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Data Science [clear filter]
Saturday, October 20


When Classical Statistics Meet Modern Data Science
Modern applications have generated many data sets of complex nature, such as high dimensionality, heterogeneity and unknown structure of interest. In this talk, I will discuss a few ideas on extending traditional statistical methods such as the principal component analysis, expectation maximization, and mixture model, to accommodate challenges in those applications. Theoretical properties, numerical results, and applications in biomedical studies will be discussed.

avatar for Weining Shen

Weining Shen

Professor, UC Irvine
Weining Shen is assistant professor of Statistics at UC Irvine. He received his PhD from North Carolina State University in 2013, and his thesis won the Leonard J. Savage Dissertation Award. In 2013-2015, he was a postdoctoral fellow in Department of Biostatistics, M.D. Anderson Cancer... Read More →

Saturday October 20, 2018 10:00am - 10:30am
Ballroom # 409


How to Use Data Analytics to “Win the Race for Eyeballs” in the Eye Candy Economy
Today we live in an “Eye Candy Economy”, everyone is craving for delightful content to satisfy their Eyes and Brain. The Digital Media Companies think that “Content is King” and are in a multi-billion dollar race to create more content. But Consumer is the “King Kong” who decides which content is viral and which content is dud. This has created a complex business problem of identifying topics and themes which will be viral and need to produce viral content. Advance Analytics and AI can be used to solve this complex problem by utilizing the Content Data from social media and Social Interaction and other data of the users and content to predict the resonating content that will have a large audience. This talk will help Digital Media Companies to “Win the race for Eyeballs and Revenue”.

avatar for Arif Ansari

Arif Ansari

Professor, University of Southern California
Arif Ansari is a Professor in the Data Sciences and Operations Department at Marshall School of Business at University of Southern California, Los Angeles. He is the CEO of Intuition Intelligence Inc. developing Creative Analytics Solution for the Digital Media. He is an expert in... Read More →

Saturday October 20, 2018 10:30am - 11:00am
Ballroom # 409


Conversational AI for Business Intelligence: Ask Interesting Questions
It often takes a long time for business users in enterprises to get the right data and insights, even if the data is well organized and structured. This is because they may not know where the data is located, how it is modeled, and how to frame the right queries for their needs. As a result, traditionally, access to analytics content from BI and analytics and data science platforms has mostly been limited to power users, business analytics and specialist data scientists with varying degrees of analytical and technical skills. This is where conversational analytics comes in. Conversational chatbots for analytics allows any user to ask voice or text questions of their data and receive back a natural language and potentially, a visual analysis of the most statistically relevant and actionable insight for that user. In this talk I shall describe some of the key AI technologies needed to deploy conversational analytics including natural-language processing (NLP), natural-language generation/narration, chatbots and AI/augmented analytics. I shall also describe some case studies where expanding access to insights from analytics to all employees helped driving strong business impact.

avatar for Anand Ranganathan

Anand Ranganathan

Chief AI Officer, Unscrambi
Anand Ranganathan is a co-founder and Chief AI Officer at Unscrambl, Inc. He is a data scientist, AI developer, Big Data developer, architect and researcher rolled into one person. He is leading Unscrambl’s product development in several cutting-edge areas, including context-aware... Read More →

Saturday October 20, 2018 11:00am - 11:30am
Ballroom # 409


Application of Random Forests for Educational Video Games
Prediction and interpretation with trees and random forests for learning behavior in educational video games. How extracting these insights can help improve adaptative learning systems.

avatar for Marie H Roy

Marie H Roy

Data Scientist, Age of Learning
I am a data scientist, soon to be PhD, specialized in predictive modeling and ensemble methods. I work in a learning sciences team in an EdTech company with a goal to leverage machine learning for educational technology.

Saturday October 20, 2018 11:30am - 12:00pm
Ballroom # 409


The Fashionable Misunderstandings of Data Science in the Industry
Along the years, I have realized that many business leaders do not understand what Data Science is or why they would need experts of the field in their organization. Data Scientists even get too often confused with Data Analysts, Business Intelligence Analysts or Data Engineers.

But Data Science, Big Data, Machine Learning or AI are fashionable concepts so companies need to hire Data Scientist, right? So how do we recruit those specialists? Sometime the job descriptions list a set of requirements that demand 3 PhDs to achieve, sometimes you just need to know Excel to apply or sometime the job description is actually describing a Data Engineer or BI analyst. Few years ago, every Data Scientists had to know Hadoop or NoSQL for some reason. Few years later, it was about knowing Spark. Today it is about knowing everything in Deep Learning or/and being a Kaggle master.

When the companies finally get hold of a new Data Science recruit with the 3 PhDs, the question remains: what should they do with them? Too many times you will find Data Scientists ending up doing dashboard reporting instead of looking for ML driven business solutions. Too many times the companies simply do not have the engineering infrastructure around the data to leverage any data science solution. Too many times, the Data Scientists are actually discouraged to explore new ideas because of the upper management’s fear around the statistical uncertainty intrinsic to the field. Let’s discuss about those misunderstandings surrounding Data Science

avatar for Damien Benveniste

Damien Benveniste

Lead Data Scientist, Rackspace
Damien is currently a Lead Data Scientist at Rackspace, one of the leading companies in managed cloud computing. He has worked in diverse industries such as a market place for virtual items (Opskins), e-commerce (Bluestem Brands), healthcare (Transfuse Solutions) or data storage (EMC... Read More →

Saturday October 20, 2018 11:30am - 12:00pm
Ballroom # 403B


Data Science in Academia vs. Indusry. What is Right for Me?
During the last few years, data science has brought about many changes to how we live and work. Students interested in careers in data science often ask "do I need a graduate degree to work as a data scientist?" Obviously, while there is no one-size-fits-all answer to that question, there are some important questions to consider when making career choices in data science. I compare and contrast academia vs industry as career options after bachelors degree or masters degree based on my personal experience in research and industry.

avatar for Sang-Yun Oh

Sang-Yun Oh

Professor, UC Santa Barbara
I worked for a number of years between my bachelor’s degree in physics at UC Berkeley, and my Ph.D. in computational and mathematical engineering at Stanford. My work experience span research and industry as medical imaging research engineer at Lawrence Berkeley National Lab, director... Read More →

Saturday October 20, 2018 1:00pm - 1:30pm
Ballroom # 403B


Latent Dirichlet Allocation on Player Session Behavior in Gaming
As data scientists at Riot Games, our goal is to focus on providing the best player experience possible. Understanding how players play individual sessions and how their styles evolve over time is key to evaluating our products and helps make decisions for future designs. In this talk, I will present how we use Latent Dirichlet Allocation (LDA), a three-level hierarchical Bayesian model, to identify major session topics in League of Legends and how we construct a player segmentation with session clusters.

avatar for Ran Cao

Ran Cao

Data Scientist, Riot Games
Ran Cao is a Data Scientist for League of Legends at Riot Games. League of Legends is one of the most-played games in the world, with frequent updates to expand the possibilities for players. Her data science background has focused on Bayesian modeling across genetics, public policy... Read More →

Saturday October 20, 2018 1:00pm - 1:30pm
Ballroom # 409


Marketing Like a Musician
I saw that the IDEAS conference is coming to L.A. in October. Since L.A. is my home, I would love to come and speak. I do talks about how to think like musicians when it comes to problem solving, marketing, engaging audiences, etc. I’d also be happy to share how I grew a Facebook audience for my business, PianoCub, to over 44K followers.
Here’s some footage of a recent talk of mine: https://www.youtube.com/watch?v=p7NiUDs9gx0

avatar for David Brown

David Brown

Entrepreneur/Musician, PianoCub
David Asher Brown is a rare voice among young, American composers. The Metropolitan Opera’s William Lewis praised him as, “one of the most brilliant music makers it has been my pleasure to serve”. His composition craft innovatively draws on the sounds and techniques of everything... Read More →

Saturday October 20, 2018 1:30pm - 2:00pm
Ballroom # 409


Location Intelligence Goes Big in Digital Marketing
The dawn of digital marketing began with search ads, then proceeded to social ads and now has evolved to include geospatial ads. Location Intelligence is the discipline that analyzes the petabytes of location data generated daily by mobile devices to extract meaningful and actionable consumer insights.

Predicting customer intent is an age-old problem. With more than 80% of sales still occurring in brick and mortar stores, it is important to understand the customer intent. Currently, many marketers such as Facebook and Snapchat are using location data to calculate ROI and lift of in-store visits for their ads. In this session, I will discuss ways to advance our understanding of store visitors using location intelligence: who they are and what they do in the physical world.

avatar for Annie Flippo

Annie Flippo

Director of Data Science, inMarket
Annie Flippo works as the Head of Data Science & Analytics at Thinknear by Telenav, a GPS navigation software, connected car and mobile advertising company. She is a data science expert focusing on the application of machine learning techniques to extract insights in the areas of... Read More →

Saturday October 20, 2018 3:00pm - 3:30pm
Ballroom # 409


Data Science That Drives Business Outcomes: A Case in the Practice Growth Space
As a discipline, Data Science continues to experience a boom in growth. Not too long ago, use of data and models were mostly confined to Finance departments, but they've now become critical in optimizing across all company functions, with ever-growing use cases in Product, Marketing, Operations, and a multitude of others. With such growth, many companies have gotten caught up in the hype, doing data science just for the sake of doing it, and without a clear plan on how it will have an impact on the business and on the bottom line. To get value, Data Science teams must work with business stakeholders to build data products that are embedded into company functions and business goals. Learn how PatientPop, the leader in the Practice Growth platform space, is undertaking this challenge in a way that serves Doctors, improves experience of their patients, and amplifies our business. In this talk, I'll share our vision for a combined data science and business strategy, and show how our business drives our data science efforts, which in turn improve existing functions and enable entirely new ones.

avatar for Charalampos Papadimitriou

Charalampos Papadimitriou

Lead Data Scientist, PatientPop
Charalampos founded and is the Lead Data Scientist of the data science team at PatientPop, where he works on data science projects, programs, and process. Previously, he worked at DataScience.com where he lead data science consulting engagements with client companies big and small... Read More →

Saturday October 20, 2018 4:00pm - 4:30pm
Ballroom # 403B


Choosing the Right Cloud, a Machine Learning Approach
As cloud services have grown in maturity and offerings, the differentiations between them has shrunk. For example, many CSPs now provide capabilities to host and run Jupyter Notebooks for Data Science workloads, but what makes one different than the other? As a data scientist, I wanted to see if it would be possible to classify respective clouds by using machine learning. An effect dataset and model could provide insights to the differences in userbases among clouds, and could help those new to developing in cloud environments a resource to choose a cloud in which other users having similar coding styles, interests, and needs

avatar for Nick Acosta

Nick Acosta

Developer Advocate, IBM
Before becoming a Developer Advocate at IBM, Nick studied computer science at Purdue University and the University of Southern California, and was a high performance computing consultant for Hewlett-Packard in Grenoble, France. He now specializes in machine learning and interacting... Read More →

Saturday October 20, 2018 4:30pm - 5:00pm
Ballroom # 403B