ODSC EAST 2024 / IN-PERSON & VIRTUAL
Boston Hynes Convention Center, MA
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
Build AI Skills in 2024
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
Why Attend the Leading AI Conference
AI EXPO AND DEMO HALL
Meet AI experts from some of the leading AI companies and startups in the industry at our AI Expo and Demo Hall. With multiple live demos get a better understanding of Build Vs Buy decisions and learn about the latest advancements in AI for enterprises and discover how to build AI better
HANDS-ON TRAINING
Top instructors help you acquire job-ready skills and stay current in LLMs, ML, DL, NLP, and more at ODSC East. With dozens of sessions to choose from. Our immersive, expert-led training also certifies AI practitioners at all levels.
CHOOSE YOUR PASS
Pick the pass that suits your schedule and build job-ready skills. We offer two and three-day passes that will give you the breadth and depth of content to succeed, from immersive training to inspirational talks. In addition, we have business and virtual passes.
LEADING EXPERT SPEAKERS
ODSC is renowned for bringing together the brightest minds and top practitioners in the field. Explore cutting-edge insights, innovations, and strategies shared by leading expert speakers. Don’t miss this opportunity to learn from the best in AI!
NETWORKING
Experience numerous in-person and virtual networking opportunities, or challenge yourself to connect with as many industry professionals as possible during our Networking events. Seize this opportunity to grow your professional network to forge invaluable connections within the growing field of AI!
Why Attend the Leading AI Conference
TRAINING
Our Top instructors help you acquire job-ready skills and stay current in LLMs, ML, DL, NLP, and more at ODSC West. With dozens of sessions to choose from. Our immersive, expert-led training also offers certification for AI practitioners at all levels.
AI EXPO HALL
Meet AI experts from some of the leading AI companies and startups in the industry at our AI Expo and Demo Hall. With multiple live demos get a better understanding of Build Vs Buy decisions and learn about the latest advancements in AI for enterprises and discover how to build AI bette
NETWORKING
Experience numerous in-person and virtual networking opportunities, or challenge yourself to connect with as many industry professionals as possible during our Networking events. Seize this opportunity to grow your professional network to forge invaluable connections within the growing filed of AI!
LEADING EXPERT SPEAKERS
ODSC is renowned for bringing together the brightest minds and top practitioners in the field. Explore cutting-edge insights, innovations, and strategies shared by leading expert speakers. Don’t miss this opportunity to learn from the best in AI!
CHOOSE YOUR PASS
Pick the pass that suits your schedule and build job-ready skills. We offer 2 and 3-day (4 with Bootcamp) passes that will give you the breadth and depth of content to succeed, from immersive training to inspirational talks. In addition, we have business and virtual passes.
Conference Tracks
Registration
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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.
ODSC East 2024 Featured Speakers
Laurence Moroney
Laurence Moroney leads AI Advocacy at Google, working with the Google AI Research and product development teams. He’s the best-selling author of ‘AI and Machine Learning for Coders,’ as well as the instructor on the Fundamentals of TinyML course at HarvardX, and the popular TensorFlow specializations with deeplearning.ai and Coursera. He’s passionate about empowering software developers to succeed in Machine Learning, democratizing AI as a result. Laurence is based on Washington State in the USA.
Valentina Alto
Valentina is a Data Science MSc graduate and Cloud Specialist at Microsoft, focusing on Analytics and AI workloads within the manufacturing and pharmaceutical industry since 2022. She has been working on customers’ digital transformations, designing cloud architecture and modern data platforms, including IoT, real-time analytics, Machine Learning, and Generative AI. She is also a tech author, contributing articles on machine learning, AI, and statistics, and recently published a book on Generative AI and Large Language Models.
In her free time, she loves hiking and climbing around the beautiful Italian mountains, running, and enjoying a good book with a cup of coffee.
The AI Paradigm Shift: Under the Hood of a Large Language Models(Workshop)
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.
Amy Hodler
Amy Hodler is an evangelist for graph analytics and responsible AI. She’s the co-author of O’Reilly books on Graph Algorithms and Knowledge Graphs as well as a contributor to the Routledge book, Massive Graph Analytics and Bloomsbury book, AI on Trial. Amy has decades of experience in emerging tech at companies such as Microsoft, Hewlett-Packard (HP), Hitachi IoT, Neo4j, Cray, and RelationalAI. Amy is the founder of GraphGeeks.org promoting connections everywhere.
Allen Downey, PhD
Allen Downey is a curriculum designer at Brilliant.org and professor emeritus at Olin College. He is the author of several books — including Think Python, Think Bayes, and Probably Overthinking It — and a blog about data science and Bayesian statistics. He received a Ph.D. in computer science from the University of California, Berkeley; and Bachelor’s and Masters degrees from MIT.
Andras Zsom, PhD
Andras Zsom is an Assistant Professor of the Practice and Director of Graduate Studies at the Data Science Initiative at Brown University, Providence, RI. He is teaching two mandatory courses in the data science master’s program, and helps the students navigate through their studies and curriculum. He also supervises interns on various research projects related to missing data, interpretability, and developing machine learning pipelines.
Dr. Andre Franca
Andre is the co-founder and CTO of connectedFlow, developing the next generation of AI co-pilots to help e-commerce/D2C operators make better decisions, without the pain of data analytics. He’s previously the VP of R&D at causaLens, where he was applying cutting edge Causal AI research to solve business-critical problems in global enterprises. Prior to that he was an executive director at Goldman Sachs, developing and validating quantitative models used by the business. Andre received his PhD in theoretical physics from the University of Munich, where he studied the interplay between quantum mechanics and general relativity in black-holes.
Causal AI: from Data to Action(Workshop)
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.
Wes Madrigal
Wes is a machine learning expert with over a decade of experience delivering business value with AI. Wes’s experience spans multiple industries, but always with an MLOps focus. His recent areas of focus and interest are graphs, distributed computing, and scalable feature engineering pipelines.
Using Graphs for Large Feature Engineering Pipelines(Workshop)
Sinan Ozdemir
Sinan Ozdemir is a mathematician, data scientist, NLP expert, lecturer, and accomplished author. He is currently applying my extensive knowledge and experience in AI and Large Language Models (LLMs) as the founder and CTO of LoopGenius, transforming the way entrepreneurs and startups market their products and services.
Simultaneously, he is providing advisory services in AI and LLMs to Tola Capital, an innovative investment firm. He has also worked as an AI author for Addison Wesley and Pearson, crafting comprehensive resources that help professionals navigate the complex field of AI and LLMs.
Previously, he served as the Director of Data Science at Directly, where my work significantly influenced their strategic direction. As an official member of the Forbes Technology Council from 2017 to 2021, he shared his insights on AI, machine learning, NLP, and emerging technologies-related business processes.
He holds a B.A. and an M.A. in Pure Mathematics (Algebraic Geometry) from The Johns Hopkins University, and he is an alumnus of the Y Combinator program. Sinan actively contribute to society through various volunteering activities.
Sinan’s skill set is strongly endorsed by professionals from various sectors and includes data analysis, Python, statistics, AI, NLP, theoretical mathematics, data science, function analysis, data mining, algorithm development, machine learning, game-theoretic modeling, and various programming languages.
Aligning Open-source LLMs Using Reinforcement Learning from Feedback(Workshop)
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.
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.
Gwendolyn D. Stripling, PhD
Gwendolyn Stripling, Ph.D., is an Artificial Intelligence and Machine Learning Content Developer at Google Cloud. Stripling is author of the widely popular YouTube video, “Introduction to Generative AI” and of the O’Reilly Media book “Low-Code AI: A Practical Project Driven Approach to Machine Learning”. They are also the author of the LinkedIn Learning video “Introduction to Neural Networks”. Stripling is an Adjunct Professor and member of Golden Gate University’s Masters in Business Analytics Advisory Board. Stripling enjoys speaking on AI/ML, having presented at Dominican University of California’s Barowsky School of Business Analytics, Golden Gate University’s Ageno School of Business Analytics, and numerous Tech conferences.
No-Code and Low-Code AI: A Practical Project Driven Approach to ML(Tutorial)
Amit Sangani
Amit Sangani is the Director of Partner Engineering leading the Applied AI Platforms team at Meta. Amit has been with Meta for 8+ years and manages developer-facing engineering teams working on Gen AI platforms such as Llama 2 and PyTorch. Amit’s mission is to democratize AI and increase the adoption of these platforms by making it easier for developers to integrate them into their products and spur innovation and increased productivity.
Building Using Llama 2(Workshop)
Michael Levin
Michael Levin is the Vannevar Bush Distinguished Professor of Biology at Tufts University, an associate faculty at Harvard’s Wyss Institute, and the director of the Allen Discovery Center at Tufts. He has published over 400 peer-reviewed publications across developmental biology, computer science, and philosophy of mind. His group works to understand information processing and problem-solving across scales, in a range of naturally evolved, synthetically engineered, and hybrid living systems. Dr. Levin’s work spans from fundamental conceptual frameworks to applications in birth defects, regeneration, and cancer.
Michael Levin is the Vannevar Bush Distinguished Professor of Biology at Tufts University, and associate faculty at Harvard’s Wyss Institute. He serves as the director of the Allen Discovery Center at Tufts and the co-director of the Institute for Computationally Designed Organisms at Tufts/UVM. He has published over 400 peer-reviewed publications across developmental biology, computer science, and philosophy of mind. Dr. Levin received dual B.S. degrees in computer science and biology, followed by a Ph.D. from Harvard with Clifford Tabin. His graduate work on the molecular basis of left-right asymmetry (Cell 1995) was chosen by the journal Nature as a “Milestone in Developmental Biology in the last century”. He did post-doctoral training at Harvard School of Medicine in cell biology, and started his independent lab in 2000, developing the first molecular tools to read and write bioelectric prepatterns in non-neural tissue. His group at Tufts works to understand information processing and problem-solving across scales, in a range of naturally evolved, synthetically engineered, and hybrid living systems. The Levin lab has pioneered approaches to organ regeneration, cancer reprogramming, non-genetic modification of the bodyplan, and the engineering of novel living proto-organisms. Using tools from behavioral and computer science, Dr. Levin seeks to understand the collective intelligence of cells and harness their problem-solving capacities for applications in birth defects, regeneration, cancer, and synthetic bioengineering.
Noah Giansiracusa, PhD
Noah Giansiracusa (PhD in math from Brown University) is a tenured associate professor of mathematics and data science at Bentley University, a business school near Boston. His research interests range from algebraic geometry to machine learning to empirical legal studies. After publishing the book How Algorithms Create and Prevent Fake News in July 2021, Noah has gotten more involved in public writing and policy discussions concerning data-driven algorithms and their role in society. He’s written op-eds for Barron’s, Boston Globe, Wired, Slate, and Fast Company and is currently working on a second book, Robin Hood Math: How to Fight Back When the World Treats You Like a Number, with a Foreword by Nobel Prize-winning economist Paul Romer.
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.
Shelbee Eigenbrode
Shelbee Eigenbrode is a Principal Machine Learning Specialist Solutions Architect at Amazon Web Services (AWS). She’s been in technology for 24 years spanning multiple roles, industries and technologies. With over 35 patents granted across various technology domains, she has a passion for continuous innovation and using data to drive business outcomes. She’s a published author as well as co-creator/instructor for ‘Practice Data Science on the AWS Cloud Specialization’ and ‘Generative AI with Large Language Models’ on Coursera. Shelbee is based in Denver, CO and is also the Co-Director of the Denver, Colorado chapter of Women in Big Data.
Enabling Complex Reasoning and Action with ReAct, LLMs, and LangChain(Workshop)
Adam Breindel
Adam Breindel is a member of the Anyscale training team and he consults and teaches on large-scale data engineering and AI/machine learning. He has served as technical reviewer for numerous O’Reilly titles covering Ray, Apache Spark, and other topics. Adam’s 20 years of engineering experience include numerous startups and large enterprises with projects ranging from AI/ML systems and cluster management to web, mobile, and IoT apps. He holds a BA (Mathematics) from University of Chicago and a MA (Classics) from Brown University. Adam’s interests include hiking, literature, and complex adaptive systems.
Serg Masis
Serg Masís has been at the confluence of the internet, application development, and analytics for the last two decades. He’s an Agronomic Data Scientist at Syngenta, a leading agribusiness company with a mission to improve global food security. Before that role, he co-founded a search engine startup, incubated by Harvard Innovation Labs, that combined the power of cloud computing and machine learning with principles in decision-making science to expose users to new places and events efficiently. Whether concerning leisure activities, plant diseases, or customer lifetime value, Serg is passionate about providing the often-missing link between data and decision-making. He wrote the bestselling book “Interpretable Machine Learning with Python” and is currently working on a new book titled “DIY AI” with do-it-yourself projects for AI hobbyists and practitioners alike.
Andrew Lamb
Andrew Lamb is the chair of the Apache Arrow Program Management Committee (PMC) and a Staff Software Engineer at InfluxData. He works on InfluxDB IOx, a time series database engine written in Rust, that heavily uses the Apache Arrow ecosystem. He actively contributes to many open source software projects including the Apache Arrow Rust implementation and the Apache Arrow DataFusion query engine.
Tutorial: Introduction to Apache Arrow and Apache Parquet, using Python and Pyarrow(Workshop)
Jeffrey Yau, PhD
Jeffrey Yau is currently Chief Data & A.I. Officer at Fanatics Collectibles. Most recently, he served as Global Head of Data Science, Analytics & Engineering at Amazon Music where he oversaw multiple teams who developed both insights-packed analytics and end-to-end statistical and machine learning systems. Prior to Amazon, Jeffrey worked at WalmartLabs as the VP of Data Science & Engineering where he led the team responsible for powering Walmart store mobile apps and the entire store finance system. Further, his team created end-to-end machine learning systems for key business initiatives and had a multi-billion dollar impact annually on Walmart U.S.
Over the years, he has held various senior level positions in quantitative finance at global investment management firm AllianceBernstein, consulting firm Data Science at Silicon Valley Data Science, multinational financial services company Charles Schwab Corporation, and the world’s leading professional services firm KPMG. He began his career as a tenure-track Assistant Professor of Economics at Virginia Tech, and he was an adjunct professor at UC Berkeley, Cornell, and NYU, teaching machine learning and advanced statistical modeling for finance and business.
Michelle Yi
Michelle is a technology leader that specializes in machine learning and cloud computing. She has 15 years of experience in the technology industry, contributed to the original IBM Watson showcased on Jeopardy, and enjoys building and leading teams that develop and deploy AI solutions to solve real-world problems. Michelle is passionate about diversity, STEM education/careers for our minority communities, and serves both on the board of Women in Data and as an avid volunteer for Girls Who Code.
Dr. Mustafa Hajij
Dr. Hajij is an Assistant Professor specializing in data science at the University of San Francisco’s Master of Science in Data Science Program. With over 8 years of research and industrial experience, he has delved into graph neural networks, topological data analysis, intelligent transportation, and topological deep learning. His expertise extends to industrial AI applications, with a focus on topological deep learning, geometric data processing, time-varying data, and predictive modeling. He co-founded AltumX, a startup utilizing deep learning for intelligent road network systems, and actively participates in AI-related workshops and conferences. He published more than 70 publications in journal and conference papers, as well as patents. Hajij served as the main organizer for MICCAI TDA workshops in 2021 and 2022. He made contributions to the tech industry, spearheading the development of innovative software solutions for both KLA Corporation and AltumX Inc.
Topological Deep Learning: Going Beyond Graph Data(Workshop)
Benjamin Batorsky, PhD
Ben is a Senior Data Scientist at the Institute for Experiential AI at Northeastern University. He obtained his Masters in Public Health (MPH) from Johns Hopkins and his PhD in Policy Analysis from the Pardee RAND Graduate School. Since 2014, he has been working in data science for government, academia and the private sector. His major focus has been on Natural Language Processing (NLP) technology and applications. Throughout his career, he has pursued opportunities to contribute to the larger data science community. He has presented his work at conferences, published articles, taught courses in data science and NLP, and is co-organizer of the Boston chapter of PyData. He also contributes to volunteer projects applying data science tools for public good.
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Participate at ODSC East 2024
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.
SAVE THE DATE!
ODSC EAST Conference April 23rd – April 25th
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.
INDUSTRY PARTNER
NETWORKING PARTNERS
MEDIA & COMMUNITY PARTNERS
Event Venue
Boston Hynes Convention Center
900 Boylston St.
Boston, MA 02115
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