Predictive Analytics World for Industry 4.0 Las Vegas 2020
May 31-June 4, 2020 – Caesars Palace, Las Vegas
Former Product Lead, Machine Learning, Lyft
Gil serves as the head of Lyft's Machine Learning Platform. Previously he was co-founder of Octarine, a security startup, and VP Product of Reflektion, an e-commerce personalization company, and AppDirect, the largest B2B app marketplace. Gil also spent a few years in product positions at Google in the Ads group, where he helped integrate YouTube and DoubleClick after their acquisition.
Gil Arditi is speaker of the following session:
With over 34 years of experience in solving engineering problems, Raja currently works as a Senior Engineer in the Global Research arm of General Electric (GE) in Bangalore, India. He is an 'Engineering Predictive Analytics' professional with deep expertise in Artificial Intelligence, Machine Learning, Data Science, and Physics across multiple verticals including Aviation, Healthcare, Oil and Gas, Nuclear, Thermal, Steam, Renewables, and Transportation.
In GE Global Research, he tackles cutting-edge technology problems using Machine Learning and Artificial Intelligence, to create fused text mining and numerical predictive analytics algorithms. Combining text, numerical data, video and images opens up new ways to solve practical yet complex engineering problems. This combination acts as a force-multiplier in bringing out engineering insights that are otherwise not easy to obtain. Raja specializes in monetizing these insights. Raja holds 18 patents and trade secrets in this area, and has authored several pioneering papers with over 100 citations
Rajagopalan Chandrasekharan is speaker of the following session:
Martin is trained as a chemist and focused on data analytics and scientific computing in his master program. After some years as a freelancing data scientist in various industries, Martin joined Covestro, a great place to solve problems like recycling of polymers and energy saving.
Martin Elstner is speaker of the following session:
Head of Responsible Innovation, Global Affairs
Jen Gennai leads Google’s Responsible Innovation team which is responsible for operationalizing Google’s AI Principles, ensuring that Google’s products have fair and ethical outcomes on individual users and the world. Her team works with product and engineering, leveraging a multidisciplinary group of experts in ethics, human rights, user research, racial justice and gender equity to validate that products and outputs align with our commitments to fairness, privacy, safety, societal benefit and more. Before she co-authored the AI Principles and founded Responsible Innovation, Jen worked on machine learning fairness and founded the Ethical ML team in Trust & Safety.
Jen Gennai is speaker of the following session:
Principal Data Scientist
Samira Golsefid is a Principal data scientist at Paypal, she is responsible for leading merchant on boarding and risk evaluation for risk as Service. In addition to that she is managing the key customer portfolio of Paypal risk platform. Samira joined Paypal in early 2018 and brings 15 years industry experience in Machine Learning and Artificial Intelligent.
In 2007 she founded her own company with a focus on predicting customer lifetime value and international market segmentation. Prior to Paypal, she led data science projects at Flybits and Toshiba. Samira holds a PhD degree in Industrial Engineering from Amirkabir University of Technology (Tehran Polytechnic), Iran. She is an expert in unsupervised learning and uncertainty modeling and has published around 30 papers in this area.
Samira Golsefid is speaker of the following session:
Rohit Kewalramani is a Data Scientist at KPIT Technolgies. He is currently hacking a way to use Bayesian Learning to create Automotive Learning Platform. He graduated as a Computer Engineer in 2015 and since then he has worked as Data Scientist into multiple domains such as Life Sciences, Automotive and Consulting. He has been rapidly taking POCs to Production. In a short span of career he has already filed for 2 patents and has a few publications under his name. Rohit expertises in developing large scale Deep / Machine Learning models over unstructured data such as sensors(Automotive / IIoT), Textual Data (NLP), etc.
Rohit Kewalramani is speaker of the following session:
Director, Advanced Analytics
Dr. Andrei Khurshudov is a Director of Advanced Analytics at Caterpillar Digital. Andrei specializes in Big Data Analytics, the Internet of Things, Cloud storage and computing, in-memory computing, and data storage reliability and technology. Andrei has spent more than 10 years at Seagate, where he was a Chief Technologist and managed various R&D organizations in such areas as data analytics, cloud technology, quality and reliability, and others. While at Seagate, Andrei created the Big Data Analytics and Insights organization, which focused on applying advanced analytics and machine learning concepts to product quality, reliability, manufacturing, and remote device monitoring, as well as finances, sales, pricing, and other critical areas where data-driven decisions are important.
In the recent past, Dr. Khurshudov served as a Chief Data Officer at Formulus Black, a New Jersey-area startup that is developing software for in-memory computing and as a CTO and Chief Data Officer at Alchemy IoT, a Boulder-area startup creating cloud-based analytics solutions for the Internet of Things. Andrei has a Ph.D. in Engineering and, before joining Seagate, worked at such companies as IBM, Hitachi Global Storage, and Samsung. Andrei has numerous publications, patents, conference presentations, and a book.
Andrei Khurshudov is speaker of the following session:
Senior Data Scientist
Jaya Mathew is a Senior data scientist at Microsoft where she is part of the Artificial Intelligence and Research team. Her work focuses on the deployment of AI and ML solutions to solve real business problems for customers across multiple domains. Prior to joining Microsoft, she has worked with Nokia and Hewlett-Packard on various analytics and machine learning use cases. She holds an undergraduate as well as a graduate degree from the University of Texas at Austin in Mathematics and Statistics respectively.
Jaya Mathew is speaker of the following session:
Global Digital Strategy and Business Development
Terry Miller has spent nearly 10 years working with OEMs to evaluate and optimize industrial processes through increased performance of their machines. After finishing a Master’s Degree in Predictive Analytics, Terry began formally training and deploying traditional statistical models, as well as Machine Learning algorithms for asset-predictive (explanatory) maintenance and process optimization, specifically on industrial robots.
Terry Miller is speaker of the following session:
Vadim Pinskiy PhD
VP of R&D
Vadim Pinskiy is the VP of Research and Development at Nanotronics, where he oversees product development, short term R&D and long term development of AI platforms. Vadim completed his doctorate work in Neuroscience, focused on mouse neuroanatomy using high throughput whole slide imaging and advanced tracing techniques. Prior to that, completed Masters in Biomedical Engineering from Cornell and Bachelor's and Master’s in Electrical and Biomedical from Stevens Institute of Technology. Vadim is interested in applying advanced AI methods and systems to solving practical problems in biological and product manufacturing.
Vadim Pinskiy PhD is speaker of the following session:
Senior Computer Scientist
Andy Ramlatchan is a member of the Data Science team at NASA Langley Research Center where he works with researchers and engineers to develop data driven models to supplement and validate physics based models for computational materials science research. He previously worked within the Intelligence Community for the United States government in the area of cyber security. Andy is currently a PhD candidate in Computer Science at Old Dominion University, in Norfolk, Virginia where his research work focuses on matrix factorization and higher dimensional tensor completion for data recovery.
Andy Ramlatchan is speaker of the following session:
Eric Siegel, Ph.D., founder of the Predictive Analytics World conference series and executive editor of The Machine Learning Times, makes the how and why of predictive analytics understandable and captivating. He is the author of the award-winning Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, a former Columbia University professor who used to sing to his students, and a renowned speaker, educator, and leader in the field.
Eric has appeared on Bloomberg TV and Radio, Business News Network (Canada), Fox News, Israel National Radio, NPR Marketplace, Radio National (Australia), and TheStreet. He and his book have been featured in Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, The Financial Times, Forbes, Forrester, Fortune, Harvard Business Review, The Huffington Post, The New York Review of Books, Newsweek, Quartz, Salon, Scientific American, The Seattle Post-Intelligencer, The Wall Street Journal, The Washington Post, and WSJ MarketWatch. Follow him at @predictanalytic.
Eric Siegel is speaker of the following session:
A Charles Thomas
Chief Data & Analytics Officer
Charles is an Enterprise Data and Analytics leader who maximizes the impact Data, Insights, and Artificial Intelligence have on business results, operational efficiency & effectiveness, and fact-based cultural change. A rare three-time Chief in the data domain, he’s led large scale data and analytics efforts for brands such as HP, USAA (where he was its first Chief Data and Analytics Officer), and Wells Fargo (its first Chief Data Officer and Head, Enterprise Data & Analytics).
He has expertise leveraging data to drive strategy across B2B and B2C segments, digital and traditional routes to market, multiple regions, and industry verticals such as energy, high-tech, pharma, retail, financial services and automotive.
Charles is committed to increasing the role of "Activist Analysts" in organizations, and driving a diversity and inclusion agenda in technology, particularly in the Data Sciences. He formerly sat on the University of California at Berkeley’s School of Information advisory panel and currently serves as a Director at the United Negro College Fund, Inc. in Washington, DC.
He holds a PhD in Sociology (with a concentration in Organizational Behavior & studies in Quantitative Methods) from Yale University, is headquartered in Detroit, and lives in Austin with his wife and two children. Select external communications Charles is featured in are listed below.
A Charles Thomas is speaker of the following session: