Oct 30th – Nov 2nd
Research Frontiers
The Most Advanced Active Research, Summarized
Research Frontiers Track
Rapid Pace of Advancement
Data Science is a broad field and advancing at a tremendous pace. Every few months new research, models, and advances are announced. For data science practitioners, it’s essential to keep abreast of the latest advances. However, given the demands on our time this can be a daunting task.
The Most Advanced Research, Summarized
The Research Frontiers track is the first of its kind. You don’t have to parse the contents of countless papers or attend academic conferences; instead, we bring the most relevant information to you. World-class academics, researchers, and professionals summarize the latest research across focus areas, and detail what’s important.
Some of Our Confirmed Research Frontiers Speakers
Jack McCauley
Jack McCauley an Innovator in Residence at Jacobs Institute for Design Innovation at UC Berkeley, Professor at UC Berkeley, Co-Founder of Oculus, an American engineer, hardware designer, inventor, video game developer and philanthropist. Jack is best known for designing the guitars and drums for the Guitar Hero video game series, and as a co-founder and former chief engineer at Oculus VR. At Oculus, Jack designed and built the Oculus DK1 and DK2 virtual reality headsets. Oculus was acquired by Facebook for $2 Billion. McCauley holds numerous U.S. patents for inventions in software, audio effects, virtual reality, motion control, computer peripherals, and video game hardware and controllers. Jack was awarded a full scholarship to attend University of California, Berkeley where he earned a BSc., EECS in Electrical Engineering and Computer Science in 1986. Jack has authored numerous research papers in the field of artificial intelligence (AI) and mathematical modeling of AI-based systems and is currently pursuing new projects at his private R&D facility and hardware incubator in Pleasanton, California.
Alex Liu, Ph.D.
Dr. Alex Liu is the founder and Director of the RMDS Lab, a data and AI ecosystem service provider. From 2013 to 2019, Alex was one of the data science thought leaders and a distinguished data scientist at IBM where he served as a Chief Data Scientist for analytics services. Before joined IBM, Dr. Liu worked as a chief data scientist for a few companies including iSKY and Retention Science. Previously, Dr. Liu taught advanced quantitative methods to PhD candidates in the University of Southern California and the University of California at Irvine, while consulted for many well-known organizations such as the United Nations and Ingram Micro. Alex has a MS of Statistical Computing and a PhD of Sociology from Stanford University.
Completing Knowledge Discovery Fast at High Quality with AI(Talk)
Gwendolyn D. Stripling, Ph.D.
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)
Hao Zhang, PhD
Hao is currently a postdoctoral researcher at the Sky Lab, UC Berkeley, working with Prof. Ion Stoica. He is recently working on the Alpa project and the Sky project, aiming at democratizing large models like GPT-3. He is an Assistant Professor at Halıcıoğlu Data Science Institute and Department of Computer Science and Engineering (affiliate) at UC San Diego in Fall 2023.
He research is primarily focused on large-scale distributed ML in the joint context of ML and systems, concerning performance, usability, cost, and privacy. His work spans across distributed ML algorithms, large models, parallelisms, performance optimizations, system architectures, ML privacy, and AutoML, with applications in computer vision, natural language processing, and healthcare.
Dr. Petar Veličković
Petar Veličković is a Staff Research Scientist at Google DeepMind, Affiliated Lecturer at the University of Cambridge, and an Associate of Clare Hall, Cambridge. Petar holds a PhD in Computer Science from the University of Cambridge (Trinity College), obtained under the supervision of Pietro Liò. His research concerns geometric deep learning—devising neural network architectures that respect the invariances and symmetries in data (a topic I’ve co-written a proto-book about). Petar’s research has been used in substantially improving travel-time predictions in Google Maps, and guiding intuition of mathematicians towards new top-tier theorems and conjectures.
Michael Auli
Michael Auli is a principal research scientist/director at FAIR in Menlo Park, California. His work focuses on speech and NLP and he helped create projects such as wav2vec/data2vec, the widely used fairseq toolkit, the first modern feed-forward seq2seq models outperforming RNNs for NLP, and several top ranked submissions at the WMT news translation task in 2018 and 2019. Before that Michael was at Microsoft Research, where he did early work on neural machine translation and using neural language models for conversational applications. During his PhD at the University of Edinburgh he worked on natural language processing and parsing. http://michaelauli.github.io
General and Efficient Self-supervised Learning with data2vec(Talk)
Walid S. Saba
Walid Saba is a Senior Research Scientist at the Institute for Experiential AI at Northeastern University. Prior to joining the institute in 2023, he worked at two Silicon Valley startups, focusing on conversational AI. This work included high-level roles as the principal AI scientist for telecommunications company Astound and CTO of software company Klangoo, where he helped develop its state-of-the-art digital content semantic engine (Magnet).
Saba’s career to date has seen him hold various positions in both the private sector and academia. His resume includes entities such as the American Institutes for Research, AT&T Bell Labs, IBM and Cognos, while he has also spent a cumulative seven years teaching computer science at the University of Ottawa, the New Jersey Institute of Technology (NJIT), the University of Windsor (a public research university in Ontario, Canada), and the American University of Beirut (AUB).
Walid is frequent invited for interviews and as a keynote speaker on AI and NLP has published over 45 technical articles, including an award-winning paper that he presented at the German Artificial Intelligence Conference (KI-2008). Walid received his BSc and MSc in Computer Science from the University of Windsor, and a Ph.D in Computer Science from Carleton University in 1999.
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)
Patrick Hall
Patrick Hall is an assistant professor of decision sciences at the George Washington University School of Business, teaching data ethics, business analytics, and machine learning classes. He also conducts research in support of NIST’s AI risk management framework and is affiliated with leading fair lending and AI risk management advisory firms.
Patrick studied computational chemistry at the University of Illinois before graduating from the Institute for Advanced Analytics at North Carolina State University. He has been invited to speak on AI and machine learning topics at the National Academies of Science, Engineering, and Medicine, ACM SIG-KDD, and the Joint Statistical Meetings. He has been published in outlets like Information, Frontiers in AI, McKinsey.com, O’Reilly Ideas, and Thompson-Reuters Regulatory Intelligence, and his technical work has been profiled in Fortune, Wired, InfoWorld, TechCrunch, and others. Patrick is the lead author of the book Machine Learning for High-Risk Applications.
Prior to joining the GW School of Business, Patrick co-founded BNH.AI, a boutique law firm focused on AI governance and risk management. He led H2O.ai’s efforts in responsible AI, resulting in one of the world’s first commercial applications for explainability and bias mitigation in machine learning. Patrick also held global customer-facing roles and R&D roles at SAS Institute. Patrick has built machine learning software solutions and advised on matters of AI risk for Fortune 100 companies, cutting-edge startups, Big Law, and U.S. and foreign government agencies.
Adopting Language Models Requires Risk Management — This is How(Talk)
Thomas Nield
Thomas Nield is the founder of Nield Consulting Group and Yawman Flight, as well as an instructor at University of Southern California. He enjoys making technical content relatable and relevant to those unfamiliar or intimidated by it. Thomas regularly teaches classes on data analysis, machine learning, mathematical optimization, and practical artificial intelligence. At USC he teaches AI System Safety, developing systematic approaches for identifying AI-related hazards in aviation and ground vehicles. He’s authored three books, including Essential Math for Data Science (O’Reilly) and Getting Started with SQL (O’Reilly)
He is also the founder and inventor of Yawman Flight, a company developing universal handheld flight controls for flight simulation and unmanned aerial vehicles.
Introduction to Math for Data Science(Bootcamp)
ODSC WEST 2023 - Oct 30th – Nov 2nd
RegisterActive Research Focus Areas
Data science is a broad and expanding field with many areas of study. Here are some of the main areas that our presenting researchers will address:
Neural Networks
Machine Learning
Transfer Learning
Machine Vision
Natural Language Processing
Predictive Analytics
Pattern Recognition
Quantitative Finance
Speech Recognition
Time Series Analysis
Graph Theory
Network Analysis
Data Visualization
Anomaly Detection
You Will Meet
Experienced data scientists
Software engineers and architects
Business professionals interested in data science advancements
Experts from other domains looking to leverage data science
Researchers from academia and industry
Industry professionals
Technologists interested in new data science applications
Industry experts looking to access the impact of data science
Why Attend?
Hear from world-class researchers and academics about the top areas of active research
Take time out of your busy schedule to accelerate your knowledge of the latest advances in data science
Be the first amongst your peers to grasp changes that will affect the field over the next few years
Take advantage of another 120 talks, tutorials, and workshops at ODSC West
Learn directly from top researchers what works and what doesn’t
Connect and network with academics, research, and fellow professionals
Meet with peers and professionals looking to learn, connect, and collaborate
Get access to other focus area content, including ML / DL, Data Visualization, Quant Finance, and Open Data Science
ODSC WEST 2023 - Oct 30th – Nov 2nd
RegisterODSC 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!