ODSC is the best community data science event on the planet. There are other events that cover special topics, or industries, etc., but ODSC is comprehensive and totally community-focused: it's the conference to engage, to build, to develop, and to learn from the whole data science community.
Kirk Borne - Principal Data Scientist and Executive Advisor at Booz Allen Hamilton @ ODSC East 2019
Hybrid Attendees
Build AI Better
Over the course of 3 days, ODSC East will provide expert-led instruction in machine learning, deep learning, NLP, MLOps, and more through hands-on training sessions, immersive workshops, and talks. You’ll also have the chance to share insights and build new connections through a wide range of events from the ODSC Networking Reception to the Ai+ Career Expo.
ODSC is the best community data science event on the planet. There are other events that cover special topics, or industries, etc., but ODSC is comprehensive and totally community-focused: it's the conference to engage, to build, to develop, and to learn from the whole data science community.
Kirk Borne - Principal Data Scientist and Executive Advisor at Booz Allen Hamilton @ ODSC East 2019
ODSC is the best community data science event on the planet. It is comprehensive and totally community-focused: it’s the conference to engage, to build, to develop, and to learn from the whole data science community.
Kirk Borne – Principal Scientist and Executive Advisor at Booz Allen Hamilton @ ODSC East 2019
What a spectacular first day attendingODSC East. This has been a wonderful day full of new knowledge, new connections, and the discovery of problems to solve and solutions alike.
Data Scientist, USA
It’s been such a wonderful week learning about all the incredible work that’s being done within the field of data science – with too many incredible sessions to list at the moment.
Machine Learning Engineer | Data Scientist, USA
It was a wonderful experience, and I literally am going back with an enhanced understanding of so many concepts, while learning about many new products and theories. Thanks, ODSC for this opportunity.
Product Specialist, India
The Leading Conference for
MACHINE LEARNING
DATA SCIENCE
DEEP LEARNING
DATA ANALYTICS
DATA ENGINEERING
NLP & NLU
RESPONSIBLE AI
CYBERSECURITY
MLOPS
COMPUTER VISION
The leading conference for Data Science using the latest languages, tools, and frameworks
12 Focus Areas. 3 Days. One Machine Learning Conference
The largest applied machine learning conference is now 3 days, including an extra day for our mini-bootcamp. Choose from in-person or virtual that includes, 3 full training days, and 2 talks/workshops days. You get even more talks, training, and workshops spread over 8 focus areas. Accelerate your machine learning knowledge, training, and network all in one event.
Why You Should Attend the Leading Data Science Conference
HANDS-ON TRAINING
Build job-ready skills and stay up-to-date with the latest advances in machine learning, NLP, data analytics, responsible AI, and more with ODSC East’s expert-led, immersive, training sessions.
With 300 hours of content, the conference features a wide range of sessions for data scientists at every level, from beginner to expert.
NETWORKING
Connect with and learn from thousands of your peers and data science experts during ODSC East’s numerous in-person and virtual events. Meet with our expert speakers to ask questions and continue the discussion during Meet the Speaker and Book Signing events. Or, set a goal to meet as many of your peers as possible at the ODSC Networking Reception.
AI EXPO AND DEMO HALL
Meet representatives from some of the leading AI startups and companies at the AI Expo and Demo Hall. Visit their booths, or see their products demoed live to learn about the latest advancements in AI in enterprise and discover how to build AI better in your organization.
You are able to buy your ticket via Invoice/Purchase Order (PO).
Please submit your request to receive a Purchase Order HERE.
Group Discounts
If you have a group of 3 to 13 or more, please email us at info@odsc.com to enquire about additional discounts. Please mention the size of your group and the types of passes required.
Donate to our Fundraise
For this year’s event, ODSC will double donations and fundraising to Support of Ukraine. Please support Ukraine, and its refugees and help those who stayed fighting for their country. All donations would be sent to the Come Back Alive Foundation.
Please donate what you can via our registration. No purchase is necessary to donate and 100% of funds raised are donated.
Irina Rish is a Full Professor in the Computer Science and Operations Research Department at the Université de Montréal (UdeM) and a core faculty member of MILA – Quebec AI Institute. She holds Canada Excellence Research Chair (CERC) in Autonomous AI and a Canadian Institute for Advanced Research (CIFAR) Canada AI Chair. She received her MSc and PhD in AI from University of California, Irvine and MSc in Applied Mathematics from Moscow Gubkin Institute. Dr. Rish’s research focus is on machine learning, neural data analysis and neuroscience-inspired AI. Before joining UdeM and MILA in 2019, Irina was a research scientist at the IBM T.J. Watson Research Center, where she worked on various projects at the intersection of neuroscience and AI, and led the Neuro-AI challenge. She received multiple IBM awards, including IBM Eminence & Excellence Award and IBM Outstanding Innovation Award in 2018, IBM Outstanding Technical Achievement Award in 2017, and IBM Research Accomplishment Award in 2009. Dr. Rish holds 64 patents, has published over 80 research papers in peer-reviewed conferences and journals, several book chapters, three edited books, and a monograph on Sparse Modeling.
Associate Professor of Computer Information SystemsQuinnipiac University
Tamilla Triantoro, PhD
Tamilla Triantoro is an Associate Professor of Computer Information Systems at Quinnipiac University and a leader of the Masters Program in Business Analytics. She was previously an Academic Director of Data Analytics at the University of Connecticut. Dr. Triantoro is an author, speaker, researcher, and educator in the fields of artificial intelligence, data analytics, user experience with technology, and the future of work. She received her Ph.D. from the City University of New York where she researched online user behavior. Dr. Triantoro presents her research around the world, attempting to demystify the complexity of today’s digital world and to make it understandable and relevant to business professionals and the general audience.
Chief Data ScientistNebula.io
Dr. Jon Krohn
Jon Krohn is Chief Data Scientist at the machine learning company untapt. He authored the book Deep Learning Illustrated, which was released by Addison-Wesley in 2019 and became an instant #1 bestseller that was translated into six languages. Jon is renowned for his compelling lectures, which he offers in-person at Columbia University, New York University, and the NYC Data Science Academy, as well as online via O’Reilly, YouTube, and his A4N podcast on A.I. news. Jon holds a doctorate in neuroscience from Oxford and has been publishing on machine learning in leading academic journals since 2010.
ProfessorHarvard University
Ariel Procaccia, PhD
Ariel Procaccia is Gordon McKay Professor of Computer Science at Harvard University. He works on a broad and dynamic set of problems related to AI, algorithms, economics, and society. He has helped create systems and platforms that are widely used to solve everyday fair division problems, resettle refugees, mitigate bias in peer review and select citizens’ assemblies. To make his research accessible to the public, he regularly writes opinion and exposition pieces for publications such as the Washington Post, Bloomberg, Wired and Scientific American. His distinctions include the Social Choice and Welfare Prize (2020), Guggenheim Fellowship (2018), IJCAI Computers and Thought Award (2015) and Sloan Research Fellowship (2015).
Prof. | VP | Distinguished ScientistUniv. of Pennsylvania | Amazon AWS
Dan Roth, PhD
Dan Roth is the Eduardo D. Glandt Distinguished Professor at the Department of Computer and Information Science, University of Pennsylvania, a VP/Distinguished Scientist at Amazon AWS, and a Fellow of the AAAS, the ACM, AAAI, and the ACL.
In 2017 Roth was awarded the John McCarthy Award, the highest award the AI community gives to mid-career AI researchers. Roth was recognized “for major conceptual and theoretical advances in the modeling of natural language understanding, machine learning, and reasoning.”
Roth has published broadly in machine learning, natural language processing, knowledge representation and reasoning, and learning theory, and has developed advanced machine learning based tools for natural language applications that are being used widely. Until February 2017 Roth was the Editor-in-Chief of the Journal of Artificial Intelligence Research (JAIR). Roth has been involved in several startups; most recently he was a co-founder and chief scientist of NexLP, a startup that leverages the latest advances in Natural Language Processing (NLP), Cognitive Analytics, and Machine Learning in the legal and compliance domains. NexLP was acquired by Reveal in 2020. Prof. Roth received his B.A Summa cum laude in Mathematics from the Technion, Israel, and his Ph.D. in Computer Science from Harvard University in 1995.
Assistant ProfessorMIT
Jacob Andreas, PhD
Jacob Andreas is the X Consortium Assistant Professor at MIT. His research aims to build intelligent systems that can communicate effectively using language and learn from human guidance. Jacob earned his Ph.D. from UC Berkeley, his M.Phil. from Cambridge (where he studied as a Churchill scholar) and his B.S. from Columbia. As a researcher at Microsoft Semantic Machines, he founded the language generation team and helped develop core pieces of the technology that powers conversational interaction in Microsoft Outlook. He has been the recipient of Samsung’s AI Researcher of the Year award, MIT’s Kolokotrones teaching award, and paper awards at NAACL and ICML.
Full ProfessorTechnical University of Darmstadt
Iryna Gurevych, PhD
Iryna Gurevych (PhD 2003, U. Duisburg-Essen, Germany) is professor of Computer Science and director of the Ubiquitous Knowledge Processing (UKP) Lab at the Technical University (TU) of Darmstadt in Germany. Her main research interests are in machine learning for large-scale language understanding and text semantics. Iryna’s work has received numerous awards. Examples are the ACL fellow award 2020 and the first Hessian LOEWE Distinguished Chair award (2,5 mil. Euro) in 2021. Iryna is co-director of the NLP program within ELLIS, a European network of excellence in machine learning. She is currently the president of the Association of Computational Linguistics. In 2022, she received an ERC Advanced Grant to support her vision for the next big step in NLP “InterText – Modeling Text as a Living Object in a Cross-Document Context”.
Joe Dery joined Western Governors University’s College of IT as the VP & Dean of Data Analytics in summer, 2022. At WGU, Joe is working to help more than 3,000 current analytics students learn how to effect change in their professional roles – surgically balancing a combination of mathematics, data management, programming, and business influence skills. Prior to joining academia full-time, Joe spent much of his corporate career working for EMC – and later, Dell Technologies – where he joined as a “hands-on-keyboard” Data Scientist in 2011. Joe went on to hold leadership positions in Dell’s Sales, Finance, and Supply Chain organizations driving efforts in Data Science, Business Intelligence, Digital Strategy, and Digital Transformation. Across these domains, Joe’s efforts touched a wide variety of business problems, including ML-driven sales quota allocations, sales forecasting & opportunity prioritization, customer cross-sell/whitespace targeting, addressable marketing opportunity sizing, sales territory optimization, supply chain planning optimization, data/analytics literacy training, and self-service BI. Building from his experiences, Joe is often invited to speak on the crucial role of decision intelligence frameworks, change management, and “improv” in bringing analytics solutions to life. Joe holds a Ph.D in Business Analytics & an M.S. in Marketing Analytics, both from Bentley University.
Chief EvangelistHugging Face
Julien Simon
Julien is currently Chief Evangelist at Hugging Face. He’s recently spent 6 years at Amazon Web Services where he was the Global Technical Evangelist for AI & Machine Learning. Prior to joining AWS, Julien served for 10 years as CTO/VP Engineering in large-scale startups.
Data Scientist | Bloomberg | Author of Hands-On Data Analysis with Pandas
Stefanie Molin
Stefanie Molin is a software engineer and data scientist at Bloomberg in New York City, where she tackles tough problems in information security, particularly those revolving around data wrangling/visualization, building tools for gathering data, and knowledge sharing. She is also the author of “Hands-On Data Analysis with Pandas,” which is currently in its second edition. She holds a bachelor’s of science degree in operations research from Columbia University’s Fu Foundation School of Engineering and Applied Science, as well as a master’s degree in computer science, with a specialization in machine learning, from Georgia Tech. In her free time, she enjoys traveling the world, inventing new recipes, and learning new languages spoken among both people and computers.
Associate Professor of AnalyticsInstitute for Advanced Analytics at NC State University
Aric LaBarr, PhD
A Teaching Associate Professor in the Institute for Advanced Analytics, Dr. Aric LaBarr is passionate about helping people solve challenges using their data. There he helps design the innovative program to prepare a modern workforce to wisely communicate and handle a data-driven future at the nation’s first Master of Science in Analytics degree program. He teaches courses in predictive modeling, forecasting, simulation, financial analytics, and risk management. Previously, he was Director and Senior Scientist at Elder Research, where he mentored and led a team of data scientists and software engineers. As director of the Raleigh, NC office he worked closely with clients and partners to solve problems in the fields of banking, consumer product goods, healthcare, and government. Dr. LaBarr holds a B.S. in economics, as well as a B.S., M.S., and Ph.D. in statistics — all from NC State University.
Director & Senior Staff Scientist | Joint Adjunct ProfessorAlibaba | Zhejiang University
Dr. Hongxia Yang, PhD
Dr. Hongxia Yang, PhD from Duke University, led the team to develop AI open sourced platforms and systems such as AliGraph, M6, Luoxi. Dr. Yang has published nearly 100 top conference and journal papers, and held more than 20 patents. She has been awarded the highest prize of the 2019 World Artificial Intelligence Conference, Super AI Leader (SAIL Award), the second prize of the 2020 National Science and Technology Progress Award (China’s Top tech award), the first prize of Science and Technology Progress of the Chinese Institute of Electronics in 2021, and the Forbes China Top 50 Women in Science and Technology in 2022. She used to work as the Senior Staff Data Scientist and Director in Alibaba Group, Principal Data Scientist at Yahoo! Inc and Research Staff Member at IBM T.J. Watson Research Center, joint adjunct professor at Zhejiang University Shanghai Advanced Research Institute respectively.
Python & Data Science Corporate Trainer | ConsultantMetaSnake
Matt Harrison
Matt Harrison has been using Python since 2000. He runs MetaSnake, a Python and Data Science consultancy and corporate training shop. In the past, he has worked across the domains of search, build management and testing, business intelligence, and storage.
He has presented and taught tutorials at conferences such as Strata, SciPy, SCALE, PyCON, and OSCON as well as local user conferences.
Julia Lintern currently works as an instructor for the Metis Data Science Flex Program. Previously, she worked as a Data Scientist for the New York Times. Julia began her career as a structures engineer designing repairs for damaged aircraft. Julia holds an MA in applied math from Hunter College, where she focused on visualizations of various numerical methods and discovered a deep appreciation for the combination of mathematics and visualizations. During certain seasons of her career, she has also worked on creative side projects such as Lia Lintern, her own fashion label.
Sr. Director - Data Science & ML EngineeringAmpersand
Daniel Gerlanc
Daniel Gerlanc has worked as a data scientist for more than decade and been writing software for nearly 20 years. He frequently teaches live trainings on oreilly.com and is the author of the video course Programming with Data: Python and Pandas. He has coauthored several open source R packages, published in peer-reviewed journals, and is a graduate of Williams College.
Thomas J. Fan is a Senior Software Engineer at Quansight Labs, working to sustain and evolve the PyData open-source ecosystem. He is a maintainer for scikit-learn, an open-source machine learning library written for Python. Previously, he worked at Columbia University, improving the interoperability between scikit-learn and AutoML systems. Thomas holds a Masters in Physics from Stony Brook University and a Masters in Mathematics from New York University.
Professor of Mathematics and Computer ScienceUC Berkeley
James Demmel, PhD
James Demmel is the Dr. Richard Carl Dehmel Distinguished Professor of Computer Science and Mathematics at the University of California at Berkeley, and former Chair of the EECS Dept. He also serves as Chief Strategy Officer for the start-up HPC-AI Tech, whose goal is to make large-scale machine learning much more efficient, with little programming effort required by users. Demmel’s research is in high performance computing, numerical linear algebra, and communication avoiding algorithms. He is known for his work on the widely used LAPACK and ScaLAPACK linear algebra libraries. He is a member of the National Academy of Sciences, National Academy of Engineering, and American Academy of Arts and Sciences; a Fellow of the AAAS, ACM, AMS, IEEE and SIAM; and winner of the IPDPS Charles Babbage Award, IEEE Computer Society Sidney Fernbach Award, the ACM Paris Kanellakis Award, the J. H. Wilkinson Prize in Numerical Analysis and Scientific Computing, and numerous best paper prizes.
Research EngineerIBM TJ Watson
Tejaswini Pedapati
Tejaswini Pedapati works at IBM Research. Her research is focused on interpretability and automating deep learning. To that end, she was involved in developing tools and algorithms to provide these capabilities for IBM products. She has a masters’ degree from Columbia University.
Leonardo De Marchi holds a Master in Artificial intelligence and has worked as a Data Scientist in the sports world, with clients such as the New York Knicks. He now works in Thomson Reuters as VP of Labs, and also provides consultancy and training for small and large companies. His previous experience includes being Head of Data Science and Analytics in Bumble, the largest dating site with over 500 million users, heading the team through acquisition and an IPO.
Associate ProfessorUniversity of Maryland
Jordan Boyd-Graber, PhD
Jordan is an associate professor in the University of Maryland Computer Science Department (tenure home), Institute of Advanced Computer Studies, iSchool, and Language Science Center. Previously, he was an assistant professor at Colorado’s Department of Computer Science (tenure granted in 2017). He was a graduate student at Princeton with David Blei.
His research focuses on making machine learning more useful, more interpretable, and able to learn and interact from humans. This helps users sift through decades of documents; discover when individuals lie, reframe, or change the topic in a conversation; or to compete against humans in games that are based in natural language.
Apache Spark Expert, Data Science Instructor and Consultant
Adam Breindel
Adam Breindel consults and teaches widely on Apache Spark and other technologies. Adam’s experience includes work with banks on neural-net fraud detection, streaming analytics, cluster management code, and web apps, as well as development at a variety of startup and established companies in the travel, productivity, and entertainment industries. He is excited by the way that Spark and other modern big-data tech remove so many old obstacles to system design and make it possible to explore new categories of interesting, fun, hard problems.
Director of the Center for Statistics and Analytical ResearchKennesaw State University
Bill Franks
Bill Franks is the Director of the Center for Statistics and Analytical Research at Kennesaw State University. He is also Chief Analytics Officer for The International Institute For Analytics (IIA) and serves on several corporate advisory boards. Franks is also the author of the books Winning The Room, Taming The Big Data Tidal Wave, The Analytics Revolution, and 97 Things About Ethics Everyone In Data Science Should Know. He is a sought after speaker and frequent blogger who has over the years been ranked a top global big data influencer, a top global artificial intelligence and big data influencer, a top AI influencer, and was an inaugural inductee into the Analytics Hall of Fame. His work, including several years as Chief Analytics Officer for Teradata (NYSE: TDC), has spanned clients in a variety of industries for companies ranging in size from Fortune 100 companies to small non-profit organizations. You can learn more at http://www.bill-franks.com.
Meg is currently a UX Researcher for Google Cloud AI and Industry Solutions, where she focuses her research on Explainable AI and Model Understanding. She has had a varied career working for start-ups and large corporations alike, in fields as varied as EdTech, weather forecasting, and commercial robotics. She has published and spoken on topics such as user research, information visualization, educational-technology design, human-robot interaction (HRI), and voice user interface (VUI) design. Meg is also a proud alumnus of Virginia Tech, where she received her Ph.D. in Human-Computer Interaction.
Vice President, Data Science & EngineeringDewpoint Therapeutics
Jesse Johnson
Jesse Johnson is Vice President of Data Science and Data Engineering at Dewpoint Therapeutics, a drug development Biotech startup founded in 2019 around a scientific field called biomolecular condensates. In this role, Jesse’s diverse set of experiences from academic math departments, engineering teams at Google, and data science teams at large, medium and small life science companies provide a unique perspective on the ways that data and wet lab teams communicate differently, or sometimes don’t communicate at all.
Global Head of Data Science and AnalyticsAmazon Music
Jeffrey Yau, PhD
Jeffrey is currently the Global Head of Data Science and Analytics at Amazon Music. Prior to Amazon, Jeffrey worked at WalmartLabs as the VP of Data Science, Data Engineering, and Platform Engineering. Before joining WalmartLabs, he pretty much spent my entire career in quantitative finance. His last role in the investment management industry was the Chief Data Scientist and Global Head of Data Science at AllianceBernstein (AB), a global investment management firm that managed almost $800B. Before AB, he was the VP and Head of Data Science at Silicon Valley Data Science, a startup acquired by Apple in 2017. Earlier in his career, he held various quantitative leadership positions, including the Corporate VP and Head of Risk Analytics and Quantitative Research at Charles Schwab Corporation, Director of Financial Risk Consulting at KPMG, and Assistant Director at Moody’s Analytics. Jeffrey enjoys academic research and teaching. He has taught finance, economics, machine learning, and statistics at University of Pennsylvania, Virginia Tech, Cornell, NYU, and UC Berkeley. He is a frequent speaker at national and international A.I., data science, and technology conferences, such as Spark&AI Summit, Strata, ODSC, PyCon, and many others. He holds a Ph.D. and an M.A. in Economics from the University of Pennsylvania and a B.S. in Mathematics and Economics from UCLA.
ODSC is proud to partner with numerous industry leaders providing organizations with the tools to accelerate digital transformation with AI. You can reach out to our Expo partners prior to the event for more information.
As part of the global data science community we value inclusivity, diversity, and fairness in the pursuit of knowledge and learning. We seek to deliver a conference agenda, speaker program, and attendee participation that moves the global data science community forward with these shared goals. Learn more on our code of conduct, speaker submissions, or speaker committee pages.
Stay current with the latest news and updates in open source data science. In addition, we’ll inform you about our many upcoming Virtual and in person events in Boston, NYC, Sao Paulo, San Francisco, and London. And keep a lookout for special discount codes, only available to our newsletter subscribers!
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