ODSC West 2021

The Leading Data Science Conference RETURNS

San Francisco, Nov 15th – 18th, 2021 

 

You’re In Good Company

The ODSC West Conference 2021 is one of the largest and ONLY applied data science training conferences in the world. Our instructors include some of the core contributors of many open source tools, libraries, and languages. Attend ODSC West 2021 and learn the latest AI & data science topics, tools, and languages from some of the best and brightest minds in the field..

Focus Areas

  • Mini-Bootcamp

  • Deep Learning

  • Machine Learning

  • Predictive Analytics

  • AI for Engineers

  • Natural Language Processing

  • Data Visualization

  • Data Wrangling

  • AI Research

  • Data Science at Scale

  • Data Science for Good

  • Data Science Management

  • Data Science Workflows

  • AI Business Summit

Training Topics

  • Recommendation Systems

  • Transfer Learning

  • Machine Vision

  • Autonomous Machines

  • Conversational AI

  • Data Science Research

  • Artificial Intelligence

  • Speech Recognition

  • Unsupervised Learning

  • Image Classification

  • Self-driving Vehicles

  • Machine Translation

  • 200+ Speakers over 4 days

Open Source Tools

  • Tensorflow, PyTorch, MXNet, Caffe 2, Chainer, CNTK

  • Python, Jupyter Notebooks, XGBoost

  • R programming, Julia, Scala, Stan,

  • Apache Spark, MLlib, Streaming

  • Scikit-learn, Theano, Shogun, Pylearn2

  • Azure ML, Amazon ML,H20.ai, Cloud ML

  • Kubeflow, Kubernetes, Seldon, Airflow,

  • Neo4J, D3.js, R-Shiny

  • Hadoop, Apache Storm, Apache Flink, Kafka, Druid

  • SAS Viya

Participate at ODSC West 2021

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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.

ODSC West 2020 Keynotes

Suchi Saria, PhD
Suchi Saria, PhD

Director of the Machine Learning and Healthcare Lab, John C. Malone Endowed Chair, Founder of Bayesian Health, MIT Technology Review’s 35 Innovators Under 35, and a World Economic Forum Young Global Leader

Johns Hopkins University

Jeannette M. Wing, PhD
Jeannette M. Wing, PhD

Avanessians Director of the Data Science Institute, Professor of Computer Science Columbia University, Former Corporate Vice President Microsoft, Former Assistant Director, National Science Foundation

Columbia University

Ion Stoica, PhD
Ion Stoica, PhD

Professor of Computer Science, Head of RISELab. Co-founder of Anyscale, Databricks, and Conviva Networks, ACM Fellow, SIGOPS Hall of Fame Award (2015), SIGCOMM Test of Time Award (2011)

UC Berkeley

Raluca Ada Popa, PhD
Raluca Ada Popa, PhD

Cybersecurity & Applied Cryptography Professor, MIT Technology Review's 35 Under 35, Recipient of Intel Early Career Faculty Honor award, George M. Sprowls Award for best MIT CS doctoral thesis, Co-founder of PreVeil

UC Berkeley

Zoubin Ghahramani, PhD
Zoubin Ghahramani, PhD

Chief Scientist, Founding Director of the AlanTuring Institute, Prof. of Information Engineering & Deputy Director of the Leverhulme Centre for the Future of Intelligence, Fellow of St John's College Cambridge and of the Royal Society

Uber | The University of Cambridge

Azalia Mirhoseini, PhD
Azalia Mirhoseini, PhD

Senior Research Scientist at Google Brain. Advisor at Cmorq. Co-founder Machine Learning for Systems Moonshot at Brain focusing on Deep RL. MIT Technology Review 35 Under 35 Award

Google Brain

Marinela Profi
Marinela Profi

Global Strategist for AI, Global Ambassador for the Women Tech Network, Author of “Mastering Model Lifecycle Orchestration: An interactive guide”

SAS

John Montgomery
John Montgomery

Corporate Vice President, Visual Studio, Microsoft Azure AI Lead, Former Chief Information Office at Imagine Publishing, Author at Visual Studio

Microsoft

Ben Taylor,PhD
Ben Taylor,PhD

Chief AI Evangelist, Deep Learning & HPC Expert, Co-founder & Chief Scientist at Zeff.ai, Former Chief Scientist at HireVue, ProductCraft Contributor

DataRobot

ODSC West 2020 Featured Speakers

Professor, Computer ScienceStanford University, Stanford AI Labs

Gill Bejerano, PhD

Gill Bejerano is an Associate Professor of Developmental Biology and Computer Science at Stanford University, and a member of the Stanford Artificial Intelligence (AI) Laboratory and Bio-X program. Mr. Bejerano is a pioneer of Human Genome research. He is the discoverer of “Ultraconserved Elements”, human genomic regions that defy understanding of molecular evolution. He has also done influential work in applying Markovian models to biosequence analysis, and in showing that co-option of junk DNA into functional roles is an under-appreciated force shaping the evolution of the Human Genome. He serves Member of the Technical Advisory Board of Numenta, Inc. He holds a triple BSc in Mathematics, Physics and Computer Science (summa cum laude) and a PhD in Computer Science (Machine Learning applications in Bioinformatics) from the Hebrew University of Jerusalem.

DirectorIBM Research

Lisa Amini, PhD

Dr. Lisa Amini is the Director of IBM Research Cambridge, which is also home to the MIT-IBM Watson AI Lab, and of IBM’s AI Horizons Network. Lisa was previously Director of Knowledge & Reasoning Research in the Cognitive Computing group at IBM’s TJ Watson Research Center in New York, and she is also an IBM Distinguished Engineer. Lisa was the founding Director of IBM Research Ireland, and the first woman Lab Director for an IBM Research Global (i.e., non-US) Lab (2010-2013). In this role she developed the strategy and led researchers in advancing science and technology for intelligent urban and environmental systems (Smarter Cities), with a focus on creating analytics, optimizations, and systems for sustainable energy, constrained resources (e.g., urban water management), transportation, and the linked open data systems that assimilate and share data and models for these domains. She earned her PhD degree in Computer Science from Columbia University.

Advances and Frontiers in Auto AI & Machine Learning(Track Keynote)

Senior Principal ResearcherMicrosoft Research

Jenn Wortman Vaughan, PhD

Jenn Wortman Vaughan is a Senior Principal Researcher at Microsoft Research, New York City. Her research background is in machine learning and algorithmic economics. She is especially interested in the interaction between people and AI, and has often studied this interaction in the context of prediction markets and other crowdsourcing systems. In recent years, she has turned her attention to fair and interpretable machine learning as part of MSR’s FATE group. Jenn came to MSR in 2012 from UCLA, where she was an assistant professor in the computer science department. She completed her Ph.D. at the University of Pennsylvania in 2009 and subsequently spent a year as a Computing Innovation Fellow at Harvard. She is the recipient of Penn’s 2009 Rubinoff dissertation award for innovative applications of computer technology, a National Science Foundation CAREER award, a Presidential Early Career Award for Scientists and Engineers (PECASE), and a handful of best paper awards. In her “spare” time, Jenn is involved in a variety of efforts to provide support for women in computer science; most notably, she co-founded the Annual Workshop for Women in Machine Learning, which has been held each year since 2006.

Intelligibility Throughout the Machine Learning Life Cycle(Talk)

Creator of scikit-learn, Brain Imaging ResearchINRIA

Gaël Varoquaux, PhD

Gaël Varoquaux is an Inria faculty researcher working on data science and brain imaging. He has a joint position at Inria (French Computer Science National research) and in the Neurospin brain research institute. His research focuses on using data and machine learning for scientific inference, applying it to brain-imaging data to understand cognition, as well as developing tools that make it easier for non-specialists to use machine learning. Years before the NSA, he was hoping to make bleeding-edge data processing available across new fields, and he has been working on a mastermind plan building easy-to-use open-source software in Python. He is a core developer of scikit-learn, joblib, Mayavi and nilearn, a nominated member of the PSF, and often teaches scientific computing with Python using the scipy lecture notes.

The Life of Scikit-learn: from Tech to People(Track Keynote)

Professor, Co-founder, InvestorUC Berkeley, DeepScale

Kurt Keutzer, PhD

Kurt received his Ph.D. degree in Computer Science from Indiana University in 1984 and then joined the research division of AT&T Bell Laboratories. In 1991 he joined Synopsys, Inc. where he ultimately became Chief Technical Officer and Senior Vice-President of Research. In 1998 Kurt became Professor of Electrical Engineering and Computer Science at the University of California at Berkeley. Kurt’s research now focuses on systems issues associated with the application of Deep Learning to computer vision, speech recognition, natural language processing, and finance.

Kurt has published six books, over 250 refereed articles, and is among the most highly cited authors in Hardware and Design Automation. Kurt was elected a Fellow of the IEEE in 1996. At the 50th Design Automation Conference Kurt received a number of awards reflecting achievements over the 50 year history of the conference. These included “Top Ten Cited Author” and “Top Ten Cited Paper.” He was also recognized as among one of only three people to have received four Best Paper Awards in the history of the conference. Kurt’s research on Deep Learning has also received Best Paper Awards at the Embedded Vision Workshop and at the International Conference on Parallel Processing.

As an entrepreneur Kurt has served as an angel investor and advisor to over twenty-five start-up companies including C-Cube Microsystems, Coverity, Simplex, and Tensilica. Kurt co-founded DeepScale with his PhD student Forrest Iandola. DeepScale was acquired by Tesla in 2019.

Making Deep Learning Efficient(Track Keynote)

Chair, Department of StatisticsColumbia University

Tian Zheng, PhD

Tian Zheng is Professor and Department Chair of Statistics at Columbia University. She develops novel methods for exploring and understanding patterns in complex data from different application domains. Her current projects are in the fields of statistical machine learning, spatiotemporal modeling and social network analysis. Professor Zheng’s research has been recognized by the 2008 Outstanding Statistical Application Award from the American Statistical Association (ASA), the Mitchell Prize from ISBA and a Google research award. She became a Fellow of American Statistical Association in 2014. Professor Zheng is the recipient of the 2017 Columbia’s Presidential Award for Outstanding Teaching. From 2018-2020, she has been the chair-elect, chair and past-chair for ASA’s section on Statistical Learning and Data Science.

Topic-Adjusted Visibility Metric for Scientific Articles(Track Keynote)

CEOAllen Institute for AI

Oren Etzioni, PhD

Dr. Oren Etzioni has served as the Chief Executive Officer of the Allen Institute for AI (AI2) since its inception in 2014. He has been a Professor at the University of Washington’s Computer Science department since 1991, and a Venture Partner at the Madrona Venture Group since 2000. He has garnered several awards including Seattle’s Geek of the Year (2013), the Robert Engelmore Memorial Award (2007), the IJCAI Distinguished Paper Award (2005), AAAI Fellow (2003), and a National Young Investigator Award (1993). He has been the founder or co-founder of several companies, including Farecast (sold to Microsoft in 2008) and Decide (sold to eBay in 2013). He has written commentary on AI for The New York Times, Nature, Wired, and the MIT Technology Review. He helped to pioneer meta-search (1994), online comparison shopping (1996), machine reading (2006), and Open Information Extraction (2007). He has authored over 100 technical papers that have garnered over 2,000 highly influential citations on Semantic Scholar. He received his Ph.D. from Carnegie Mellon in 1991 and his B.A. from Harvard in 1986.

VP Data & Analytics, Cybersecurity Technology and ControlsJPMorgan Chase & Co

Charles Givre

Charles Givre recently joined JP Morgan Chase works as a data scientist and technical product manager in the cybersecurity and technology controls group. Prior to joining JP Morgan, Mr. Givre worked as a lead data scientist for Deutsche Bank. Mr. Givre worked as a Senior Lead Data Scientist for Booz Allen Hamilton for seven years where he worked in the intersection of cybersecurity and data science. At Booz Allen, Mr. Givre worked on one of Booz Allen’s largest analytic programs where he led data science efforts and worked to expand the role of data science in the program. Mr. Givre is passionate about teaching others data science and analytic skills and has taught data science classes all over the world at conferences, universities and for clients. Mr. Givre taught data science classes at BlackHat, the O’Reilly Security Conference, the Center for Research in Applied Cryptography and Cyber Security at Bar Ilan University. He is a sought-after speaker and has delivered presentations at major industry conferences such as Strata-Hadoop World, Open Data Science Conference and others. One of Mr. Givre’s research interests is increasing the productivity of data science and analytic teams, and towards that end, he has been working extensively to promote the use of Apache Drill in security applications and is a committer and PMC Member for the Drill project. Mr. Givre teaches online classes for O’Reilly about Drill and Security Data Science and is a coauthor for the O’Reilly book Learning Apache Drill. Prior to joining Booz Allen, Mr. Givre, worked as a counterterrorism analyst at the Central Intelligence Agency for five years. Mr. Givre holds a Masters Degree in Middle Eastern Studies from Brandeis University, as well as a Bachelors of Science in Computer Science and a Bachelor’s of Music both from the University of Arizona. Mr. Givre blogs at thedataist.com and tweets @cgivre.

Rapid Data Exploration and Analysis with Apache Drill(Half-Day Training)

Professor, Computer ScienceNortheastern University

Tina Eliassi-Rad, PhD

Tina Eliassi-Rad is a Professor of Computer Science at Northeastern University. She is also a core faculty member at Northeastern University’s Network Science Institute. Prior to joining Northeastern, Tina was an Associate Professor of Computer Science at Rutgers University; and before that she was a Member of Technical Staff and Principal Investigator at Lawrence Livermore National Laboratory. Tina earned her Ph.D. in Computer Sciences at the University of Wisconsin-Madison. Her research is rooted in data mining and machine learning; and spans theory, algorithms, and applications of big data from networked representations of physical and social phenomena. She has over 100 peer-reviewed publications (including a few best paper and best paper runner-up awardees). Tina’s work has been applied to personalized search on the World-Wide Web, statistical indices of large-scale scientific simulation data, fraud detection, mobile ad targeting, cyber situational awareness, and ethics in machine learning. Her algorithms have been incorporated into systems used by the government and industry (e.g., IBM System G Graph Analytics) as well as open-source software (e.g., Stanford Network Analysis Project). In 2017, Tina served as the program co-chair for the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining  and as the program co-chair for the International Conference on Network Science . In 2020, she is serving as the program co-chair for the International Conference on Computational Social Science. Tina received an Outstanding Mentor Award from the Office of Science at the US Department of Energy in 2010; and became a Fellow of the ISI Foundation in Turin Italy in 2019. 

Just Machine Learning(Talk)

Boeing Assistant Professor of Aeronautics and AstronauticsMIT

Julie A. Shah, PhD

Julie Shah is an Associate Professor in the Department of Aeronautics and Astronautics at MIT and leads the Interactive Robotics Group of the Computer Science and Artificial Intelligence Laboratory. Shah received her SB (2004) and SM (2006) from the Department of Aeronautics and Astronautics at MIT, and her PhD (2010) in Autonomous Systems from MIT. Before joining the faculty, she worked at Boeing Research and Technology on robotics applications for aerospace manufacturing. She has developed innovative methods for enabling fluid human-robot teamwork in time-critical, safety-critical domains, ranging from manufacturing to surgery to space exploration. Her group draws on expertise in artificial intelligence, human factors, and systems engineering to develop interactive robots that emulate the qualities of effective human team members to improve the efficiency of human-robot teamwork. In 2014, Shah was recognized with an NSF CAREER award for her work on “Human-aware Autonomy for Team-oriented Environments,” and by the MIT Technology Review TR35 list as one of the world’s top innovators under the age of 35. Her work on industrial human-robot collaboration was also recognized by the Technology Review as one of the 10 Breakthrough Technologies of 2013, and she has received international recognition in the form of best paper awards and nominations from the International Conference on Automated Planning and Scheduling, the American Institute of Aeronautics and Astronautics, the IEEE/ACM International Conference on Human-Robot Interaction, the International Symposium on Robotics, and the Human Factors and Ergonomics Society.

What to Expect When You Are Expecting Robots – The Future of Human-Robot Collaboration(Talk)

Machine Learning Researcher and Vanier Doctoral ScholarMila and McGill University

Charles Onu, PhD

Charles is a PhD candidate at McGill University and Mila – the Québec AI Institute. He is interested in the design and development of improved diagnostic and decision-making tools in healthcare. He leads the Ubenwa Health, a collaboration between researchers in Canada and Nigeria, developing low-cost, AI-powered mobile app for the diagnosis of perinatal asphyxia from the infant cry. At the Montreal Children’s Hospital, Charles is involved in the APEX project, where he has been developing machine learning algorithms for analyzing cardiorespiratory behaviour of preterm newborns in order to determine their readiness for extubation. He has worked with Health Experiences Research Canada contributing to the design and leading the development of the HERS mobile app – a personalized recommendation tool for breast cancer patients. Charles is a Jeanne Sauvé Fellow and a Vanier Doctoral Scholar.

Using Artificial Intelligence to Save Lives at Birth(Talk)

deep learning with TensorFlow
Chief Data ScientistUntapt

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.

Director of Applied Statistics CenterColumbia University

Andrew Gelman, PhD

Andrew Gelman is a professor of statistics and political science and director of the Applied Statistics Center at Columbia University. He has received the Outstanding Statistical Application award from the American Statistical Association, the award for best article published in the American Political Science Review, and the Council of Presidents of Statistical Societies award for outstanding contributions by a person under the age of 40. His books include Bayesian Data Analysis (with John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Don Rubin), Teaching Statistics: A Bag of Tricks (with Deb Nolan), Data Analysis Using Regression and Multilevel/Hierarchical Models (with Jennifer Hill), Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do (with David Park, Boris Shor, and Jeronimo Cortina), and A Quantitative Tour of the Social Sciences (co-edited with Jeronimo Cortina). Andrew has done research on a wide range of topics, including: why it is rational to vote; why campaign polls are so variable when elections are so predictable; why redistricting is good for democracy; reversals of death sentences; police stops in New York City, the statistical challenges of estimating small effects; the probability that your vote will be decisive; seats and votes in Congress; social network structure; arsenic in Bangladesh; radon in your basement; toxicology; medical imaging; and methods in surveys, experimental design, statistical inference, computation, and graphics.

Bayesian Workflow as Demonstrated with a Coronavirus Example(Talk)

Founder & Chief Scientist, ProfessorPetuum, Carnegie Mellon University

Eric Xing, PhD

Eric P. Xing is a Professor of Computer Science at Carnegie Mellon University, and the Founder, CEO, and Chief Scientist of Petuum Inc., a 2018 World Economic Forum Technology Pioneer company that builds standardized artificial intelligence development platform and operating system for broad and general industrial AI applications. He completed his undergraduate study at Tsinghua University, and holds a PhD in Molecular Biology and Biochemistry from the State University of New Jersey, and a PhD in Computer Science from the University of California, Berkeley. His main research interests are the development of machine learning and statistical methodology, and large-scale computational system and architectures, for solving problems involving automated learning, reasoning, and decision-making in high-dimensional, multimodal, and dynamic possible worlds in artificial, biological, and social systems. Prof. Xing currently serves or has served the following roles: associate editor of the Journal of the American Statistical Association (JASA), Annals of Applied Statistics (AOAS), IEEE Journal of Pattern Analysis and Machine Intelligence (PAMI) and the PLoS Journal of Computational Biology; action editor of the Machine Learning Journal (MLJ) and Journal of Machine Learning Research (JMLR); member of the United States Department of Defense Advanced Research Projects Agency (DARPA) Information Science and Technology (ISAT) advisory group. He is a recipient of the Carnegie Science Award, National Science Foundation (NSF) Career Award, the Alfred P. Sloan Research Fellowship in Computer Science, the United States Air Force Office of Scientific Research Young Investigator Award, the IBM Open Collaborative Research Faculty Award, as well as several best paper awards. Prof Xing is a board member of the International Machine Learning Society; he has served as the Program Chair (2014) and General Chair (2019) of the International Conference of Machine Learning (ICML); he is also the Associate Department Head of the Machine Learning Department, founding director of the Center for Machine Learning and Health at Carnegie Mellon University; and he is a Fellow of the Association of Advancement of Artificial Intelligence (AAAI), and an IEEE Fellow.

David Talby: NLP for healthcare
CTOPacific AI, John Snow Labs

David Talby, PhD

David Talby is a chief technology officer at Pacific AI, helping fast-growing companies apply big data and data science techniques to solve real-world problems in healthcare, life science, and related fields. David has extensive experience in building and operating web-scale data science and business platforms, as well as building world-class, Agile, distributed teams. Previously, he was with Microsoft’s Bing Group, where he led business operations for Bing Shopping in the US and Europe and worked at Amazon both in Seattle and the UK, where he built and ran distributed teams that helped scale Amazon’s financial systems. David holds a Ph.D. in computer science and master’s degrees in both computer science and business administration.

Model Governance: A checklist for getting AI safely to production(Talk)

State-of-the-Art Natural Language Processing with Spark NLP(Tutorial)

Principal Research Scientist Google DeepMind

Oriol Vinyals, PhD

Oriol Vinyals is a Principal Scientist at Google DeepMind, and a team lead of the Deep Learning group. His work focuses on Deep Learning and Artificial Intelligence. Prior to joining DeepMind, Oriol was part of the Google Brain team. He holds a Ph.D. in EECS from the University of California, Berkeley and is a recipient of the 2016 MIT TR35 innovator award. His research has been featured multiple times at the New York Times, Financial Times, WIRED, BBC, etc., and his articles have been cited over 85000 times. Some of his contributions such as seq2seq, knowledge distillation, or TensorFlow are used in Google Translate, Text-To-Speech, and Speech recognition, serving billions of queries every day, and he was the lead researcher of the AlphaStar project, creating an agent that defeated a top professional at the game of StarCraft, achieving Grandmaster level, also featured as the cover of Nature. At DeepMind he continues working on his areas of interest, which include artificial intelligence, with particular emphasis on machine learning, deep learning and reinforcement learning.

AlphaStar: Grandmaster Level in StarCraft II Using Multi-Agent Reinforcement Learning(Track Keynote)

C.V. Starr Distinguished Professor of Finance | Visiting ScholarHofstra University

Ahmet K. Karagozoglu, Ph.D.

Dr. Ahmet Karagozoglu is the C.V. Starr Distinguished Professor in Finance & Investment Banking at Hofstra University and a visiting scholar at the Volatility and Risk Institute at New York University. He is also the founding academic director of the Martin B. Greenberg Trading Room at Hofstra’s Zarb School of Business since 2005. He was a visiting research professor at NYU’s Stern School of Business in 2019.
Dr. Karagozoglu’s primary research interests are in the areas of financial derivatives, risk management and market microstructure. His recently published articles focus on idiosyncratic volatility and news; short-sale constraints and information asymmetry; volatility and social media sentiment; credit risk and CDS markets; stress testing and model validation. Currently, he is investigating, with Dr. Nazli S. Alan and Dr. Robert F. Engle, the language complexity of earnings calls transcripts and volatility, using NLP, and the impact of COVID-19 pandemic on volatility in global equity markets.

Language Complexity and Volatility in Financial Markets: Using NLP to Further our Understanding of Information Processing(Track Keynote)

Assistant ProfessorUC Davis Machine Learning & AI Group UC Davis

Gerald Quon, PhD

Gerald Quon is an Assistant Professor in the Department of Molecular and Cellular Biology at the University of California at Davis. He obtained his Ph.D. in Computer Science from the University of Toronto, M.Sc. in Biochemistry from the University of Toronto, and B. Math in Computer Science from the University of Waterloo. He also completed postdoctoral research training at MIT. His lab focuses on applications of machine learning to human genetics, genomics and health, and is funded by the National Science Foundation, National Institutes of Health, the Chan Zuckerberg Initiative, and the American Cancer Society.

A Hands-On Tutorial for Training Interpretable Variational Autoencoders Using siVAE(Workshop)

Founder | Former Research ScientistStealth Startup |Open AI

Josh Tobin, PhD

Josh is the Founder of Stealth Startup and his research focuses on applying deep reinforcement learning, generative models, and synthetic data to problems in robotic perception and control. Additionally, he co-organizes a machine learning training program for engineers to learn about production-ready deep learning called Full Stack Deep Learning. Previously, Josh was a Research Scientist at OpenAI working at the intersection of machine learning and robotics. Josh did his PhD in Computer Science at UC Berkeley advised by Pieter Abbeel. He have also been a management consultant at McKinsey and an Investment Partner at Dorm Room Fund.

Testing Production Machine Learning Systems (Talk)

Professor, Computer ScienceUniversity of California - Los Angeles

Sriram Sankararaman, PhD

Sriram Sankararaman is an assistant professor in the Departments of Computer Science, Human Genetics, and Computational Medicine at UCLA where he leads the machine learning and genomic lab. His research interests lie at the interface of computer science, statistics and biology and is interested in developing statistical machine learning algorithms to make sense of large-scale biomedical data and in using these tools to understand the interplay between evolution, our genomes and traits. He received a B.Tech. in Computer Science from the Indian Institute of Technology, Madras, a Ph.D. in Computer Science from UC Berkeley and was a post-doctoral fellow in Harvard Medical School before joining UCLA. He is a recipient of the Alfred P. Sloan Foundation fellowship (2017), Okawa Foundation grant (2017), the UCLA Hellman fellowship (2017), the NIH Pathway to Independence Award (2014), a Simons Research fellowship (2014), and a Harvard Science of the Human Past fellowship (2012) as well as the Northrop-Grumman Excellence in Teaching Award at UCLA (2019).

Machine Learning for Biology and Medicine(Talk)


See our full Speaker LineUP

8 Focus Areas. 4 Days. One Data Science Conference

The largest applied data science conference is now 4 days, including mini-bootcamp days, 3 full training days, and 2 talks/workshops days. You get even more talks, trainings, and workshops spread over 8 focus areas. Accelerate your data science knowledge, training, and network all in one event. Start learning now with our pre-bootcamp live and on-demand training and hackathon.

ODSC in 60 Seconds

Conference Focus Areas

November 15th – 18th, 2021

AI for Social Good

Applying AI to help solve social, climate, and humanitarian challenges
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EVENT SUMMARY

Pre-conference Training & Hackathon

– A real immersive learning experience –

Start learning now with live and on-demand pre-bootcamp sessions.  

4 Days of Data Science Training 

– Taught by World-Class Data Scientists –

Learn the latest data science concepts, tools, and techniques from the best.  

2 Days of Keynotes, Talks, and Workshops 

– Presented by the best in the field of data science –                             

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Access to Keynotes, Talks & Workshops (Thur-Fri)
Access to Sessions Recordings and slides **
Access to Networking Receptions, Meet the Experts, Dinner with DS and more
Access to AI Solution Showcase Expo Area
Access to Demo Talks (Wed-Thur)
Access to Career Lab & Expo (Fri)
Access to Wednesday Training & Workshop Sessions
Accelerate AI Business Summit (Business Talks & Panels on Tue-Wed)
Access to Tuesday Training Sessions
Daily Access to Speaker/VIP networking Lunch
Daily Access to Speaker & VIP Lounge
VIP Registration & Gift Bag
VIP, Speaker, & Business Networking Reception (Tues)
Biz 2-Day
$1,196
Business Talks & Workshops (2 Days Tue/Wed)
Access to Keynotes, Talks & Workshops (Thur-Fri)
Access to Sessions Recordings and slides **
Access to Networking Receptions, Meet the Experts, Dinner with DS and more
Access to AI Solution Showcase Expo Area
Access to Demo Talks (Wed-Thur)
Access to Career Lab & Expo (Fri)
Access to Wednesday Training & Workshop Sessions
Accelerate AI Business Summit (Business Talks & Panels on Tue-Wed)
Access to Tuesday Training Sessions
Daily Access to Speaker/VIP networking Lunch
Daily Access to Speaker & VIP Lounge
VIP Registration & Gift Bag
VIP, Speaker, & Business Networking Reception (Tues)
Go to Door
Silver
$1,436
ODSC Talks & Workshops (2 Days Thur/Fri)
Access to Keynotes, Talks & Workshops (Thur-Fri)
Access to Sessions Recordings and slides **
Access to Networking Receptions, Meet the Experts, Dinner with DS and more
Access to AI Solution Showcase Expo Area
Access to Demo Talks (Wed-Thur)
Access to Career Lab & Expo (Fri)
Access to Wednesday Training & Workshop Sessions
Accelerate AI Business Summit (Business Talks & Panels on Tue-Wed)
Access to Tuesday Training Sessions
Daily Access to Speaker/VIP networking Lunch
Daily Access to Speaker & VIP Lounge
VIP Registration & Gift Bag
VIP, Speaker, & Business Networking Reception (Tues)
Go to Door
Gold
$2,796
ODSC Training, Workshops, Talks (3 Days Wed,Thur&Fri)
Access to Keynotes, Talks & Workshops (Thur-Fri)
Access to Sessions Recordings and slides **
Access to Networking Receptions, Meet the Experts, Dinner with DS and more
Access to AI Solution Showcase Expo Area
Access to Demo Talks (Wed-Thur)
Access to Career Lab & Expo (Fri)
Access to Wednesday Training & Workshop Sessions
Accelerate AI Business Summit (Business Talks & Panels on Tue-Wed)
Access to Tuesday Training Sessions
Daily Access to Speaker/VIP networking Lunch
Daily Access to Speaker & VIP Lounge
VIP Registration & Gift Bag
VIP, Speaker, & Business Networking Reception (Tues)
Go to Door
Platinum
$3,596
All 4 Days (Tue,Wed,Thur&Fri)
Access to Keynotes, Talks & Workshops (Thur-Fri)
Access to Sessions Recordings and slides **
Access to Networking Receptions, Meet the Experts, Dinner with DS and more
Access to AI Solution Showcase Expo Area
Access to Demo Talks (Wed-Thur)
Access to Career Lab & Expo (Fri)
Access to Wednesday Training & Workshop Sessions
Accelerate AI Business Summit (Business Talks & Panels on Tue-Wed)
Access to Tuesday Training Sessions
Daily Access to Speaker/VIP networking Lunch
Daily Access to Speaker & VIP Lounge
VIP Registration & Gift Bag
VIP, Speaker, & Business Networking Reception (Tues)
Go to Door
VIP
$5,196
VIP All 4 Days (Tue,Wed,Thur&Fri)
Access to Keynotes, Talks & Workshops (Thur-Fri)
Access to Sessions Recordings and slides **
Access to Networking Receptions, Meet the Experts, Dinner with DS and more
Access to AI Solution Showcase Expo Area
Access to Demo Talks (Wed-Thur)
Access to Career Lab & Expo (Fri)
Access to Wednesday Training & Workshop Sessions
Accelerate AI Business Summit (Business Talks & Panels on Tue-Wed)
Access to Tuesday Training Sessions
Daily Access to Speaker/VIP networking Lunch
Daily Access to Speaker & VIP Lounge
VIP Registration & Gift Bag
VIP, Speaker, & Business Networking Reception (Tues)
Go to Door

Save 75% on Door Price Price

STATUS
First 100
Door Price
Access to Keynotes, Talks & Workshops (Thur-Fri)
Access to Sessions Recordings and slides **
Access to Networking Receptions, Meet the Experts, Dinner with DS and more
Access to AI Solution Showcase Expo Area
Access to Demo Talks (Wed-Thur)
Access to Career Lab & Expo (Fri)
Access to Wednesday Training & Workshop Sessions
Accelerate AI Business Summit (Business Talks & Panels on Tue-Wed)
Access to Tuesday Training Sessions
Daily Access to Speaker/VIP networking Lunch
Daily Access to Speaker & VIP Lounge
VIP Registration & Gift Bag
VIP, Speaker, & Business Networking Reception (Tues)
Biz 2-Day
$299.00
Business Talks & Workshops (2 Days Tue/Wed)
Access to Keynotes, Talks & Workshops (Thur-Fri)
Access to Sessions Recordings and slides **
Access to Networking Receptions, Meet the Experts, Dinner with DS and more
Access to AI Solution Showcase Expo Area
Access to Demo Talks (Wed-Thur)
Access to Career Lab & Expo (Fri)
Access to Wednesday Training & Workshop Sessions
Accelerate AI Business Summit (Business Talks & Panels on Tue-Wed)
Access to Tuesday Training Sessions
Daily Access to Speaker/VIP networking Lunch
Daily Access to Speaker & VIP Lounge
VIP Registration & Gift Bag
VIP, Speaker, & Business Networking Reception (Tues)
Save 75%
Biz 4-Day
$599.00
Business Talks & Workshops on Days 1&2 (Tue&Wed) and All ODSC Talks & Workshops on Days 3&4 (Thur&Fri)
Access to Keynotes, Talks & Workshops (Thur-Fri)
Access to Sessions Recordings and slides **
Access to Networking Receptions, Meet the Experts, Dinner with DS and more
Access to AI Solution Showcase Expo Area
Access to Demo Talks (Wed-Thur)
Access to Career Lab & Expo (Fri)
Access to Wednesday Training & Workshop Sessions
Accelerate AI Business Summit (Business Talks & Panels on Tue-Wed)
Access to Tuesday Training Sessions
Daily Access to Speaker/VIP networking Lunch
Daily Access to Speaker & VIP Lounge
VIP Registration & Gift Bag
VIP, Speaker, & Business Networking Reception (Tues)
Save 75%
VIP
$1,299
VIP All 4 Days (Tue,Wed,Thur&Fri)
Access to Keynotes, Talks & Workshops (Thur-Fri)
Access to Sessions Recordings and slides **
Access to Networking Receptions, Meet the Experts, Dinner with DS and more
Access to AI Solution Showcase Expo Area
Access to Demo Talks (Wed-Thur)
Access to Career Lab & Expo (Fri)
Access to Wednesday Training & Workshop Sessions
Accelerate AI Business Summit (Business Talks & Panels on Tue-Wed)
Access to Tuesday Training Sessions
Daily Access to Speaker/VIP networking Lunch
Daily Access to Speaker & VIP Lounge
VIP Registration & Gift Bag
VIP, Speaker, & Business Networking Reception (Tues)
Save 75%
Access to Keynotes, Talks & Workshops (Thur-Fri)
Access to Sessions Recordings and slides **
Access to Networking Receptions, Meet the Experts, Dinner with DS and more
Access to AI Solution Showcase Expo Area
Access to Demo Talks (Wed-Thur)
Access to Career Lab & Expo (Fri)
Access to Wednesday Training & Workshop Sessions
Accelerate AI Business Summit (Business Talks & Panels on Tue-Wed)
Access to Tuesday Training Sessions
Daily Access to Speaker/VIP networking Lunch
Daily Access to Speaker & VIP Lounge
VIP Registration & Gift Bag
VIP, Speaker, & Business Networking Reception (Tues)
Biz 2-Day
$1,196
Business Talks & Workshops (2 Days Tue/Wed)
Access to Keynotes, Talks & Workshops (Thur-Fri)
Access to Sessions Recordings and slides **
Access to Networking Receptions, Meet the Experts, Dinner with DS and more
Access to AI Solution Showcase Expo Area
Access to Demo Talks (Wed-Thur)
Access to Career Lab & Expo (Fri)
Access to Wednesday Training & Workshop Sessions
Accelerate AI Business Summit (Business Talks & Panels on Tue-Wed)
Access to Tuesday Training Sessions
Daily Access to Speaker/VIP networking Lunch
Daily Access to Speaker & VIP Lounge
VIP Registration & Gift Bag
VIP, Speaker, & Business Networking Reception (Tues)
Register
Biz 4-Day
$2,396
Business Talks & Workshops (Tue&Wed) and ODSC Talks & Workshops (Thur&Fri)
Access to Keynotes, Talks & Workshops (Thur-Fri)
Access to Sessions Recordings and slides **
Access to Networking Receptions, Meet the Experts, Dinner with DS and more
Access to AI Solution Showcase Expo Area
Access to Demo Talks (Wed-Thur)
Access to Career Lab & Expo (Fri)
Access to Wednesday Training & Workshop Sessions
Accelerate AI Business Summit (Business Talks & Panels on Tue-Wed)
Access to Tuesday Training Sessions
Daily Access to Speaker/VIP networking Lunch
Daily Access to Speaker & VIP Lounge
VIP Registration & Gift Bag
VIP, Speaker, & Business Networking Reception (Tues)
Register
VIP
$5,196
VIP All 4 Days (Tue,Wed,Thur&Fri)
Access to Keynotes, Talks & Workshops (Thur-Fri)
Access to Sessions Recordings and slides **
Access to Networking Receptions, Meet the Experts, Dinner with DS and more
Access to AI Solution Showcase Expo Area
Access to Demo Talks (Wed-Thur)
Access to Career Lab & Expo (Fri)
Access to Wednesday Training & Workshop Sessions
Accelerate AI Business Summit (Business Talks & Panels on Tue-Wed)
Access to Tuesday Training Sessions
Daily Access to Speaker/VIP networking Lunch
Daily Access to Speaker & VIP Lounge
VIP Registration & Gift Bag
VIP, Speaker, & Business Networking Reception (Tues)
Register

Registration & Discount Resources

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.

Diversity and Inclusion Scholarship

The data science and the tech communities should strive to be more inclusive and offer opportunities for everyone to learn and grow their career in data science. To help achieve this goal ODSC offers diversity and inclusion scholarship passes to minorities, underrepresented groups, graduate students, and others who express interest in the content ODSC offers. We will open the application soon.

Discounts

We offer academic, government, non-profit and start-up discounts.

To find out more please check later.

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.

How to Convince your manager to attend ODSC West 2021?

Let us help you convince your manager that your attendance will benefit your organization.
Please check HERE for more information.

Volunteer

In exchange for a free pass, ODSC is seeking volunteers to help with our program and event planning.  See more details HERE.

Donate to our Fundraise

For this year’s event, ODSC West is donating to Girls Who Code and Black Girls Who Code. We invite you to join us and donate to our fundraiser.  Both these organizations are dedicated to increasing the number of women in engineering and helping them become innovators in the STEM fields. Please donate what you can via our registration. No purchase is necessary to donate and 100% of funds raised are donated. 

AI EXPO PARTNERS

Limited Booths Availability

Join ODSC West Expo

REQUEST BROCHURE

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ODSC Virtual Conference – How It Works

  • Virtual conference experience includes networking lounge area, speaker auditorium, expo halls, and prizes

  • Access multiple livestream tracks on Tuesday, Wednesday, Thursday, or Friday

  • Switch between sessions or tracks as your interests dictate

  • 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

  • Directly download slides and other session materials

  • (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.

Where Business Meets AI

Ai X  Business Summit

Co-located at ODSC West, Ai X brings together the leading practitioners, innovation experts, and business professionals that drive artificial intelligence across a range of industries

Innovation

Discover how techniques from Machine Learning, Deep Learning, and Predictive Analytics are driving AI Innovation

Expertise

Gain AI expertise and learn from leading experts how to work with the frameworks and tools employed in AI

Management

Manage and deploy AI in the real world. Hear from AI management and heads of data science teams on a range of topics

Networking

Network with the AI experts, innovators, business professionals, and data scientists building the future of AI

Full Details

Past ODSC Speakers

Daphne Koller, PhD
Daphne Koller, PhD

Co Founder & Co-Chairman

Coursera

Andrej Karpathy, PhD
Andrej Karpathy, PhD

Director of AI

Tesla

Hilary Mason
Hilary Mason

GM of Machine Learning Cloudera

CEO of Fast Forward Labs,

DJ Patil
DJ Patil

Former

U.S. Chief Data Scientist

Cathy O'Neil
Cathy O'Neil

Author

Weapons of Math Destruction

Dawn Xiaodong Song, PhD
Dawn Xiaodong Song, PhD

One of MIT’s “the Top 35 Innovators in the World under the age of 35,

University of California - Berkeley, BAIR Lab

Pieter Abbeel, PhD
Pieter Abbeel, PhD

Professor & Director, Robot Learning Lab, Co-Founder

UC Berkeley, covariant.ai, Gradescope

Michael I. Jordan, PhD
Michael I. Jordan, PhD

Cited as one of the world's most influential data scientists,

UC Berkeley AI Lab

Rachel Thomas, PhD
Rachel Thomas, PhD

One of Forbes’ “20 Incredible Women in AI, Co-founder at fast.ai

fast.ai, University of San Francisco

Dr. Jürgen Schmidhuber
Dr. Jürgen Schmidhuber

Scientific Director, Professor of AI

IDSIA, USI

Yoshua Bengio, PhD
Yoshua Bengio, PhD

Professor, Université de Montréal

Scientific Director - MILA

Professor Alex Pentland
Professor Alex Pentland

Director

MIT Connection Science and Human Dynamics labs

Drew Conway, PhD
Drew Conway, PhD

Entrepreneur, author, and Data Scientist

Mike Stonebreaker
Mike Stonebreaker

A.M. Turing Award Laureate, Professor, Co-Founder

MIT CSAIL, Tamr

Professor Gary Marcus
Professor Gary Marcus

Scientist, Author, and award-winning NYU Professor

Dr. Kirk Borne
Dr. Kirk Borne

Principal Data Scientist

Booz Allen Hamilton

Manuela Veloso, PhD
Manuela Veloso, PhD

Head of AI Research, Head of ML Dept.(On Leave) At CMU

J.P. Morgan., CMU

Regina Barzilay, PhD
Regina Barzilay, PhD

Professor, MacArthur Fellow

MIT CSAIL

Reza Zadeh, PhD
Reza Zadeh, PhD

Founder and CEO at Matroid and Adjunct Professor at Stanford University

Matroid

Cassie Kozyrkov, PhD
Cassie Kozyrkov, PhD

Global Leader in Decision Intelligence at Google

Chief Decision Scientist Google

Research Frontiers - Past Participating AI Labs

ODSC is delighted to host presentations from the following research labs including:

Partnering With ODSC

Last year, ODSC welcomed nearly 20,000 attendees to an unparalleled range of events, from our large conferences, to hackathons and small community gatherings.
Request Partnership Brief

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