Michael comes to Metis from General Electric where he worked to establish the company’s data science strategy and capabilities for field services and to build solutions supporting global operations, risk, engineering, sales, and marketing. He also taught data science and machine learning for General Assembly. Prior to GE, Michael spent several years as a data […]

Soumith Chintala is a Researcher at Facebook AI Research, where he works on deep learning, reinforcement learning, generative image models, agents for video games and large-scale high-performance deep learning. Prior to joining Facebook in August 2014, he worked at MuseAmi, where he built deep learning models for music and vision targeted at mobile devices. He […]

Furong Huang is a 6th year Ph.D. Candidate from UC Irvine working with Professor Anima Anandkumar. Her research interests lie in developing scalable and parallel algorithms for large-scale data using statistical models. She has worked on non-convex function optimization such as finding tensor decomposition using stochastic gradient descent; developing fast detection algorithm to discover hidden […]

Damien Lefortier is a Senior Machine Learning Engineer and Tech Lead in the Prediction Machine Learning team at Criteo where he has been actively involved in the development of Criteo’s large scale distributed machine learning library as well as in improving Criteo’s predictive algorithms for ad targeting. Before Criteo, Damien worked 3 years in the […]

Brad Klingenberg is the Director of Styling Algorithms at Stitch Fix in San Francisco. His team uses data and algorithms to improve the selection of merchandise sent to clients. Prior to joining Stitch Fix Brad worked with data and predictive algorithms at financial and technology companies. He studied applied mathematics at the University of Colorado […]

Andy Feng is a Distinguished Architect at Yahoo leading the architecture and design of nextgen Big Data platforms as well as machine learning initiatives. He is a PPMC member and commiter of the Apache Storm project and a contributor to the Apache Spark project. He served as a track chair and program committee member at […]

Alessandro Magnani received his Ph.D. and M.S. from Stanford University in Electrical Engineering. He is currently a data scientist at @WalmartLabs, working on product classification and attribute extraction. Prior to that, he was a research scientist at Adchemy where he worked on optimization algorithms for online advertising. His current interests are machine learning, large scale […]

Braxton is the technical lead and founder of Ufora, a software company that has built an adaptively distributed, implicitly parallel runtime. Before founding Ufora with backing from Two Sigma Ventures and others, Braxton led the ten-person MBS/ABS Credit Modeling team at Ellington Management Group, a multi-billion dollar mortgage hedge fund. He holds a BS (Mathematics), […]

Isabelle Guyon is an independent consultant, specialized in statistical data analysis, pattern recognition and machine learning. Her areas of expertise include computer vision and bioinformatics. Her recent interest is in applications of machine learning to the discovery of causal relationships. Prior to starting her consulting practice in 1996, Isabelle Guyon was a researcher at AT&T […]

Alex Smola is the Manager of the Cloud Machine Learning Platform at Amazon. Prior to his role at Amazon, Smola was a Professor in the Machine Learning Department of Carnegie Mellon University and cofounder and CEO of Marianas Labs. Prior to that he worked at Google Strategic Technologies, Yahoo Research, and National ICT Australia. Prior […]

Subutai Ahmad is the VP of Research at Numenta, a company focused on Machine Intelligence. Our technology, Hierarchical Temporal Memory (HTM), is a detailed computational framework based on principles of the brain. Our HTM learning algorithms are available through the NuPIC open source community and are embedded in our commercial streaming analytics applications. Subutai’s experience […]

Narayanan Sundaram is a research scientist in Intel’s Parallel Computing Lab. His research interests include large scale graph analytics and machine learning. He has worked on several big data and high performance computing problems, with recent emphasis on developing fast, distributed graph analytics frameworks. He has also worked on making computer vision and machine learning […]

Ben Hamner is Kaggle’s co-founder and CTO at Kaggle, he currently’s focused on creating tools that empower data scientists to frictionlessly collaborate on analytics and promote their results. He has worked with machine learning across many domains, including natural language processing, computer vision, web classification, and neuroscience. Prior to Kaggle, Ben applied machine learning to […]

Deep Learning Engineer at Skymind.io. Previous experience included data science and engineering at Change.org and a comprehensive consulting career. I have a passion for working on machine learning problems at scale and AI.

Dr.Raji Balasuubramaniyan working as a senior data scientist at Manheim, Atlanta. Previously she worked for Center for Disease Control and Prevention as a Bioinformatics scientist contractor and did research on Influenza viruses. She received her PhD in Bioinformatics from Max-Planck Institute for terrestrial Microbiology, Marburg Germany. Her interest is on wide variety of topics in […]

Working as a Data Scientist at TACC, a Supercomputer center at UT Austin. I work on machine learning algorithms for predictive modeling, sentiment analysis, recommender systems, statistical modeling, natural language processing, text mining of unstructured big data. I have worked as a Data Architect for 3 years for the state of Utah. I have done […]

Hank is a Data Scientist & Hacker at H2O. Hank comes to H2O with a background turning data into products and system solutions and loves helping others find value in their data. He has a deep background in the the application domains of telematics, remote sensing, logistics, manufacturing, agriculture, and the Internet of Things. Before […]

Jason is a Senior Solutions Architect at Qubole, where he works with prospects and customers to perform massive ad hoc queries in the public cloud. Prior to joining Qubole, Jason served as a technical architect for enterprise solutions spanning centralized logging, business intelligence, data analytics, private cloud infrastructure, distributed systems and computational grids within financial […]

Maja is software engineer at Facebook, working on Data Infrastructure for iterative and graph processing team. She is PMC member of Apache Giraph, open source project which Facebook uses for doing large scale analytics. She makes Giraph scale to Facebook data sizes, and develops highly performant algorithms on top of it, with current focus on […]

Dr. Gilmore is currently a data scientist on the team at Ayasdi where she specializes in highly complex and dimensional data across a variety of industries. Prior to joining Ayasdi, Allison served as a National Science Foundation Post-Doctoral Fellow and an Assistant Adjunct Professor in mathematics at the University of California Los Angeles. Dr. Gilmore […]

Ce is a postdoctoral researcher in the Department of Computer Science at Stanford University. He is working with Christopher Ré on problems related to data management and database systems. Ce is especially interested in understanding how to build a general platform for the next generation of analytics tasks that are probabilistic, Web-scale, and declarative to […]

Jennifer Marsman is a Principal Developer Evangelist in Microsoft’s Developer and Platform Evangelism group, where she educates developers on Microsoft’s new technologies. In this role, Jennifer is a frequent speaker at software development conferences across the United States. In 2009, Jennifer was chosen as “Techie whose innovation will have the biggest impact” by X-OLOGY for […]

Jorge Castañón hails from Mexico City and received his Ph.D. in Computational and Applied Mathematics from Rice University. He has a genuine passion for data science and machine learning applications of any kind, especially imaging problems. Since 2007, he is been developing numerical optimization models and algorithms for regularization and inverse problems. At IBM, Jorge […]

Jorge Silva received his PhD in Electrical and Computer Engineering from Instituto Superior Técnico (IST), Lisbon, Portugal, in 2007. From 2007 to 2012 he was a research scientist at Duke University, where he applied statistical models to large-scale problems, e.g., unsupervised learning, analysis of multi-modal data, recommender systems and social networks. Since 2012 he is […]

Pedro Domingos is a professor of computer science at the University of Washington in Seattle. He is a winner of the SIGKDD Innovation Award, the highest honor in data science. He is a Fellow of the Association for the Advancement of Artificial Intelligence, and has received a Fulbright Scholarship, a Sloan Fellowship, the National Science […]

Joseph is an Apache Spark committer and works at Databricks on MLlib, Spark’s Machine Learning library. Previously, he received his Ph.D. in Machine Learning from Carnegie Mellon University, where he worked on probabilistic graphical models and parallel sparse regression. He also researched peer grading systems and sparse models during postdoctoral study at the University of […]

Robert is currently a third year Ph.D. student at the NYU Stern School of Business in the Information Systems group where he works on causal inference and machine learning problems with Professor Foster Provost. Simultaneously, he is a data science intern at Integral Ad Science where he explores the causal effects of online advertisements using […]

Ehtsham Elahi is a Senior Research Engineer in the Personalization Science and Engineering group at Netflix where his focus is on Personalized video ranking algorithms. His main research area is Probabilistic Graphical Models for modeling rich user behavior and their large scale implementations to use them in Netflix Personalization Algorithms. Prior to Netflix, Ehtsham worked […]

Ray has 25 years experience in the software industry as a programmer and software architect. As CTO of Simularity, a predictive analytics software company, Ray has created Simularity’s High Performance Correlation Engine, Dynamic Classifier, and Time Series Analysis products. Prior to Simularity, Ray was a Senior Principal Technologist at Wind River, where he designed embedded […]

Shiva Amiri is the Director of Data Science at Zymergen Inc. a technology company in the San Francisco Bay Area focused on Biology, Automation and Data Science. She was previously the CEO of BioSymetrics Inc., a machine learning company specializing in complex biomedical data. Prior to BioSymetrics she was the Chief Product Officer at Real […]

Dr. Ronald P. Menich, Chief Data Scientist from Predictix, LLC, describes his firm’s experience in applying machine learning to retail demand forecasting, utilizing many different attributes / features/ causal factors / demand-drivers. Ron Menich is EVP and Chief Data Scientist and Predictix, LLC, where he leads a team of machine learning and retail implementation personnel, […]

Mathias Brandewinder has been developing software professionally for about 10 years, with a focus on forecasting and risk analysis models. He is a Microsoft F# MVP, and speaks regularly on functional programming and related topics at conferences worldwide. He is the author of “Machine Learning Projects for .NET Developers” (Apress), and the founder of Clear […]

Jeremy Stanley is currently Founder and CTO of a Stealth startup building a foundational new layer for the modern cloud data warehouse stack. Most recently VP Data Science at Instacart, focused on machine learning for logistics and marketplace discovery. Previously led data science and engineering at Sailthru, building personalization tools for e-commerce and publishing companies. […]

Irina Rish is a researcher at the AI Foundations department of the IBM T.J. Watson Research Center. She received MS in Applied Mathematics from Moscow Gubkin Institute, Russia, and PhD in Computer Science from the University of California, Irvine. Her areas of expertise include artificial intelligence and machine learning, with a particular focus on probabilistic […]

Ilona Murynets is a scientist at the Chief Security Office at AT&T. She obtained her Ph.D. in Systems Engineering at School of Systems and Enterprises, Stevens Institute of Technology. Her dissertation received an Outstanding Dissertation Award. Ilona holds B.Sc. degree in Mathematics and M.S. degree in Statistics, Financial & Actuarial Mathematics from Kiev National Taras […]