Ai X Finance
Ai X Marketing
Ai X Healthcare
Ai X Energy
Ai X Biotech & Pharma
Ai X Retail
Ai X Climate
Ai X Machines
Ai X Cyber & Fraud
Ai X Manufacturing
Applying Artificial Intelligence Across the Enterprise
Forming and Managing Effective AI Teams
Understanding Deep Learning and Machine Learning for Business
Understanding AI Ethics, Governance, and Bias in Models
Artificial Intelligence for Good
Explainable AI and Transparency in AI Workflows and Models
Artificial Intelligence Governance, Compliance, and Regulation
Leveraging AI for Online Marketing, Sales, and Advertising
Cybersecurity and Threat Detection with AI and Machine Learning
And many more topics over 4 days.
Hear from top expert speakers and prepare your company for the next wave of innovation and growth.
As Chief Decision Scientist at Google Cloud, Cassie Kozyrkov advises leadership teams on decision process, AI strategy, and building data-driven organizations. She is the innovator behind bringing the practice of Decision Intelligence to Google, personally training over 15,000 Googlers. Prior to joining Google, Cassie worked as a data scientist and consultant. She holds degrees in mathematical statistics, economics, psychology, and neuroscience.
Making Data Useful(Track Keynote)
Abhinav Joshi is a Director, Product Marketing at Red Hat. He and his team are focused on cloud-native workloads on Red Hat OpenShift, including AI/ML, data analytics, databases, etc. Abhinav has over 20 years of industry experience in Hybrid Cloud, AI/ML, Data Analytics, Digital Workspace, and Software Defined Data Center.. Throughout his career, Abhinav has held strategic roles in Product Management, Product Marketing, Sales, and Consulting Services at Red Hat, VMware, Cisco, NetApp, etc. He holds an MS in Systems Engineering from the University of Maryland College Park, Strategic Management Graduate Certificate from Harvard University, and a B.Tech in Chemical Engineering from Nagpur University, India.
Accelerate AI/ML Deployments with Enterprise-grade MLOps(Track Keynote)
Matt leads OEM enablement for partner software-based solutions at NVIDIA. Most of Matt’s background is in open source infrastructure, holding roles in technical sales, product management, and business development. Prior to that, Matt worked as a solution architect designing one of the first enterprise grade multi-tenant container-as-a-service private clouds. He holds a bachelor’s science degree in computer science and applied computational physics from Hampden-Sydney College.
Accelerate AI/ML Deployments with Enterprise-grade MLOps(Track Keynote)
Since joining Syracuse University in 2014, Jeff has focused on how to effectively manage and coordinate data science projects within and across teams. Via his research and consulting, Jeff has become an expert in this field, having worked across a range of organizations and published 30+ peer-reviewed academic papers that (1) explore the challenges in executing data science projects, and (2) evaluate potential frameworks via experiments and real-world case studies.
Prior to joining Syracuse University and consulting on data science efforts, Jeff worked at JPMorgan Chase, where he reported to the firm’s Global Chief Information Officer and drove technology innovation across the organization, while also having other leadership roles within the bank, such as leading the IT effort for credit risk analytics within the consumer bank.
Managing Data Science Projects via an Agile Framework(Business Talk)
Dr Felicity Bell, PhD, is a Research Fellow for the Future of Law and Innovation in the Profession (FLIP) Research Stream, funded by the Law Society of New South Wales and based at the University of New South Wales, Sydney, Australia. FLIP provides research and thought leadership on the core concerns of the legal profession into the future. Felicity’s research looks at law and technology, and how lawyers’ regulation, professionalism and ethics interact with innovation in law. She has published widely and recently co-authored the book Artificial Intelligence and the Legal Profession (Hart, 2020).
What do Lawyers Need (and want) from Legaltech?(Business Talk)
Sadid Hasan is a Senior Director for AI at CVS Health leading the team responsible for AI-enabled clinical care plan initiatives in Aetna. His recent work involves solving problems related to clinical information extraction, paraphrase generation, natural language inference, and clinical question answering using Deep Learning. Sadid has over 60 peer-reviewed publications in the top NLP/Machine Learning venues, where he also regularly serves as a program committee member/area chair including ACL, IJCAI, EMNLP, NeurIPS, ICML, COLING, NAACL, AMIA, MLHC, MEDINFO, ICLR, ClinicalNLP, TKDE, JAIR etc.
AI for Clinical Care Planning and Decision Support(Business Talk)
Masheika Allgood is an AI Ethicist and the founder of AllAI Consulting, LLC, a platform for providing AI education across various industries to people with non-tech and non-AI backgrounds. Masheika is a Member of the Board of the Foundation for Best Practices in Machine Learning and an active member of the IEEE where she is involved in writing AI ethical standards as a Member of the IEEE Global Ethics Education Committee, and Participant in Standard 3119 – the Standard for the Procurement of Artificial Intelligence and Automated Decision Systems. Masheika’s first foray into AI Ethics was as the founder and lead of NVIDIA’s first AI Ethics Workgroup. She is passionate about the need for AI literacy, the role of the every day activist in ensuring ethical AI, and developing AI educational resources that are accessible for all. Masheika holds an LL.M in Litigation and Dispute Resolution from the George Washington University School of Law, a Juris Doctorate from Florida State University, and a Masters in International Business from Florida International University.
Can We Let AI be Great? Practical Considerations in Designing Effective and Ethical AI Products.(Business Talk)
While a PhD student in energy econometrics at UC Berkeley, Gavin McCormick invented “Automated Emissions Reduction”: software that instantly reduces pollution from smart devices such as electric vehicles and smart thermostats. Today he is Executive Director of WattTime, a nonprofit that helps Fortune 500 companies and governments use this technology to lower their carbon footprint at scale. He is also a cofounder of Climate TRACE: a coalition of nonprofits, tech companies, and universities using satellites and AI to monitor every source of greenhouse gas emissions source on Earth.
Timing IoT Devices to Slash Carbon Emissions at Scale(Business Talk)
A seasoned professional with over 20 years of leadership experience in language technology, NLP, ML and AI data generation and annotation, Olga is the VP, AI Innovation at Welocalize. She is passionate about growing business through driving change and innovation, and an expert in building things from scratch and bringing them to measurable success. Olga has experience on both the buyer and the supplier side, giving her unique perspective around establishing strategic buyer/supplier alliances and designing cost-effective Global Content Lifecycle Programs. She has built and managed global production, engineering and development teams of up to 300 members specializing in NLP and broader ML and AI.
Creating Data to Enable Multilingual AI: What Can Go Wrong and Ways to Mitigate It (Business Talk)
Keith McCormick serves as CloudFactory’s Chief Data Science Advisor. He’s also an author, LinkedIn Learning contributor, university instructor, and conference speaker. Keith has been building predictive analytics models since the late 90s. More recently his focus has shifted to helping organizations build and manage their data science teams.
What Analytics Leaders need to know about EXplainable AI (XAI)(Talk)
Tony Kreager is Senior Vice President of Data Engineering & Data Science at FedEx Dataworks—an organization within FedEx Services focused on harnessing the power of the rich FedEx data ecosystem to revolutionize global commerce and transform the digital and physical experiences of customers. In this role, Tony leads a multidisciplinary team responsible for building and leveraging large-scale cloud operations, complex data platforms, and advanced AI to create differentiated insights that help optimize the FedEx business and create value for customers. Since joining FedEx in 2008, Tony has played a key role in digital transformation efforts across the enterprise, gaining experience in product management, design thinking, big data platform engineering, Data and Decision Science, and leadership excellence. Prior to his time in FedEx Dataworks, Tony served as a director of IT, leading the strategy and delivery for FedEx’s online and native mobile customer experience, including fedex.com and customer-facing mobile applications.
Dr. Arle Lommel is a senior analyst with independent market research firm CSA Research. He is a recognized expert in translation quality processes and interoperability standards. Arle’s research focuses on translation technology and the intersection of language and artificial intelligence as well as the value of language in the economy. Born in Alaska, he holds a PhD from Indiana University. Prior to joining CSA Research he worked at the German Research Center for Artificial Intelligence (DFKI) in its Berlin-based language technology lab. In addition to English he speaks fluent Hungarian and passable German, along with bits and pieces of other languages.
How Can We Make Machine Translation Responsive and Responsible?(Business Talk)
A modern polymath, John holds advanced degrees in mechanical engineering, kinesiology and data science, with a focus on solving novel and ambiguous problems. As a senior applied data scientist at Amazon, John worked closely with engineering to create machine learning models to arbitrate chatbot skills, entity resolution, search, and personalization.
As a principal data scientist for Oracle Cloud Infrastructure, he is now defining tooling for data science at scale. John frequently gives talks on best practices and reproducible research. To that end, he has developed an approach to improve validation and reliability by using data unit tests and has pioneered Data Science Design Thinking. He also coordinates SoCal RUG, the largest R meetup group in Southern California.
Tired of Cleaning your Data? Have Confidence in Data with Feature Types(Workshop)
As Max progresses through his Master’s Program, he is particularly interested in intelligent digital accessibility design, along with the ethical analysis of existing predictive models. His passion for creating quality user-centered tools drives him to understand as much as he can about end users while leveraging what data can reveal.
Z by HP Panel Discussion on the Diverse Role of Data Science in Education(Talk)
Dan Chaney is the VP, Enterprise AI / Data Science Solutions, for Future Tech Enterprise, Inc., an award-winning global IT solutions provider. He oversees all sales, marketing, and technical activities focused on Future Tech’s comprehensive range of AI and data science workstation solutions. Prior to joining Future Tech, Dan spent 20 years at Northrop Grumman, most recently serving as the company’s Enterprise Director of IT Solution Architecture & Engineering. Dan earned his bachelor’s and master’s degrees in communication and computer science from the University of Kentucky. Dan is a Certified Information Systems Security Professional (CISSP) and adjunct instructor for the University of Louisville’s cybersecurity workforce program sponsored by the National Centers of Academic Excellence in Cybersecurity.
Z by HP Panel Discussion on the Diverse Role of Data Science in Education(Talk)
New speakers will be added soon
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Want to keep up with the latest AI developments, trends, and insights? Dealing with the build or buy dilemma to grow your business? Seeking to interact with data-obsessed peers and build your network?
Look no further: The ODSC AI Expo & Demo Hall is the right destination for you
Hear from top expert speakers and prepare your company for the next wave of innovation and growth. Here is a sample of our incredibly insightful session topics from 2022:
Building a Smarter Artificial Intelligence Strategy for the Enterprise
Accelerating Business Innovation with Deep Learning
Leading Data Science Teams: A Framework to Help Guide Data Science Project Managers
From Cognitive Computing to Artificial Intelligence, the Next 10 Years
Democratizing Artificial Intelligence in a Business Context
Accelerating AI Development with Deep Learning and Transfer Learning
Recent Advances in Machine Learning with Applications to Internet of Things (IoT)
Building and Managing World Class Data Science Teams
Data Ethnography: Understanding Bias in Machine Learning Models
How to Run your Business with Data Science & Machine Learning
.
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Virtual conference experience includes networking lounge area, speaker auditorium, expo halls, and prizes
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Multiple focus areas including deep learning, machine learning, NLP, research frontiers, AI X for business, and more
Sessions you missed can be viewed on demand at your leisure
Engage virtually with fellow attendees, speakers, and Expo partners
Participate in Q&A sessions with your speaker over live chat
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(Training only) Access training and workshops prerequisites, notebooks, and other materials prior to training session starting
(Training only) Access hands-on training and workshops with instructor-led code labs and notebooks.
Hear from top industry executives using data science to grow their business
Attend talks, panels, and group discussions to get you up to speed
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Innovators such as: Startup-ups, Investors, VCs, Entrepreneurs, Evangelists & Decision-makers, and Strategy Executives.
ODSC events attract some of world’s most influential and market-shaping publications across trade and industry publications and blogs.
As AI and data science transform industry and touch every aspect of our lives, more people need to be informed of its impact. Come hear and meet the thought leaders, core contributors, and innovators who are driving this new age of disruption.
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.
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