and expert in the disciplines of Data Quality, Data Management, Entity.

David has over 20 years of experience in the credit industry focusing on the technical development and growth of Equifax's data platforms. This includes Equifax’s state of the art big data analytics platform that provides valuable cost effective insights and analytics, on its wide range of differentiated data sources.At Equifax, David has held multiple positions; Vice President of Technology, Decision 360 Technology Leader, Enterprise Data Leader and most recently Solutions Delivery Leader within Equifax’s Data & Analytics organization.David holds a degree in Computer Science from North Georgia College.

Monday December 4, 2017 2:30pm - 3:00pm
Maryam-Curie Stage Computer History Museum

2:30pm

Open Mic
Monday December 4, 2017 2:30pm - 3:00pm
Srinivasa Ramanujan Stage Computer History Museum

3:00pm

PM Break
Monday December 4, 2017 3:00pm - 3:15pm
Computer History Museum

3:15pm

A 2017 retrospective on AI in Healthcare and Life Sciences: Data, Algorithms and Infrastructures - Sanjay Joshi - H2O.ai
Sanjay Joshi is the Chief of Technology, Healthcare and Life Sciences at H2O.ai. Based in Seattle, Sanjay’s 25+ year career has spanned the entire gamut of life-sciences and healthcare from clinical and biotechnology research to healthcare informatics to medical devices. A “skunkworks” engineer, bioengineer and informaticist, he defines himself as a “non-reductionist” with a “systems view of the world.” His current focus is a systems-level understanding of Healthcare, Genomics, Proteomics, Microbiomics, Imaging and IoT processes. Recent experience has included data management and instruments for Electronic Medical Records; Proteomics and Flow Cytometry; FDA and HIPAA validations; Lab Information Management Systems (LIMS); Translational Genomics research and Imaging. Sanjay holds a patent in multi-dimensional flow cytometry analytics. He began his career developing and building X-Ray machines. Sanjay was the recipient of a National Institutes of Health (NIH) Small Business Innovation Research (SBIR) grant and has been a consultant or co-Principal-Investigator on several NIH grants. He is actively involved in non-profit biotech networking and educational organizations in the Seattle area and beyond. Sanjay holds a Master of Biomedical Engineering from the University of New South Wales, Sydney and a Bachelor of Instrumentation Technology from Bangalore University. He has completed several medical school and PhD level courses (in Sydney and Seattle). He likes to balance his fuzzy, neural-network achievements with maker-projects that actually involve physical effort.

Monday December 4, 2017 3:15pm - 3:35pm
Paul Erdos Stage Computer History Museum

3:15pm

Design Patterns for Machine Learning in Production - Sergei Izrailev - BeeswaxIO
Dr. Sergei Izrailev is Chief Data Scientist at BeeswaxIO, where he is responsible for data strategy and building AI applications powering the next generation of real time bidding technology. Before Beeswax, Sergei led data science teams at Integral Ad Science and Collective, where he focused on architecture, development and scaling of data science based advertising technology products. Prior to advertising, Sergei was a quant/trader and developed trading strategies and portfolio optimization methodologies. Previously, he worked as a senior scientist at Johnson & Johnson, where he developed intelligent tools for structure-based drug discovery. Sergei holds a Ph.D. in Physics and Master of Computer Science degrees from the University of Illinois at Urbana-Champaign.

Monday December 4, 2017 3:15pm - 3:40pm
Maryam-Curie Stage Computer History Museum

3:15pm

HR Analytics: Using Machine Learning to Predict Employee Turnover - Matt Dancho - Business Science
Matt Dancho is the founder of [Business Science](www.business-science.io), a consulting firm that assists organizations in applying data science to business applications. He is the creator of R packages tidyquant and timetk and has been working with data science for business and financial analysis since 2011. Matt holds master’s degrees in business and engineering, and has extensive experience in business intelligence, data mining, time series analysis, statistics and machine learning. Connect with Matt on twitter (https://twitter.com/mdancho84) and LinkedIn (https://www.linkedin.com/in/mattdancho/).

Monday December 4, 2017 3:15pm - 3:40pm
Srinivasa Ramanujan Stage Computer History Museum

3:37pm

Healthcare, Spark, H2O, EMR, Production - Adam Sullivan - Change Healthcare
Change Healthcare is a leader in Artificial Intelligence solutions built at scale across one of the world's largest healthcare datasets.  We deploy production jobs using H2O, Spark, and EMR, all while maintaining the highest levels of HIPAA security and compliance.  In this talk, we'll highlight one of our use cases on identifying erroneous payments to hospital systems and how we boosted a business using H2O, Sparkling Water, and AutoML while engaging the team at H2O to solve encryption of PHI.  We'll also discuss our strategy as we turn our attention to medical records using GPU's and H2O's Deep Water package

Monday December 4, 2017 3:37pm - 4:08pm
Paul Erdos Stage Computer History Museum

3:45pm

Predicting and Preventing Avoidable Truck Rolls (ATR) - Bernard Burg, Bhavana Bhasker, Ryan March - Comcast
Bernard Burg spearheads Comcast’s applied AI team at Comcast Silicon Valley. Our mission is to improve the user experience by monitoring the behavior of our networks, predict their performance and implement self-healing.  Bernard earned a PhD in machine learning with a focus on behavioral process control, a predecessor of reinforcement learning.

Ryan March is a Data Scientist at the Comcast Applied AI team in CSV, where he focuses on engineering data ingestion and processing pipelines. His primary tasks include cleaning, joining, and preparing data for use in Machine Learning flows.

Bhavana Bhasker is a Data Scientist at the Comcast Applied AI team in CSV. She has research experience in Deep neural networks and Applied Machine Learning. She is also a part time lecturer at San Jose State University. Her area of interests are Computer Vision and Natural Language processing.

Monday December 4, 2017 3:45pm - 4:13pm
Maryam-Curie Stage Computer History Museum

3:45pm

Explaining Black-Box Machine Learning Predictions - Sameer Singh - UC Irvine

Dr. Sameer Singh is an Assistant Professor of Computer Science at the University of California, Irvine. He is working on large-scale and interpretable machine learning applied to natural language processing. Sameer was a Postdoctoral Research Associate at the University of Washington and received his PhD from the University of Massachusetts, Amherst, during which he also worked at Microsoft Research, Google Research, and Yahoo! Labs on massive-scale machine learning. He was awarded the Adobe Research Data Science Faculty Award, was selected as a DARPA Riser, won the grand prize in the Yelp dataset challenge, and received the Yahoo! Key Scientific Challenges fellowship. Sameer has published extensively at top-tier machine learning and natural language processing conferences. (http://sameersingh.org)



Monday December 4, 2017 3:45pm - 4:13pm
Srinivasa Ramanujan Stage Computer History Museum

4:10pm

Forecasting Influenza-Like Illnesses

Jennie Shin is the Director of SCAL Strategic Technology Solutions at Kaiser Permanente. Jennie is a Healthcare IT leader focused on aligning business strategy with leadership, organizational, technology and culture needs to transform the way care is delivered. She has experience with designing and orchestrating various solutions and processes to increase efficiency, access to data and improve customer experiences and create a personalized care model that delivers the right care at the right time.

Joanne Shin is currently a Data Scientist at Kaiser Permanente. From 2013 to 2015, Ms. Shin's passion for technology and analytics led her to pursue a Master of Science degree in Artificial Intelligence under the Electrical Engineering department at UC San Diego; a discipline that focuses on statistical learning. While in graduate school she interned for Kaiser Permanente and worked as a research assistant in the Neural Interaction Lab under the guidance of Professor Todd Coleman.

Charles Bach is a Principal Architect for Kaiser Permanente serving the Southern California region. Being an integrated provider, Kaiser Permanente has the unique advantage of caring for patients throughout the many touch points of healthcare. However, with this advantage, enormous amounts of data are generated at every touch point along the patient life cycle. In order to derive meaningful information from this complex data environment, Charles designs and provides architecture for data management and analytics solutions. Charles also conducts rapid proof of concepts on new and emerging technologies that can rise to the challenge of a changing healthcare landscape that not only includes growing patient volumes but also new patient touch points such as social and medical devices.

Karen Hayrapetyan is a senior data scientist at H2O.ai. Karen works with H2O.ai customers to derive substantive business value from machine learning technologies. Prior to joining H2O.ai, he spent three years at startups working on growth and analytics problems. Karen holds a Ph.D. in Physics from Purdue University with research focus in molecular imaging and nanoparticle biosensors.


Monday December 4, 2017 4:10pm - 4:35pm
Paul Erdos Stage Computer History Museum

4:15pm

Bringing scientists to data to accelerate discoveries and improve human health - Somalee Datta - Stanford University
Somalee is a computational physicist by training, a biotechnologist by profession and a data analyst by the way of passion. She believes that with the explosion of data in healthcare and with new methods to analyze such large amounts of data, we will see massive changes in how human diseases are addressed via novel drugs, large scale genomics, wearable sensors, and software to tie it all together. She wants to drive part of this revolution.

Monday December 4, 2017 4:15pm - 4:35pm
Srinivasa Ramanujan Stage Computer History Museum

4:15pm

Financial Services Panel
Monday December 4, 2017 4:15pm - 5:00pm
Maryam-Curie Stage Computer History Museum

4:37pm

Healthcare Panel
Monday December 4, 2017 4:37pm - 5:10pm
Paul Erdos Stage Computer History Museum

5:00pm

Driverless AI Hands-On Lab - Redo!
Monday December 4, 2017 5:00pm - 6:00pm
Paul Erdos Stage Computer History Museum

5:00pm

Evening Reception
Monday December 4, 2017 5:00pm - 7:00pm
Computer History Museum
 
Tuesday, December 5
 

8:00am

8:30am

Hackathon
Tuesday December 5, 2017 8:30am - 5:00pm
Bohle Computer History Museum

9:00am

9:32am

Keynote - Rob Tibshirani - Professor, Stanford University
Robert Tibshirani is a Professor in the Departments of Statisticsand Biomedical Data Sciences at Stanford University In his work he has madeimportant contributions to the analysis of complex datasets, most recently ingenomics and proteomics.  Some of hismost well-known contributions are the lasso, which uses L1 penalization in  regression and related problems, generalizedadditive models and Significance Analysis of Microarrays (SAM). He alsoco-authored four widely used books "Generalized Additive Models",  "An Introduction to the Bootstrap","The Elements of Statistical Learning",  and "Sparsity in Statistics: the Lassoand its generalizations."

Tuesday December 5, 2017 9:32am - 10:15am
Maryam-Curie Stage Computer History Museum

10:17am

Keynote - Jeff Herbst - VP Business Development, NVIDIA
Tuesday December 5, 2017 10:17am - 10:50am
Maryam-Curie Stage Computer History Museum

10:50am

AM Break
Tuesday December 5, 2017 10:50am - 11:00am
Computer History Museum

11:00am

Deep learning-based AI for the Enterprise - Sumit Gupta - IBM

Sumit Gupta is a Vice President in the IBM Cognitive systems business, responsible for offering (product) and business management for High Performance Computing (HPC), AI, and Machine and Deep Learning. With over 20 years of experience, Sumit is a recognized industry expert in the fields of HPC, deep learning, and data analytics. Sumit conceived and leads the development of IBM’s PowerAI deep learning software offering. 

Sumit joined IBM in 2015 from NVIDIA, where he was the General Manager for the Tesla GPU accelerator business. He was central in building this startup business within NVIDIA from zero to a several hundred million dollar business and in building its large developer ecosystem and deep learning strategy. Sumit is a product management, marketing, and business leader for enterprise systems and software products. He has previously held positions in marketing, business strategy, and engineering at Tensilica, Tallwood Venture Capital, Intel, S3, and IBM. Sumit has a Ph.D. in Computer Science from the University of California, Irvine, and a Bachelor of Technology in Electrical Engineering from the Indian Institute of Technology, Delhi. He has authored one book, one patent, several book chapters and more than 20 technical publications.



Tuesday December 5, 2017 11:00am - 11:18am
Paul Erdos Stage Computer History Museum

11:00am

Machine Learning in HCM - Xiaojing Wang - ADP
Xiaojing Wang, Principal Data Scientist and Senior Director, is responsible for combining ADP’s rich HCM data with cutting edge technologies in big data, machine learning and predictive analytics to create next generation data products. Her team develops the award-winning benchmarking product and ADP predictive analytical platform.Prior to joining ADP, Xiaojing was principal consultant for Intelogic, advising clients ranging from startups to established financial companies on data product strategies and data architecture.Prior to that, Xiaojing spent 10 years in CNET, leading a team building its enterprise data warehouse and business intelligence infrastructure. She created the first revenue generating data product and led the development of first terabyte advertising data mart enabling advanced ad delivery and optimization.

Tuesday December 5, 2017 11:00am - 11:28am
Maryam-Curie Stage Computer History Museum

11:00am

How to design deep networks to process images on mobile devices - Karunkar Singamreddy - Digitalist Group
Karunkar Singamreddy (SK) is the Chief Product Officer, AI and ML at Digitalist Group (www.digitalistgroup.com) and a successful twice start-up entrepreneur. He is a frequent speaker in conferences and meetups. Additionally, he is a ML/NLP blogger. He believes that machine learning enthusiasts are looking for ML/NLP sessions where they can understand more of 'how' rather than 'what'. 
  His focus is to develop ML models to combine image and text processing. Also he has developed solutions in text summarization, question-answering and text mining.

Tuesday December 5, 2017 11:00am - 11:28am
Srinivasa Ramanujan Stage Computer History Museum

11:20am

Supervised Learning with Unstructured Text Data - Megan Kurka - H2O.ai
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. Megan is based in New York City and holds a degree in Applied Mathematics. In her free time, she enjoys hiking and yoga.

Tuesday December 5, 2017 11:20am - 11:38am
Paul Erdos Stage Computer History Museum

11:30am

Scaling Machine Learning at Booking.com with H2O Sparkling Water and FeatureStore - Luca Falsina & Ben Teeuwen - Booking.com
Luca is a Software Developer at Booking.com in Amsterdam. He is currently working to leverage infrastructure and improve tooling to help internal teams taking advantage of machine learning techniques at scale. Previously, he contributed to the implementation and deployment of an engine to flag fraudulent attempts of payment on the B.com platform. Prior to Booking.com, Luca had a six months internship in Amazon in the localization team and before that he studied Computer Science in Milan. During that time he developed Grab’n Run, a library to secure and simplify dynamic code loading in Android apps.

Ben Teeuwen spends most of his work time as a data scientist empowering data scientists through tooling and trainings to use ML to further personalize Booking.com. Ben guided widespread adoption of Spark throughout the company. Before starting to work for Booking.com in 2014, he studied cognitive psychology, researched public sector innovation and worked on educational publishing tech.

Tuesday December 5, 2017 11:30am - 12:00pm
Maryam-Curie Stage Computer History Museum

11:30am

Natural Language Processing - Darren Cook - QQ Trend
Darren Cook has over 20 years of experience as a softwaredeveloper, data analyst, and technical director, working on everythingfrom financial trading systems to NLP, data visualization tools, and PRwebsites for some of the world's largest brands. He is skilled in a widerange of computer languages, including R, C++, PHP, JavaScript, andPython. He works at QQ Trend, a financial data analysis and dataproducts company.

Tuesday December 5, 2017 11:30am - 12:00pm
Srinivasa Ramanujan Stage Computer History Museum

11:40am

Auto Visualization - Leland Wilkinson - H2O.ai
Leland Wilkinson is Chief Scientist at H2O and Adjunct Professor of Computer Science at the University of Illinois Chicago. He received an A.B. degree from Harvard in 1966, an S.T.B. degree from Harvard Divinity School in 1969, and a Ph.D. from Yale in 1975. Wilkinson wrote the SYSTAT statistical package and founded SYSTAT Inc. in 1984. After the company grew to 50 employees, he sold SYSTAT to SPSS in 1994 and worked there for ten years on research and development of visualization systems. Wilkinson subsequently worked at Skytree and Tableau before joining H2O. Wilkinson is a Fellow of the American Statistical Association, an elected member of the International Statistical Institute, and a Fellow of the American Association for the Advancement of Science. He has won best speaker award at the National Computer Graphics Association and the Youden prize for best expository paper in the statistics journal Technometrics. He has served on the Committee on Applied and Theoretical Statistics of the National Research Council and is a member of the Boards of the National Institute of Statistical Sciences (NISS) and the Institute for Pure and Applied Mathematics (IPAM). In addition to authoring journal articles, the original SYSTAT computer program and manuals, and patents in visualization and distributed analytic computing, Wilkinson is the author (with Grant Blank and Chris Gruber) of Desktop Data Analysis with SYSTAT. He is also the author of The Grammar of Graphics, the foundation for several commercial and open­source visualization systems (IBM­RAVE, Tableau, R­ggplot2, and Python­Bokeh).

Tuesday December 5, 2017 11:40am - 12:00pm
Paul Erdos Stage Computer History Museum

12:00pm

Lunch
Tuesday December 5, 2017 12:00pm - 1:00pm
Computer History Museum

12:00pm

Open Mic
Tuesday December 5, 2017 12:00pm - 1:00pm
Srinivasa Ramanujan Stage Computer History Museum

1:00pm

Use of H2O for Mobile Transaction Anomaly detection - Donald Gennetten & Rahul Gupta - Capital One

Donald Gennetten has over 15 years’ experience supporting digital channels in the Financial Services industry. In his current role as a Data Engineer for Capital One’s Monitoring Intelligence team, he leads a cross functional group of Data, Business, and Engineering subject matter experts to deliver Advanced Analytics solutions for real-time customer transaction monitoring and issue detection.

Rahul Gupta is a Data Engineer in Capital One's Center for Machine Learning, focusing heavily on back-end development and model creation.  His primary efforts include building an Algorithmic IT Operations (AIOps) platform that utilizes a combination of batch and streaming data with Machine Learning capabilities to improve the stability of Capital One services and overall customer experience.




Tuesday December 5, 2017 1:00pm - 1:28pm
Maryam-Curie Stage Computer History Museum

1:00pm

Best Practices for Enterprises Taking a Platform-Based Approach to Data Science - William Merchan - Datascience.com
William Merchan leads business and corporate development, partner initiatives, and strategy at DataScience.com as chief strategy officer. He most recently served as SVP of Strategic Alliances and GM of Dynamic Pricing at MarketShare, where he oversaw global business development and partner relationships, and successfully led the company to a $450 million acquisition by Neustar.

Tuesday December 5, 2017 1:00pm - 1:28pm
Srinivasa Ramanujan Stage Computer History Museum

1:00pm

Hands-on Lab - Sparkling Water - Jakub Hava - H2O.ai

Jakub finished his bachelors degree in computer science at Charles University in Prague, and is currently finishing his master’s in software engineering as well. As a bachelors thesis, Kuba wrote a small platform for distributed computing of tasks of any type. On his current masters studies he’s developing a cluster monitoring tool for JVM based languages which should make debugging and reasoning about performance of distributed systems easier using a concept called distributed stack traces. Kuba enjoys dealing with problems and learning new programming languages, functional ones at most in the last days. At H2O, Kuba mostly works on our Sparkling Water project.

Aside from programming, Kuba enjoys exploring new cultures and bouldering. He’s also a big fan of tea preparation and associated ceremony.


Tuesday December 5, 2017 1:00pm - 2:00pm
Paul Erdos Stage Computer History Museum

1:30pm

Afternoon Session by Bingwei Liu

Dr. Bingwei Liu is a Sr. Data Engineer at Aetna Inc. He works on researching and supporting new technologies on Hadoop environment, user education and Cloud engineering.



Tuesday December 5, 2017 1:30pm - 1:58pm
Maryam-Curie Stage Computer History Museum

1:30pm

Distributed Learning of Rule Ensemble Models with H2O - Giovanni Seni - Amazon's A9
Giovanni Seni currently leads a team of data scientists and data engineers at Amazon’s A9.com, working on computational advertising problems. As an active data mining practitioner in Silicon Valley, he has over 15 years R&D experience in statistical pattern recognition and data mining applications. He has been a member of the technical staff at large technology companies, and a contributor at smaller organizations. He holds five US patents and has published over twenty conference and journal articles. His book “Ensemble Methods in Data Mining – Improving accuracy through combining predictions”, was published in February 2010 by Morgan & Claypool.

Tuesday December 5, 2017 1:30pm - 1:58pm
Srinivasa Ramanujan Stage Computer History Museum

2:00pm

Robust approach to machine learning models comparison - Dmitry Larko - H2O.ai
Senior Data Scientist at H2O.ai, Dmitry 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.

Tuesday December 5, 2017 2:00pm - 2:18pm
Maryam-Curie Stage Computer History Museum

2:00pm

GPU-powered Visualization, Data Analysis and Machine Learning - Ashish Sahu & Mateusz Dymczyk - Mapd Technologies & H2O.ai
Ashish is responsible for heading products at MapD. He was most recently VP of Product Marketing at Cask Data, a big data startup. Previously, Ashish was responsible for launching Analytics, Geospatial, & Advanced Analytics for SAP's in-memory platform, SAP HANA, and held a mix of technical and product roles at Checkpoint and Motorola. Ashish has an MBA from Haas School of Business, Berkeley, Masters in Information Systems from IIM, and BS in Mechanical Engineering from NIT India.

Mateusz is a software developer at H2O.ai who loves all things distributed, machine learning and hates buzzwords. His favourite hobby data juggling. He obtained his M.Sc. in Computer Science from AGH UST in Krakow, Poland, during which he did an exchange at L’ECE Paris in France and worked on distributed flight booking systems. After graduation he move to Tokyo to work as a researcher at Fujitsu Laboratories on machine learning and NLP projects, where he is still currently based. In his spare time he tries to be part of the IT community by organising, attending and speaking at conferences and meet ups.


Tuesday December 5, 2017 2:00pm - 2:28pm
Srinivasa Ramanujan Stage Computer History Museum

2:02pm

Driverless Hands-on focused on Machine Learning Interpretability - Patrick Hall, Navdeep Gill, Mark Chan - H2O.ai
Patrick Hall is a 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 R & D research roles at SAS Institute. He holds multiple patents in automated market segmentation using clustering and deep neural networks. Patrick was the 11th person worldwide to become a Cloudera certified data scientist. He studied computational chemistry at the University of Illinois before graduating from the Institute for Advanced Analytics at North Carolina State University.

Navdeep is a Software Engineer/Data Scientist at H2O.ai. He graduated from California State University, East Bay with a M.S. degree in Computational Statistics, B.S. in Statistics, and a B.A. in Psychology (minor in Mathematics). During his education he gained interests in machine learning, time series analysis, statistical computing, data mining, & data visualization. Previous to H2O.ai he worked at Cisco Systems, Inc. focusing on data science & software development. Before stepping into industry he worked in various Neuroscience labs as a researcher/analyst. These labs were at institutions such as California State University, East Bay, University of California, San Francisco, and Smith Kettlewell Eye Research Institute. His work across these labs varied from behavioral, electrophysiology, and functional magnetic resonance imaging research. In his spare time Navdeep enjoys watching documentaries, reading (mostly non-fiction or academic), and working out.

Mark Chan is a hacker at H2O. He was previously in the finance world as a quantitative research developer at Thomson Reuters and Nipun Capital. He also worked as a data scientist at an IoT startup, where he built a web based machine learning platform and developed predictive models. Mark has a MS Financial Engineering from UCLA and a BS Computer Engineering from University of Illinois Urbana-Champaign. In his spare time Mark likes competing on Kaggle and cycling.


Tuesday December 5, 2017 2:02pm - 3:00pm
Paul Erdos Stage Computer History Museum

2:30pm

Talk by Matt Dowle

Matt is the main author of the data.table package in R. He has worked for some of the world’s largest financial organizations: Lehman Brothers, Salomon Brothers, Citigroup, Concordia Advisors and Winton Capital. He is particularly pleased that data.table is also used outside Finance, for example Genomics where large and ordered datasets are also researched.

Matt has been programming in S/R for 15 years, knows C pretty well and holds a first class BSc in Applied Maths and Computing from Warwick University, U.K.


Tuesday December 5, 2017 2:30pm - 3:00pm
Srinivasa Ramanujan Stage Computer History Museum

2:40pm

Driver Vs Driverless AI

Mark Landry is a competitive data scientist and a product manager at H2O.ai. He is well-trained in getting quick solutions to iterate over and enjoys testing ideas in Kaggle competitions, where his worldwide ranking stands in the top 0.03%. His first encounter with H2O.ai was while when he was hacking R. He reached out Arno Candel (CTO, H2O.ai) to team up in Kaggle competition as he felt it would be exciting to work with the lead developers of the tool that contributed to his work in R. Mark holds a B.S. in Computer Science from Mississippi State University and was a Principal Engineer at Dell before joining H2O.ai. At Dell, he spearheaded data modelling and project support for the business transformation team, and also developed analytical tools and machine learning models to increase business efficiency.


Mark was the first Kaggle Grandmaster to be employed at H2O.ai and he enabled inroads into the Kaggle community for H2O. At H2O.ai, he has helped modernize the GBM algorithm and provided guidance on multiple projects before being pulled into one of H2O’s biggest projects. He holds interests in multi-model architectures and helps the world make fewer models that perform worse than the mean. He also has a number of publications to his name with multiple citations from the industry and academia alike. Mark 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.



Tuesday December 5, 2017 2:40pm - 3:00pm
Maryam-Curie Stage Computer History Museum

3:00pm

PM Break
Tuesday December 5, 2017 3:00pm - 3:15pm
Computer History Museum

3:15pm

Leakage in Meta Modeling And Its Connection to HCC Target-Encoding - Mathias Müller - H2O.ai
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.

Tuesday December 5, 2017 3:15pm - 3:43pm
Maryam-Curie Stage Computer History Museum

3:15pm

Talk by Pablo Abreu
Tuesday December 5, 2017 3:15pm - 3:43pm
Srinivasa Ramanujan Stage Computer History Museum

3:15pm

Hands-on Lab - H2O4GPU - Jonathan C. McKinney - H2O.ai
Jonathan C. McKinney is the research director at H2O.ai.  He was a professor in physics at the University of Maryland at College Park where he created new numerical models, algorithms, and code to simulate astrophysical plasmas and black holes to test Einstein's theories.  He used machine learning through-out his research, and now applies himself at H2O.ai to develop its latest machine learning algorithms on GPUs.  He also contributes to other projects like DriverlessAI.  In his free time he goes mountain climbing (e.g. Uhuru peak on Kilimanjaro), hiking, biking, and spending time with his family.

Tuesday December 5, 2017 3:15pm - 4:30pm
Paul Erdos Stage Computer History Museum

3:45pm

Talk by Johnathan Mercer - Ledger Investing
John is the Chief Product Officer at Ledger Investing. As a data science and product leader, he has 15+ years of experience across industries building advanced analytics, apps, and platforms that empower people.

John started his career as the Founder/CEO of Xumbrus, an academic software company that helped tens of thousands of students, and later worked in many industries and advanced analytics groups at some of the greatest organizations in the US. At the Broad Institute of MIT & Harvard, John was a senior computational and technology lead where he invented and built GeNets, a multiple-award winning and patented platform for biological pathway analysis. As Chief Analytics Officer at a leading mobile intelligence company - Apptopia - he led the data science group to transform the analytic layer of the platform and drive all analytics in the organization. 

John is a hackathon winner, has published in top scientific journals such as Nature, and has been honored to speak at events like the Business of Software Conference, Spark Summit, Annual Meeting of the American Society of Human Genetics, and the Annual Retreat of the Broad Institute of MIT and Harvard. 

John graduated magna cum laude in both Economics (B.A.) and Statistics (M.S.), has a graduate level certificate in Data Science from Harvard, done other graduate work in Management Science and Applied Mathematics, and is addicted to courses through Udacity, EdX, and Coursera.

Tuesday December 5, 2017 3:45pm - 4:13pm
Srinivasa Ramanujan Stage Computer History Museum

3:45pm

Autokazanova42 - Marios Michailidis - H2O.ai
Recent world no.1 Kaggle Grandmaster, Marios Michailidis, is now a Research Data Scientist at H2O.ai. He is finishing his PhD in machine learning at the University College London (UCL) with a focus on ensemble modeling and his previous education entails a B.Sc in Accounting Finance from the University of Macedonia in Greece and an M.Sc. in Risk Management from the University of Southampton. He has gained exposure in marketing and credit sectors in the UK market and has successfully led multiple analytics’ projects based on a wide array of themes including: acquisition, retention, recommenders, uplift, fraud detection, portfolio optimization and more. Before H2O.ai, Marios held the position of Senior Personalization Data Scientist at dunnhumby where his main role was to improve existing algorithms, research benefits of advanced machine learning methods, and provide data insights. He created a matrix factorization library in Java along with a demo version of personalized search capability. Prior to dunnhumby, Marios has held positions of importance at iQor, Capita, British Pearl, and Ey-Zein.  At a personal level, he is the creator and administrator of KazAnova, a freeware GUI for quick credit scoring and data mining which is made absolutely in Java. In addition, he is also the creator of StackNet Meta-Modelling Framework. His hobbies include competing in predictive modeling competitions and was recently ranked 1st out of 465,000 data scientists on the popular data competition platform, Kaggle.

Tuesday December 5, 2017 3:45pm - 4:23pm
Maryam-Curie Stage Computer History Museum

4:15pm

Enterprise Chatbots: Looking Beyond Telling the Weather - Sanjana Reddy - SAP

I like telling stories using data. I'm a Data Scientist who works on helping machines to read and comprehend words. I graduated from University of Southern California with a Masters in Spring 2016 and now work at SAP Labs with the mission to empower enterprise users with Conversational AI.



Tuesday December 5, 2017 4:15pm - 4:43pm
Srinivasa Ramanujan Stage Computer History Museum

4:25pm

Kaggle Grandmaster Panel
Tuesday December 5, 2017 4:25pm - 5:10pm
Maryam-Curie Stage Computer History Museum

4:27pm

AI in Enterprise Panel
We'll explore how AI is transforming many industries including automotive, energy, healthcare and insurance.

This panel will be moderated by Rosalie Bartlett, Director of Community and Content Management at H2O.ai. She's excited to be joined by four fantastic panelists:
- Devon Bernard, VP Engineering, Enlitic
- Jitender Aswani, VP Products, Design and Analytics, Kespry
- Todd Mostak, CEO, MapD
- William Merchan, CSO, DataScience.com

Tuesday December 5, 2017 4:27pm - 5:10pm
Paul Erdos Stage Computer History Museum

4:45pm

Open Mic
Tuesday December 5, 2017 4:45pm - 5:10pm
Srinivasa Ramanujan Stage Computer History Museum

5:10pm

5:15pm

Event Concludes
Tuesday December 5, 2017 5:15pm - 5:20pm
Computer History Museum