Scrupulously managed data and open source software projects are changing the way we build AI products.
Together, they're the backbone of today's cloud deployment. Join this conference to learn about how best to leverage your investments of time and manpower and finally put your project into production.
Data Scientists/Engineers
ML Engineers
AI Engineers/Developers
AI Architects
Citizen Data Scientists
Cloud Architects
Why Virtual Community Day?
1-Day virtual
conference
Learning platform for
developers
There's no cost – This part speaks for itself, right?
It’s global – Join from the convenience of your home or desk. All sessions will be webcast live. No badges, no lines, no travel. And most importantly, all of the talks are available for replay for 90 days.
It’s valuable – All of our presenters are developers and managers from IBM and associated companies who build things for users just like you. Many of them will offer office hour sessions, scheduled interviews or even a troubleshooting call.
25 industry speakers
Evangelist/Data Science Thought Leader
Derwen AI
Industry Analyst / Speaker / Researcher / Thought Leader
TWIML
Distinguished Engineer and Director, Data & AI
IBM
Distinguished Engineer, Master Inventor,
Fellow of the Royal Academy of Engineering
IBM
Chief ML Scientist and Head of Machine Learning
SIG
Principal Research Staff Member and Manager, AI Lifecycle Acceleration
IBM
Chief Analytics Officer, IBM FSS Industry and Distinguished Engineer
IBM
Director of AI Platforms and Runtimes, IBM Research AI
IBM
Manager of AI Security and Privacy Solutions - Research Staff Member, Ph.D.
IBM
Principal Research Staff Member, IBM T. J. Watson Research Center
IBM
Lead Data Scientist, Machine Learning Hub World Wide
IBM
Data Science and AI Curriculum Developer
IBM
AI Solutions Architect Data Science Practitioner
IBM
Research Staff Member, IBM Research AI
IBM
Tech Lead/Manager, Data Scientist - Thought Leader, Master Inventor and Academy of Technology Member
IBM
Data Scientist on Data and AI Technical Marketing Team
IBM
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Known as a "player/coach", with core expertise in data science, natural language processing, machine learning, cloud computing; 35+ years tech industry experience, ranging from Bell Labs to early-stage start-ups. Co-chair Rev. Advisor for NYU Coleridge Initiative, IBM Data Science Community, Amplify Partners, Anyscale, Recognai, Primer, Data Spartan. Former role: Director, Community Evangelism @ Databricks and Apache Spark.
Evangelist/Data Science Thought Leader
Derwen AI
Mike serves as Chief ML Scientist and Head of Machine Learning for SIG, UC Berkeley Data Science faculty, and Director of Phronesis ML Labs. He has led teams of Data Scientists in the bay area as Head of Data Science at Uber ATG, Chief Data Scientist for InterTrust and Takt, Director of Data Science for MetaScale/Sears, and CSO for Galvanize where he founded the galvanizeU-UNH accredited Masters in Data Science degree and oversaw the company's transformation from co-working space to Data Science organization. Mike began his career in academia serving as a mathematics teaching fellow for Columbia University before teaching at the University of Pittsburgh.
Chief ML Scientist and Head of Machine Learning
SIG
Roger McNamee is the author of the New York Times bestseller, Zucked: Waking Up to the Facebook Catastrophe, which documents his journey from mentor to Mark Zuckerberg to critic of Facebook. Since April 2017, Roger has been engaged, along with former Google design ethicist Tristan Harris and others, in a campaign to trigger a global conversation about the dark side of social media.
In the context of his activism, Roger has been featured in two documentaries, The Facebook Dilemma, a PBS Frontline film about election interference which won the coveted Peabody Award, and The Great Hack, about Cambridge Analytica. Roger will also be featured in two other documentaries that are in the works.
Roger began his career in 1982 at T. Rowe Price Associates, where he managed the top performing Science & Technology Fund and co-managed the New Horizons Fund. In 1991, he launched Integral Capital Partners, the first crossover fund (combining later stage venture capital with public market investments), in partnership with Kleiner Perkins Caufield & Byers and Morgan Stanley & Co. In 1999, Roger co-founded Silver Lake Partners, the first private equity fund focused on technology businesses. In 2004, Roger and his partners launched Elevation Partners, an investment partnership focused on the intersection of media and technology. U2’s Bono was a co-founder of Elevation.
Roger is a frequent guest on “Squawk Alley” on CNBC and on Ali Velshi’s show on MSNBC. He was a technical advisor to HBO’s Silicon Valley for seasons 2 through 6.
In philanthropy, Roger is a co-founder of the Haight Street Art Center and the Center for Counterculture Studies. He also serves on the board of directors for the Rock and Roll Hall of Fame Museum and the Rex Foundation. Roger is a past member of boards of the Tuck School of Business at Dartmouth College, Bryn Mawr College, The GRAMMY Foundation, and the operating business of the National Geographic Society. He was also responsible for raising the money that created the Wikimedia Foundation. Roger serves on the advisory boards of the Center for Humane Technology, the Open Markets Institute and the Electronic Privacy Information Center (EPIC).
Roger performs in the bands Full Moonalice and Doobie Decibel System, in which he plays guitar and guitar. Moonalice pioneered livestream concert videos and is renowned for the quality of poster art associated with the band. The Moonalice series exceeds 1,160 posters after twelve years. Moonalice’s single “It’s 420 Somewhere” has been downloaded more than 4.6 million times, a record from a band’s own website that has been certified by the Rock ‘n’ Roll Hall of Fame.
Roger holds a B. A. from Yale University and an M.B.A. for the Amos Tuck School of Business at Dartmouth College.
Roger holds four U.S. patents related to live broadcast of video to mobile devices.
Links:
TIME magazine cover story about Zucked:
https://time.com/magazine/us/5505429/january-28th-2019-vol-193-no-3-u-s/
New Yorker profile:
https://www.newyorker.com/magazine/2019/12/02/big-techs-big-defector
Managing Director & Co-Founder,
Author of Zucked
Elevation Partners
Nathalie Baracaldo leads the AI Security and Privacy Solutions team and is a Research Staff Member at IBM’s Almaden Research Center in San Jose, CA. Nathalie is passionate about delivering machine learning solutions that are highly accurate, withstand adversarial attacks and protect data privacy. Her team focuses on two main areas: federated learning, where models are trained without directly accessing training data and adversarial machine learning, where defenses are designed to withstand potential attacks to the machine learning pipeline. Nathalie has over eighteen patents filed, and five granted. She has published more than twenty papers in peer-reviewed conferences and journals, receiving two best paper awards. Nathalie received her Ph.D. degree from the University of Pittsburgh in 2016.
Manager of AI Security and Privacy Solutions - Research Staff Member, Ph.D.
IBM
Sam Charrington is a noted ML/AI industry analyst and host of the popular TWIML AI Podcast (This Week in Machine Learning and AI). The show has nearly 7 million downloads and regularly appears on Apple’s Top 40 Tech Podcasts chart. Sam has interviewed over 300 of the industry’s leading machine learning and AI experts. He has conducted extensive research into enterprise AI adoption strategies, emerging ML and AI platforms, and other enabling technologies.
Industry Analyst / Speaker / Researcher / Thought Leader
TWIML
Jorge Castañón hails from Mexico City and received his Ph.D. in Computational and Applied Mathematics from Rice University. He has a genuine passion for data science and machine learning applications of any kind. For 10+ years he is been developing data science and AI models as well as algorithms to solve numerical optimization and regularized inverse problems. At IBM, Jorge is the Lead Data Scientist of the Machine Learning Hub World Wide.
Lead Data Scientist, Machine Learning Hub World Wide
IBM
Meredith Mante is a Data Scientist with a focus on education. Within IBM's Data and AI Expert Labs, she develops curriculum in emerging areas like AutoAI. She has a bachelor's degree in Psychology from Princeton and a master's degree in Computer Science from NYU. She is passionate about sharing Data Science and AI with a broad community of learners from diverse backgrounds. Outside of work, she enjoys exploring the different neighborhoods, museums and parks in NYC.
Data Science and AI Curriculum Developer
IBM
Miguel Maldonado leads the Machine Learning curriculum development for IBM's Data & AI Expert Labs Learning. He has 10+ years of experience in Machine Learning, Data Science, and AI. He has worked in R&D developing data mining products and served in leadership roles as Director of Data Science and VP of Analytics across several industries including Retail, Banking, and Fintech. He holds a B.Sc. in Physics from Monterrey Tech and an M.S. in Analytics from NC State's Institute for Advanced Analytics. In his free time he enjoys hiking and bouldering. He is passionate about democratizing Data Science and actively participates in datathons, local meetups, and events that support NGOs.
Machine Learning Curriculum Lead
Appen/Figure Eight
Hemanth Manda is the director of offering management at IBM and is responsible for Cloud Pak for Data & Cloud Pak for Data System offerings. He has broad experience in the technology and software industry spanning a number of strategy and execution roles over the past 17 years. In his current role, Hemanth leads a cross-functional team to simplify and modernize Data & AI portfolio, a $6 B business. Among other things, he is responsible for rationalizing and streamlining Analytics offerings, modernizing Data & AI portfolio to support cloud native architectures and delivering new platform wide capabilities through a brand new IBM offering called “Cloud Pak for Data”.
Twitter: @hkmanda
Director, Offering Management, Cloud
Pak for Data
IBM
Karthikeyan Natesan Ramamurthy is a research staff member in IBM Research AI at the T. J. Watson Research Center. His broad research interests include understanding the geometry and topology of high-dimensional data and developing theory and methods for efficiently modeling the data. He has also been intrigued by the interplay between humans, machines, and data and the societal implications of machine learning. His papers have won best paper awards at the 2015 IEEE International Conference on Data Science and Advanced Analytics and the 2015 SIAM International Conference on Data Mining. He's an associate editor of Digital Signal Processing and a member of the IEEE. He holds a PhD in electrical engineering from Arizona State University.
Research Staff Member, IBM Research AI
IBM
Omid is a software engineer and data scientist at the IBM Developer Advocacy team with 5-years of experience of development. he has vast knowledge, from electronics to full-stack web dev, to data science and enjoys solving problems of all kinds. Moreover, he loves helping others find the right solutions, so if you have a problem, you know who to reach out to for pointers!
IBM Cognitive Applications Developer Advocate
IBM
Ryan Hagemann is the co-director of the IBM Policy Lab and a Technology Policy Executive on IBM's government and regulatory affairs team. He was previously a senior policy fellow at the International Center for Law & Economics. Before joining the International Center for Law & Economics, he was a senior fellow at the Niskanen Center, where he also served as the senior director for policy and director of technology policy. His policy expertise focuses on regulatory governance of emerging technologies, as well as a broader research portfolio that includes genetic modification and regenerative medicine, bioengineering and healthcare IT, artificial intelligence, autonomous vehicles, commercial drones, the Internet of Things, and other issues at the intersection of technology, regulation, and the digital economy. His work on “soft law” governance systems, autonomous vehicles, and commercial drones has been featured in numerous academic journals, and his research and comments have been cited by The New York Times, MIT Technology Review, and The Atlantic, among other outlets. He has been published in The Wall Street Journal, Wired, National Review, The Washington Examiner, U.S. News & World Report, The Hill, and elsewhere.
Ryan graduated from Boston University with a B.A. in international relations, foreign policy, and security studies and holds a Master of Public Policy in science and technology policy from George Mason University.
Co-Director,
IBM Policy Lab
IBM
Nick Pentreath is a principal engineer in IBM's Center for Open-source Data & AI Technology (CODAIT), where he works on machine learning. Previously, he cofounded Graphflow, a machine learning startup focused on recommendations. He has also worked at Goldman Sachs, Cognitive Match, and Mxit. He is a committer and PMC member of the Apache Spark project and author of "Machine Learning with Spark". Nick is passionate about combining commercial focus with machine learning and cutting-edge technology to build intelligent systems that learn from data to add business value.
Principal Engineer,
IBM's Center for Open-source Data & AI Technology (CODAIT)
IBM
Robert Chesebrough is currently an AI Solutions Architect/ Data science practitioner at IBM. His educational background is physics. His industry experience has been software development and application/performance engineering for fortune 100 companies and national laboratories for over three decades. He is a practicing data scientist, using machine learning/ deep learning for over five years while working for Intel and IBM. He specializes in helping clients create AI solutions from ensembles of multiple AI models and has a lot of experience in computer vision applications.
AI Solutions Architect/ Data Science Practitioner
IBM
Scott D'Angelo is a Cognitive Applications Developer Advocate with IBM. He will discuss monitoring a deployed AI model for performance, bias, and explainability on his talk.
IBM Cognitive Applications Developer Advocate
IBM
Luciano Resende is an Open Source AI Platform Architect with IBM's CODAIT group. He's a highly performant technical leader that embraces challenges and complex problems to drive breakthrough innovations. Luciano's expertise is in open source, and enterprise-grade AI platform technologies with about 20 years of experience successfully designing, building and delivering complex software in fortune 500 companies and open source. He has a strong background in open source big data platforms such as Apache Spark, and data science building blocks such as the Jupyter Notebook Stack and Apache Toree Scala kernel.
Open Source AI Platform Architect, CODAIT
IBM
As the General Manager of Technical Go To Market for IBM Cloud and Cognitive Software, Beth is responsible for building and optimizing our go-to-market strategy and execution across Technical Sales, IBM Garage, Digital Technical Engagement and Customer Success. Beth is focused on ensuring technical expertise and engagement is most optimal for the success of deploying IBM Cloud and Cognitive software to transform mission critical workloads.
Beth’s passion for technology took root in 1987 with her first role as a programmer in Cary, NC. Over the years, she has held several executive roles in IBM, including most recently, the General Manager of IBM Watson where she led the end to end business of engineering and delivery of the technology and the global ecosystem of partners and developers.
Beth holds a BS in Computer Science from North Carolina State University.
General Manager, IBM Cloud and Cognitive, Technical GTM
IBM
Evelyn Duesterwald is a Principal Research Staff Member and Manager of the AI Lifecycle Acceleration Group at IBM Research in Yorktown Heights, New York. Her team is currently working on operationalizing the AI lifecycle with a focus on continuous improvements for production deployed AI models. In prior roles at IBM, Evelyn earned IBM Research Accomplishment awards in the areas of AI Security, High Performance Computing, and Software Technologies. Holding MS and PhD degrees in Computer Science, she has been granted over 30 patents and has published on a broad range of topics in machine learning safety, parallel programming, compilers, dynamic and static program optimization, and software engineering. Evelyn is an ACM Distinguished Scientist.
Principal Research Staff Member and Manager, AI Lifecycle Acceleration
IBM
Rajesh Bordawekar is a Principal Research Staff Member at the IBM T. J. Watson Research Center. His current interest is applying AI techniques for data management workloads and associated software-hardware co-design. He works at the intersection of high-performance computing, analytics, and data management domains. He has published over 40 technical publications and have 36 issued patents. Rajesh has been exploring general purpose applications of GPUs since 2008, and recently, he has been investigating IBM Power Systems's NVLink capabilities could be used for accelerating key kernels in machine learning, data management, and deep learning workloads. He has presented a tutorial on "Analyzing Analytics" at multiple computer science conferences. A book based on this tutorial was published by the Morgan and Claypool Publishers in the Synthesis Lecture series on Computer Architecture in November 2015. Rajesh is a ACM Distinguished Scientist.
Principal Research Staff Member, IBM T. J. Watson Research Center
IBM
Gabriela de Queiroz is a Sr. Engineering & Data Science Manager at IBM where she manages and leads a team of developers working on Data & AI Open Source projects. Her team contributes to projects such as TensorFlow, PyTorch, Apache Arrow, Apache Spark, and several other open source projects. She works to democratize AI by building tools and launching new open source projects. She is passionate about making data science available to everybody and is actively involved with several organizations to foster an inclusive community.
She is the founder of AI Inclusive (ai-inclusive.org), a global organization that is helping increase the representation and participation of gender minorities in Artificial Intelligence. She is also the founder of R-Ladies (rladies.org), a worldwide organization for promoting diversity in the R community with more than 180 chapters in 50+ countries.
Twitter handle: @gdequeiroz
LinkedIn: https://www.linkedin.com/in/gabrieladequeiroz/
Sr. Engineering & Data Science Manager
IBM
Jalal Mahmud is a tech lead, manager and data science thought leader at IBM Watson. He led IBM Watson Sentiment product across multiple languages, drove innovations to several natural language understanding products including Sentiment, Entity, Keyword and Categories and accelerated AI innovations across Watson portfolio. He served as a technical lead for several Watson products such as personality insights, tone analyzer and emotion modeling. He has conducted research in the area of personality analysis, conversation analysis, dialogue strategy, response generation, emotion and tone analysis, emotion aware chatbot, personalized recommendation, consumption preference and brand preference. He has extensively published in top rated conferences and journals, received several best paper nominations, regularly serve on technical program committees/organizing commitees for major international conferences. Jalal is an IBM Master inventor and has filed more than 60 patents.
Tech Lead/Manager, Data Scientist - Thought Leader, Master Inventor and Acamedy of Technology Member
IBM
Saishruthi Swaminathan is a Developer Advocate for IBM's Center for Open-source Data & AI Technology (CODAIT). On her talk, she will discuss the following: Democratize AI - Deploy Deep Learning models as Microservices in minutes.
Developer Advocate - CODAIT
IBM
Meeta is a passionate, customer-obsessed product leader with a track record of strategizing, building and launching innovative products that solve real business problems.
As VP Product at Appen/Figure Eight she is building a machine learning data annotation platform focused on Computer Vision, Autonomous Vehicles, Conversational AI and NLP. She partners with the most innovative companies solving challenges of last mile relevance, bias, security, privacy et all to make AI work for real world business cases.
Prior to Figure Eight, Meeta held several product leadership roles in Cisco Systems, Tokbox/Telefonica and Computer Associates with a focus on AI, Chatbots, Voice/Video and Data Analytics. She has an MBA Degree from UC Davis and engineering degree from National Institute of Technology, India.
VP of Product
Appen
Dean Wampler (@deanwampler) is an expert in streaming data systems, focusing on applications of ML/AI. He is Head of Developer Relations at Anyscale.io, which is focused on distributed Python for ML/AI. Previously, he was an engineering VP at Lightbend, where he led the development of Lightbend CloudFlow, an integrated system for building and running streaming data applications with popular open source tools. Dean has written books for O'Reilly and contributed to several open source projects. He is a frequent conference speaker and tutorial teacher, and a co-organizer of several conferences and user groups in Chicago. Dean has a Ph.D. in Physics from the University of Washington.
Head of Developer Relations
AnyScale
John J. Thomas is a Distinguished Engineer and Director in IBM's Data & AI business. He currently leads IBM's Data Science Elite team comprised of data scientist who implement AI in the enterprise by applying Machine Learning, Deep Learning, and related techniques. John has 25+ years of experience in enterprise architecture, software development, competitive strategy and worldwide client engagements. A lifelong learner, his expertise spans a spectrum including Systems, Cloud, Analytics, Data Science, and AI.
Distinguished Engineer and Director, Data & AI
IBM
Mandy is a trusted advisor to executives from large organizations, working with them to develop their strategy and architecture relating to the governance, integration, and management of information. She is also driving IBM's strategic move to open metadata and governance through her leadership of the ODPi Egeria open source project (https://egeria.odpi.org). More information about Mandy’s work and publications can be found:
On LinkedIn: http://www.linkedin.com/pub/mandy-chessell/22/897/a49
At her blog: https://poimnotes.blog/
Distinguished Engineer, Master Inventor,
Fellow of the Royal Academy of Engineering
IBM
Avijit currently serves as Chief Analytics Officer in IBM FSS Industry. Previously, he served as the Chief Data Scientist of the IBM Data Science Elite team. He is an IBM Distinguished Engineer and a member of the IBM Academy of Technology. His work focuses on next generation analytics that leverage AI and machine learning to drive business impact. He holds a Ph.D. in Computer Science from the University of Southern California.
Chief Analytics Officer, IBM FSS Industry and Distinguished Engineer
IBM
Rania Khalaf is the Director of AI Platforms and Runtimes at IBM Research AI where she leads teams pushing the envelope in AI platforms to make creating AI models and applications easy, fast, and safe for data scientists and developers. Her multi-disciplinary teams tackle key problems at the intersection of core AI, distributed systems, human computer interaction and cloud computing. Their recent projects include the Deep Learning capabilities in IBM Watson Studio, core features in IBM OpenScale, AI Fairness 360, and IBM’s Learn and Play AI games. Prior to this role, Rania was Director of Cloud Platform, Programming Models and Runtimes where her teams’ work resulted in Apache OpenWhisk and IBM Cloud Functions, Swift@IBM, API Harmony and Amalgam8 (now Istio). Before that, she led efforts on Machine Learning in Business Process and Case Management and made foundational contributions to SOA and Web standards, earning awards including IBM’s Extraordinary Research Accomplishment. Rania serves on the Advisory Board of the Hariri Institute for Computing at Boston University. She has received several Outstanding Technical Innovation awards for major impact to the field of computer science and is a finalist for the 2019 MassTLC CTO of the Year award. She has lived in 8 countries, spent a summer in India teaching kids to code, and holds a PhD with honors from University of Stuttgart and a Masters and Bachelors in EECS from MIT.
Director of AI Platforms and Runtimes, IBM Research AI
IBM
Austin is a Data Scientist on the Technical Marketing and Evangelism team in San Francisco, California. As a recent graduate student of Florida State University, Austin is focused on the balance of bleeding-edge research produced by academia and the tools used in applied data science. His Masters thesis was on White Collar Crime using Time-aware Joint-Topic-Sentiment Analysis (TTS), and his areas of interests are NLP, applied data science, and Explainable AI. Austin currently resides in San Francisco, with his fiancé, dog, and two cats.
Data Scientist on Data and AI Technical Marketing Team
IBM
Gregg Willhoit is Chief Technologist for Rocket Software where he provides technical leadership for their IBM Z offerings. He has continually drove new innovation to IBM Z, from early days with the first direct to IBM Z ODBC data access, to delivering the first z/OS based data virtualization platform that is extending mission critical real-time data to the API economy, cognitive analytics, cloud and mobile. He is a pioneer of next generation mainframe solutions that help businesses exploit their investments in IBM Z technology to gain better insight, expand their customer engagement and drive new channels of revenue.
Chief Technologist
Rocket Software
Doug Dailey has over 20 years combined technical & management experience in the software industry with emphasis in customer service and offering management. He is currently part of IBM Analytics Offering Management team servicing our Hybrid Data Management portfolio over on-premises, private and public cloud.
Currently, Doug is investing a lot of time working to build out enhancements and capability for data virtualization using IBM federation and Queryplex technology, so that regardless of what platform you operate from, you have a common framework, technology and user experience. He is vested in connecting data siloes across an enterprise by using virtualization to bringing data to surface for exploration.
Doug also been diving into business continuity for IBM's HDM portfolio. In particular, he is working on a new replication offering that aims to deliver continuous availability so that the business can better optimize and operationalize the use of data. Replication is one of many technologies driving data integration that provides a strong value chain, including disaster recovery for critical Tier 1 data.
IBM Analytics Offering Management
IBM
Clement Delangue is the co-founder and CEO of Hugging Face, the leading NLP startup, based in NYC and Paris, that raised more than $20M from prominent investors. The company created Transformers, the fastest growing open-source library enabling thousands of companies to leverage natural language processing. Prior to Hugging Face, Clement started his machine learning journey at Moodstocks, a start up that built machine learning for computer vision and got acquired by Google.
Co-Founder & CEO
Hugging Face
Vincent Marois is an AI Resident at IBM and is currently working on concept learning. His research interests also gravitate around visual reasoning and transfer learning. Vincent graduated from a dual-degree curriculum in Computer Science & Engineering between Georgia Tech & INSA Lyon. He is interested in tech in general, with an emphasis on the intersection of open-source software & deep learning.
AI Resident for IBM Research
IBM