Thank you for joining us at ODSC East 2023
ODSC East 2024 Dates Announced Soon!
Speakers
Hours of Content
Companies
Kirk Borne - Principal Data Scientist and Executive Advisor at Booz Allen Hamilton @ ODSC East 2019
Hybrid Attendees
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 attending ODSC 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
MEET OUR ODSC 2023 ATTENDEES AND SPEAKERS
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 attending ODSC 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
MEET OUR ODSC 2023 ATTENDEES AND SPEAKERS
Upcoming ODSC Events
Missed ODSC East? Join us at our next conference, ODSC Europe in London, June 14-15th. Can’t make it In-Person? Join us virtually!
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 here.
GENERATE THE FUTURE WITH AI
Over the course of 3 days, you’ll have the opportunity to learn from some of the best and brightest minds in data science and AI. You’ll also learn about the latest tools and advances in the field, from generative models to new frameworks, and how you can utilize these in your own work.
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.
NETWORKING
Grow your network and connect with your peers from across the country and from a wide range of industries, You’ll also have the chance to meet with leading experts in transformative tools and techniques.
Conference Tracks
Online Registration Ends In
Registration & Discount Resources
In-person passes are sold out online, but you can still buy a pass on spot
Save 20% on Full Price
Save 20% on Full Price
Tickets available at a group rate (additional discount on the top of the website price)
* 4 Pre-Bootcamp live tutorials on Data Literacy, AI Literacy, Programming with Python, and SQL (Value $796) Check more info here.
Hotel DEAL
The Westin Copley Place
10 Huntington Avenue, Boston, MA 02116
For a limited time, hotel rooms start from just $369 + taxes and fees per night.
Book NOW here.
WHAT TO EXPECT
Please visit our What to Expect page here.
Pay by invoice/purchase order
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.
Past Keynotes & Track Keynotes
Featured Speakers & Instructors
Dr. Jon Krohn
Jon Krohn is Co-Founder and Chief Data Scientist at the machine learning company Nebula. He authored the book Deep Learning Illustrated, an instant #1 bestseller that was translated into seven languages. He is also the host of SuperDataScience, the data science industry’s most listened-to podcast. Jon is renowned for his compelling lectures, which he offers at leading universities and conferences, as well as via his award-winning YouTube channel. He holds a PhD from Oxford and has been publishing on machine learning in prominent academic journals since 2010.
Deep Learning with PyTorch and TensorFlow(Training)
NLP with GPT-4 and other LLMs: From Training to Deployment with Hugging Face and PyTorch Lightning(Training)
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”.
SQuARE: Towards Multi-Domain and Few-Shot Collaborating Question Answering Agents(Talk)
Allen Downey, PhD
Allen Downey is a Staff Scientist at DrivenData and professor emeritus at Olin College. He is the author of several books related to computer science and data science, including Think Python, Think Stats, Think Bayes, and Think Complexity. His blog, Probably Overthinking It, features articles about Bayesian statistics. He received his Ph.D. in Computer Science from U.C. Berkeley, and M.S. and B.S. degrees from MIT.
Causation, Collision, and Confusion: Avoiding the most dangerous error in statistics(Talk)
Jared Lander
Jared Lander is the Chief Data Scientist of Lander Analytics a data science consultancy based in New York City, the Organizer of the New York Open Statistical Programming Meetup and the New York R Conference and an Adjunct Professor of Statistics at Columbia University. With a masters from Columbia University in statistics and bachelors from Muhlenberg College in mathematics, he has experience in both academic research and industry. His work for both large and small organizations ranges from music and fundraising to finance and humanitarian relief efforts. He specializes in data management, multilevel models, machine learning, generalized linear models, data management and statistical computing. He is the author of R for Everyone: Advanced Analytics and Graphics, a book about R Programming geared toward Data Scientists and Non-Statisticians alike and is creating a course on glmnet with DataCamp.
Machine Learning in R Part I & II(Training)
Irina Rish, PhD
Irina Rish is an Associate 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.
Recent Advances in Foundation Models: Scaling Laws, Emergent Behaviors, and AI Democratization(Talk)
Florian Jacta
Florian Jacta is a specialist of Taipy, a low-code open-source Python package enabling any Python developers to easily develop a production-ready AI application. Package pre-sales and after-sales functions. He is data Scientist for Groupe Les Mousquetaires (Intermarche) and ATOS. He developed several Predictive Models as part of strategic AI projects. Also, Florian got his master’s degree in Applied Mathematics from INSA, Major in Data Science and Mathematical Optimization.
How to Build Stunning Data Science Web applications in Python – Taipy Tutorial(Workshop)
Bringing AI to Retail and Fast Food with Taipy’s Applications(Track Keynote)
Demo Session Title: Turning your Data/AI algorithms into full web apps in no time with Taipy
Abstract:
In the Python open-source ecosystem, many packages are available that cater to:
– the building of great algorithms
– the visualization of data
Despite this, over 85% of Data Science Pilots remain pilots and do not make it to the production
stage.
With Taipy, a new open-source Python framework, Data Scientists/Python Developers are able to
build great pilots as well as stunning production-ready applications for end-users.
Taipy provides two independent modules: Taipy GUI and Taipy Core.
In this talk, we will demonstrate how:
1. Taipy-GUI goes way beyond the capabilities of the standard graphical stack: Gradio,
Streamlit, Dash, etc.
2. Taipy Core fills a void in the standard Python back-end stack.
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.
Graph Viz: Exploring, Analyzing and Visualizing Graphs and Networks with Gephi and ChatGPT(Workshop)
AI + Human: A Powerful Partnership for Success(Women Ignite)
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.
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.
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.
Interpreting Features in Deep Networks(Tutorial)
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.
Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training(Tutorial)
Christina Qi
Christina Qi is the CEO of Databento, an on-demand market data platform. She formerly founded Domeyard LP, a hedge fund focused on high frequency trading (HFT) that traded up to $7.1 billion USD per day. Failing to earn a job offer after a Wall Street internship, Christina started Domeyard from her dorm room with $1000 in savings, about 9 years ago. Her fund was a tiny minnow amongst the tigers of the hedge fund world, but after Michael Lewis’s Flash Boys came out in 2014 and HFT firms hid from the spotlight, Domeyard accidentally found itself in the center of the ring. Over the next decade, her company’s story was featured on the front page of Forbes and Nikkei, and quoted in the Wall Street Journal, Bloomberg, CNN, NBC, and the Financial Times as a result of the controversy and fascination with HFT. By a series of accidents, Christina became a voice in her industry, contributing to the World Economic Forum’s research on AI in finance, guest lecturing at dozens of universities, and teaching Domeyard’s case study at Harvard Business School. She is grateful to be able to open up about her mistakes, and to help people turn failures into opportunities.
No amount of therapy has quashed Christina’s impostor syndrome, but she will always be proud of her non-profit volunteer work. Christina was elected as a Member of the MIT Corporation, MIT’s Board of Trustees. She is Co-Chair of the Board of Invest in Girls, bringing financial literacy education to underserved populations across the US. Christina also sits on the Board of Directors of The Financial Executives Alliance (FEA) Hedge Fund Group, drives entrepreneurship efforts at the MIT Sloan Boston Alumni Association (MIT SBAA), and served on the U.S. Non-Profit Boards Committee of 100 Women in Finance. Although “X Under X” lists are a gimmick, she’ll admit that Forbes 30 Under 30 made a positive impact on her life by giving her a community – friends who dragged her out of bed during the lowest days of her life. Christina holds a Bachelor of Science in Management Science from MIT and is a CAIA Charterholder.
When Robots Beat Humans: How ChatGPT is Changing the Financial Industry(Business Talk)
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.
Hyper-productive NLP with Hugging Face Transformers(Workshop)
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.
Towards the Next Generation of Artificial Intelligence with its Applications in Practice(Talk)
Elijah Meeks
Elijah Meeks is a co-founder and Chief Innovation Officer of Noteable, a startup focused on evolving how we analyze and communicate data. He is known for his pioneering work in the digital humanities while at Stanford, where he was the technical lead for acclaimed works like ORBIS and Kindred Britain. He was Netflix’s first Senior Data Visualization Engineer, and while at Netflix and Apple worked to develop the charting library Semiotic as well as bring cutting-edge data visualization techniques to analytical applications for stakeholders across the organization including A/B testing, conversation flows, algorithms, membership, people analytics, content, image testing and social media. He is a prolific writer, speaker and leader in the field of data visualization and the co-founder and first executive director of the Data Visualization Society.
The Future Is Notebooks(Talk)
Matteo Pirotta
Bio Coming Soon!
Exploration in Reinforcement Learning(Tutorial)
Arvind Neelakantan, PhD
Arvind Neelakantan is a Research Lead and Manager at OpenAI working on deep learning research for real-world applications. He got his PhD from UMass Amherst where he was also a Google PhD Fellow. His work has received best paper awards at NeurIPS and at Automated Knowledge Base Construction workshop.
Text and Code Embeddings(Talk)
Colleen Molloy Farrelly
Colleen M. Farrelly is a lead data scientist whose expertise spans generative AI, topological data analysis, network science, and NLP, among others. She’s recently focused her research on the geometry of generative AI models and how this impacts their performance on tasks such as bias detection, and her volunteer work includes mentoring African machine learning students. She and Dr. Yae Gaba are the authors of The Shape of Data, an overview of machine learning from a geometric perspective.
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.
Advanced Fraud Modeling & Anomaly Detection with Python & R part 1(Training)
Advanced Fraud Modeling & Anomaly Detection with Python & R part 2(Training)
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.
Machine Learning with XGBoost(Workshop)
Idiomatic Pandas(Workshop)
Thomas J. Fan
Thomas J. Fan is a Staff Software Engineer at Quansight Labs and is a maintainer for scikit-learn, an open-source machine learning library for Python. Previously, Thomas worked at Columbia University to improve interoperability between scikit-learn and AutoML systems. He is a maintainer for skorch, a neural network library that wraps PyTorch. Thomas has a Masters in Mathematics from NYU and a Masters in Physics from Stony Brook University.
Introduction to scikit-learn: Machine Learning in Python (Training)
Rebecca Vislay-Wade, PhD
Rebecca Vislay-Wade is a Principal Data Scientist at Moderna, where she leads a team of scientists developing AI applications for clinical operations, regulatory science, and pharmacovigilance. Prior to Moderna, she worked as Senior Research Data Scientist at Highmark Health. Rebecca holds a PhD in biochemistry from Harvard University and did postdoctoral work in neuroscience at the NIH and Children’s National Medical Center in Washington, DC. She currently lives in the Boston area with her family.
Data Science @ Moderna: Accelerating Regulatory Communication with Natural Language Processing(Talk)
Leonardo De Marchi
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.
Generative AI(Training)
NLP Fundamentals(Training)
Julia Lintern
Julia Lintern currently works as a Director of Data Science at Gartner. 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.
Introduction to Machine Learning(Bootcamp)
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.
Winning The Room: Creating And Delivering An Effective Data-Driven Presentation(Business Talk)
Previous Partners
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.
DIAMOND PARTNERS
INDUSTRY PARTNER
PLATINUM PARTNERS
INDUSTRY PARTNER
GOLD PARTNERS
SILVER PARTNERS
NETWORKING PARTNERS
MEDIA & COMMUNITY PARTNERS
Interested in Partnering With ODSC?
REQUEST BROCHUREEvent Venue
Boston Hynes Convention Center
900 Boylston St.
Boston, MA 02115
ODSC Newsletter
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!