Machine Learning and AI Applications in Media and Entertainment

NEW YORK, JUNE 13 2019

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Sponsored by

Early Bird

Group

All sessions
Regular seating
Food included
Opening reception





 Early Bird

Individual

All sessions
Regular seating
Food included
Opening reception





Early Bird

Group

All sessions
Regular seating
Food included
Opening reception





 Early Bird

Individual

All sessions
Regular seating
Food included
Opening reception





The Data Science Salon is a destination conference which brings together specialists face-to-face to educate each other, illuminate best practices, and innovate new solutions in a casual atmosphere with food, drinks, and entertainment.

Data Science Salon unites the brightest leaders in the media and entertainment in New York data science fields. We gather to educate each other, illuminate best practices, and innovate new solutions.

DSS NY is the only industry conference that brings together specialists in media and entertainment data science field to educate each other, illuminate best practices, and innovate new solutions in a casual atmosphere. Learn from practitioners, technical experts and executives how to solve real-world problems by harnessing disruptions in data, artificial intelligence, machine learning, and cutting-edge technologies.

Data Science Salon NY provides a common framework for thinking about what Machine Learning and AI means to the media and entertainment industry. You will see a mix of use-cases, technical talks and workshops, you will walk away with actionable insights from those working on the frontlines of Machine Learning in the enterprise.

Every major application of Machine Learning in media and entertainment will be covered.

Enhancing the Viewer Experience with Machine Learning & AI

Content Personalization and Monetization

Personalization at Scale with AI

Cloud Automation and Machine Learning

Audience Targeting and Segmentation (across platforms)

Data and AI for emerging platforms

Data Governance

and More!

media execs and data science practitioners

Director and above

VP of Product Strategy &
Data Science,

Ayan Bhattacharya

Advanced Analystics Specialst Leader,

Deloitte Consulting

Marc Fridson

Director of Data Science,
Sony Music

Lauren Lombardo

Senior Data Scientist,

Joshua Miller

Director, Data Analytics

Samba TV

Anne Bauer

Lead Data Scientist

New York Times

VP of Product Strategy & Data Science,

Christopher Whitely

Senior Director, Applied Analytics,

Gilad Lotan

VP, Head of Data Science,

Anna Coenen

Data Scientist,
New York Times

Justin Hendrix

Executive Director,

NYC Media Lab

Lauren Lombardo

Senior Data Scientist,

Anna Nicanorova

Annalect Labs

Harini Kannan

Data Scientist,

Marc Fridson

Director of Data Science,
Sony Music

Ayan Bhattacharya

Advanced Analystics Specialst Leader,

Deloitte Consulting

Sergey Fogelson

Vice President,

Data Science & Modelling,

Viacom

Anne Bauer

Lead Data Scientist,

New York Times

Paul Barrett

Managing Director,
Accenture Applied Intelligence

Joshua Miller

Director, Data Analytics,

Samba TV

“The Data Science Salon series is the most important new conversation happening in the industry right now.”

Eduardo Arino de la Rubia

Instagram

“Their conferences are smaller, more intimate, with lots of opportunities for workshops and networking, which helps fill that need in the data science community to get together from time to time.”
Roger Magoulas

O’Reilly Media

“I think it’s easy to get preoccupied with the project of the day. What I appreciate about the Data Science Salon is that it’s a conference I actually want to go to – it’s fun, you learn some great things, you meet some great people, and at the end of the day you feel energized rather than drained. It’s taken me out of my silo and put me in the community. I think it’s great.”
Jack Parmer

Plotly

“Both Viacom and Data Science Salon are known for being at the forefront of their fields. We’re proud to provide a platform for DSS, and to host the most relevant conversations on data science in media and entertainment.”
Das Dasgupta

Viacom

Jeremy and Anna – FormulatedBy

Sergey Fogelson

Vice President, Data Science and Modelling, Viacom

At Viacom we want to know who our viewers are and what content they’ve engaged with, in order to target them and similar viewers so that we can ultimately increase our total viewership. For this to happen, we need to gather our customer data and enrich it so we know our customers as well as the walled-garden social media platforms know them. To this end, we’ve built our unique audience platform (UAP), which provides a single consolidated view of our customers and can be used for marketing, personalization, programming, and analytics use cases. In this talk, I will describe the data engineering challenges around building out the UAP in house and at a reasonable cost, while covering some of the key components of platform. Finally, I’ll highlight some example use-cases of this next-generation audience-unification architecture.

About the speaker

Sergey Fogelson enjoys applying his quantitative skills to large-scale data intensive problems and mentoring junior colleagues. In his current role, he manages a team of data scientists responsible for measuring the quality of the assets available at a large media corporation. He also enjoys sharing and communicating what knowledge he has. To that end, he teaches data science courses, both in-person and online, at several bootcamps/hacker academies. In the past, Sergey built custom large scale data products for clients in the financial industry, led a team that developed data products at a small cybersecurity startup, and worked at a digital advertising startup. Sergey obtained his Ph.D. in Cognitive Neuroscience from Dartmouth.

Lauren Lombardo

Senior Data ScientistNielsen

Products underpinned by traditional statistical methods, big data, and artificial intelligence increasingly provide new and unique insight into the rapidly growing media landscape. How can you make sure that your product will have the impact that you expect it to? What factors do you need to consider when developing a product to ensure that the tool is understood by the market and used appropriately? To what extent is this the concern of a data scientist? This talk will discuss how these questions apply to those hoping to deliver data-oriented insight to the media and entertainment industry.

 About the speaker

Lauren currently works as a Senior Data Scientist for Nielsen Media. In this capacity, she focuses on the design, delivery, and development of measurement solutions for Nielsen’s digital clients. Lauren started her Nielsen career on the International Media Data Science team where she supported the expansion of Nielsen’s global measurement footprint. Lauren has also worked on Nielsen’s Big Data team and as a client service associate supporting digital clients.

A California native, Lauren moved to New York City two years ago and is still adjusting to the unfortunate reality of winter. Lauren has trained academically in economics and public policy and enjoys reading, international travel, and listening to podcasts.

Joshua Miller

Director, Data Analytics, Samba TV

To understand the effect of an advertisement, measuring a conversion rate alone does not paint a complete picture – we want to measure the incremental lift an advertisement has on an audience after taking into account the targeted audience’s propensity to convert without being exposed to the advertisement. In digital advertising, this effect is quantified by selecting some of the people that meet the targeting criteria (location, demographics) that would have been exposed to the digital ad and instead serving them a “placebo ad,” placing them into a control group. In general, most broadcast TV commercials are an all-or-nothing scenario, i.e., everyone watching the program gets the same commercial. Samba TV’s proprietary Synthetic Control Group (SCG) process allows us to overcome this hurdle by deriving a control group using a household’s TV viewership data. We design the control group to be, based on our data, the target group that was likely to see a specific ad campaign spot but that did not. We assign these households “synthetic” television exposures so that they can be compared to the same attribution window used to measure the ad campaign, allowing an apples-to-apples comparison. Comparing the exposed group’s conversion rate to the conversion rate of this control group then reveals a measurable, attributable lift.

About the speaker

Joshua Miller is the Director of Data Analytics at Samba TV in San Francisco. He earned his Ph.D. in astrophysics performing multiwavelength studies of transient pulsars at West Virginia University. After teaching Physics and Astronomy courses at Penn State, Josh accepted an Insight Data Science fellowship and packed his bags for Silicon Valley to begin applying his love of solving challenging problems to business applications. Josh joined the then-small TV data startup Samba TV as their first data scientist in 2015 where he has been pivotal in using data-driven insights to help drive their business decisions. He now leads and mentors international teams of data analysts helping them each discover and develop their own inner scientist.

Speaker TBA

Viacom

Marc Fridson

Director of Data Science, Sony Music

Amy Yu – VP Data Science Products, Viacom

Amy Yu is VP of Product Strategy & Data Science in the Audience Science team at Viacom, where she leads the design and development of visual data science platforms that enable data-driven decisions across Viacom’s portfolio brands. Amy holds a M.S. in Media Arts and Sciences from MIT Media Lab and graduated from the Jerome Fisher Program in Management and Technology at the University of Pennsylvania.

Christopher Whitely – Senior Director, Applied Analytics, Comcast

Christopher Whitely is Senior Director of Data Science and Research at Comcast / Freewheel, working on deep-dive viewership modeling efforts and data-driven advertising campaigns. Previously, as part of Comcast EBI, he led applied analysis projects and developed business intelligence tools to identify drivers of content performance and enhance networks’ programming strategies. Chris also led cross-platform research efforts at the Weather Channel and ad sales research at the national cable networks of NBCU. He holds an MBA from the University of Michigan Ross School of Business and a BA from Middlebury College.

Anne Bauer – Lead Data Scientist , New York Times

Anne is a lead data scientist at The New York Times, where she has built models and data products to interpret and act on the company’s data with a variety of groups including marketing, print circulation, and the newsroom. She currently leads the NYT’s Algorithmic Recommendations team. Before becoming a data scientist she was an astrophysics and cosmology postdoc in Barcelona and Munich, received her Ph.D. in physics from Yale, and her B.A. in physics and computer science from Amherst College.

Gilad Lotan – VP, Head of Data Science, Buzzfeed

Gilad is the Head of Data Science and Analytics at BuzzFeed where he leads a team that’s tasked with building state of the art analytics and data products to support entertainment, news, business and tech. Previously Gilad led Data Science at betaworks, and built data products at Microsoft. Gilad’s work has been covered across a wide range of academic journals and publications, most recently focused on propaganda and bias within algorithmic ranking systems.

Anna Coenen

Data Scientist, New York Times

Algorithmic curating at the Times brings many unique challenges. We want our recommendations to feel personal and relevant, but not creepy. We want articles to be timely, yet also showcase older pieces that our readers still enjoy. We want to increase engagement, but without sacrificing editorial judgment. This talk describes how we achieved these goals through a combination of Machine Learning, experimentation, and diligent editorial curation.

About the speaker

Anna is a Data Scientist at The New York Times. She works on identifying drivers of reader engagement and builds recommendation models that serve personalized article suggestions to users of the website. Prior to working at the Times, she received her PhD in Cognitive Psychology at New York University, where she used behavioral experiments and computational models to understand how people learn, gather information, and make decisions. She has also worked as a research analyst conducting psychological experiments to help businesses understand customer decisions.

Ayan Bhattacharya

Advanced Analystics Specialst Leader, Deloitte Consulting

Justin Hendrix

Executive Director, NYC Media Lab

Synthetic Media, or content that has been algorithmically created or modified with AI and deep learning, is saturating the digital landscape. From chatbots to voice assistants and deep fakes, many fear the blurring of the line between what is real and what is synthesized, of the spread of hoaxes and lies. But these technologies will also create new means for expression, and new tools to create art and engage people. In this talk, I’ll discuss the opportunities and challenges for a new form of media at the intersection of computer generated images, video, and voice, sourcing examples from new university research, R&D, and innovation in the space. What balance will the media industry need to strike when working with AI generated content? How is Synthetic Media changing the production, consumption, and monetization of media?

About the speaker

Justin Hendrix is Executive Director of NYC Media Lab, a public-private partnership between the City’s industry and its universities to drive emerging media and technology innovation and entrepreneurship, and the founding Executive Director of RLab, a new 16,500 square foot facility including co-working labs, classrooms, studios, and more in the Brooklyn Navy Yard that is New York’s City’s home for VR, AR and spatial computing. RLab is the nation’s first city-funded center for research, entrepreneurship and education in virtual and augmented-reality, spatial computing and other emerging media technologies. Previously he was Vice President, Business Development & Innovation for The Economist. He holds a BA from the College of William & Mary and an MSc in Technology Commercialization from the McCombs School of Business, University of Texas at Austin.

Anna Nicanorova – Director, Annalect Labs

Anna Nicanorova is Director of Annalect Labs – space for experimentation and rapid software development within Annalect. The objective of the lab to build marketing software and algorithms based on the latest developments in tech as well as needs of Omnicom agencies. Anna is Co–Founder of Books+Whiskey meetup and volunteer coding teacher with ScriptEd (Science Skill Center High School). She holds an MBA from the University of Pennsylvania – The Wharton School and BA from Hogeschool van Utrecht. In her free time, she can be found art-hunting in museums or climbing very tall mountains.

Harini Kannan – Data Scientist, Capsule8

Harini Kannan is a data scientist at cybersecurity company Capsule8, where she applies her skills in statistics, visualization, machine learning and deep learning to threat detection and computer security problems. Before joining Capsule8, Harini obtained her M.S in Business Statistics from University of Texas, Arlington.

Lauren Lombardo – Senior Data Scientist, Nielsen

Formulatedby

media partners

Early Bird

Group

All sessions
Regular seating
Food included
Opening reception





 Early Bird

Individual

All sessions
Regular seating
Food included
Opening reception





Early Bird

Group

All sessions
Regular seating
Food included
Opening reception





 Early Bird

Individual

All sessions
Regular seating
Food included
Opening reception





attendees from

And many more!

DATE AND TIME

June 13, 2019 | 8:00 AM – 8:00 PM EDT

LOCATION

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