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Sunday, October 22
 

8:00am PDT

Registration
Sunday October 22, 2017 8:00am - 8:30am PDT
TBA

8:30am PDT

Welcoming Speech
Speakers
avatar for Jason Geng

Jason Geng

CEO, Wise IOT Solutions
Guest Lecturer at University of Southern California August 2016 - Present Guest Lecturer for Database and Data Science Committee Chair May 2016 - Present Working as committee chair in NPO board and was organizer for "SoCal Data Science Conference 2016"; Organizer of "Dallas Data Science... Read More →


Sunday October 22, 2017 8:30am - 8:40am PDT
Room D Room D

8:40am PDT

Keynote-Data-Driven AI for Entertainment and Healthcare
Speakers
avatar for Demetri Terzopoulos

Demetri Terzopoulos

FRS, FACM, FIEEE; DISTINGUISHED PROFESSOR OF COMPUTER SCIENCE, UCLA; CO-FOUNDER & CHIEF SCIENTIST, VOXELCLOUD INC.
Demetri Terzopoulos is a Chancellor's Professor of Computer Science at the University of California, Los Angeles, where he holds the rank of Distinguished Professor and directs the UCLA Computer Graphics & Vision Laboratory. He is also Co-Founder and Chief Scientist of VoxelCloud... Read More →


Sunday October 22, 2017 8:40am - 9:00am PDT
Room D Room D

9:00am PDT

Keynote: How to Turn an AI Technology into an AI Business
Moderators
avatar for Steve Schoch

Steve Schoch

Former CEO, Miramax Films
Schoch served as CEO of Miramax Films for five years through the end of 2016, and concurrently served as CFO, a position he held from 2010. He led the building of a new studio company from the Miramax assets purchased from The Walt DisneyCompany in late 2010. During this period of... Read More →

Speakers
avatar for Xavier Kochhar

Xavier Kochhar

Founder and CEO, The Video Genome Project (Hulu)
Xavier Kochhar is the Founder and CEO of The VideoGenome Project® (The VGP), a company whose mission is deeply rooted in the belief that the world's data should be accessible for all to use. The VGP is the largest, broadest, and most granular structured database of video content... Read More →


Sunday October 22, 2017 9:00am - 9:40am PDT
Room D Room D

9:45am PDT

Keynote: Artificial Intelligence: Hype, Reality, Vision.
There has been tremendous progress in AI over the past few years. For example, speech recognition in devices like Siri and Alexa, language translation, image categorization, and semi-autonomous driving are now performing at levels that engineers could only dream about just 5 years ago.

Almost all of these improvements are driven by Machine Learning, Big Data, and Massive Computing. These rapid advances have spawned an AI investment mania driven by often quite unrealistic hype and projections – including such claims as fully autonomous driving in 2 years, or 50% unemployment within 10 years. Such claims, plus other misconceptions, are fostering a cadre of ‘prophets of doom’ with warnings of demons and WW3. 

A more sober view, one held by most computer scientists actually working on AI, is that today’s ‘AI’ technologies actually possess very little intelligence – they are very narrow and quite brittle. We seem to be a long way from achieving, for example, the navigational or learning ability of a bee. Never mind the conversational skills of a 4-year old. 

Recently, an increasing number of prominent researchers have begun to publicly acknowledge some core problems of current approaches – namely, the inability of systems to learn incrementally and autonomously, and their lack of generality, transfer learning, and reasoning ability. 

I order to break through this intelligence bottleneck, another approach is starting to gain momentum: ‘Cognitive Architectures’. This paradigm is closely related to what has been called the ‘Third Wave of AI’ – computers that can think, learn, and reason like humans.

Speakers
avatar for Peter Voss

Peter Voss

Founder & CEO, AGI Innovations Inc.
Peter Voss' careers include being an entrepreneur, engineer, and scientist. His experience includes growing a computer solutions company from zero to a 400-person IPO. For the past 15 years, his focus has been on developing AGI (artificial general intelligence). In 2009 Peter founded... Read More →


Sunday October 22, 2017 9:45am - 10:15am PDT
Room D Room D

9:45am PDT

Implementing Artificial Intelligence with Big Data
Human beings have been doing research on Artificial Intelligence for decades, and the algorithms that are commonly used today to implement AI products are not new. It is with the large volume of data available today, along with the computing power, we are finally able to implement the methodology to achieve more accurate results, and build AI products. This talk will go over the basics on machine learning and deep learning for the purpose of AI, and how Big Data can improve the performance.

Speakers
avatar for Raymond Fu

Raymond Fu

Big Data Architect, Trace3
Raymond Fu is a seasoned IT professional specializing in big data, artificial intelligence, and enterprise architecture. As an innovative technology builder balanced by business acumen, his ten-year corporate career with Bank of America was highlighted by leading many data integrations... Read More →


Sunday October 22, 2017 9:45am - 10:15am PDT
Room C Room C

9:45am PDT

Everything You Wish You Knew About Search
Whether it is to browse the web, to shop the latest trends or to retrieve relevant documents, search engines make our lives easier, and we use them on a daily basis, both in our personal and professional lives. However, no matter how effortless they appear, their creation is anything but easy. In reality, large corporations employ tens and even sometimes hundreds of engineers, product managers and data scientists to support the development, improvement and maintenance of the entire system. In this talk, I will explain how search differs across industries and how enterprise search contrasts with retail search or web search.  I will describe some of the most popular ranking algorithms and give some tips about how to choose the one that is the most appropriate for your application. I will also dig into the different peripheral algorithms and pieces that come into play, emphasizing the main reasons why creating a comprehensive, high-performance engine is ultimately a very challenging task.

Speakers
avatar for Jennifer Prendki

Jennifer Prendki

Head of Data Science, Atlassian
Jennifer Prendki is the Head of Data Science at Atlassian, where she uses Big Data and Machine Learning to create products that help other companies change the world. Her original area of expertise is particle physics, a field aiming at measuring subtle signals through the analysis... Read More →


Sunday October 22, 2017 9:45am - 10:15am PDT
Room E Room E

9:45am PDT

How Does Big Data Assessment Stimulate the Growth of Consumer Finance?
In the present global financial market, consumer finance is in the middle of a whirlwind, bringing many golden opportunities. Large in scale, the consumer finance market has enormous potential, especially in developing countries like China. The Chinese consumer finance market has been growing rapidly since 2008, with an estimated current size of 6 trillion RMB. The prediction has it that the consumption loan in China may surpass 12 trillion RMB by 2020, if growing at an estimated 20% annual rate.
Compared with the U.S. consumer finance that was incepted after World War II, the Chinese consumer finance is still relatively new and facing many challenges despite its large scale and great market potential. China, on the one hand, has a unique compliance system. On the other hand, China does not yet have a well-established credit service system. Therefore, further developing the individual credit system and realizing big data credit assessment is essential to stimulate the growth of consumer finance. How so?
1. Not only dramatically reduces labor costs, but also perfects risk identification, judgment, evaluation, and management, therefore accelerating the credit audit process.
2. Help consumer finance platforms control bad debt and overdue rates, therefore lowering potential risks.
3. Provides accurate credit evaluation, it also exploits precise scenes and unique markets for different groups of individuals by exploring their consumer habits and needs.

Speakers
avatar for Lingyun Gu

Lingyun Gu

Founder & CEO, IceKredit, Inc.
Dr. Gu received his Ph.D. in Computer Science from Carnegie Mellon University. He later joined ZestFinance in Los Angeles as one of the Founding members and the head of the modeling team. After ZestFinance, Gu worked for Kabbage as the Chief Scientist. He then joined Turbo Financial... Read More →


Sunday October 22, 2017 9:45am - 10:15am PDT
Room G Room G

9:45am PDT

Using AI to Tackle the Future of Health Care Data
Adoption of new Patient Centric software in the Health Care industry means huge new data sets will soon be available. These corpora include enormous amounts of unstructured text, detailed phenotype expression data, bio-bank tissue data and complicated interactions of pharmaceuticals. Though welcome, these data require we take large steps forward in our ability to process, analyze, model and predict patient health.We will discuss:
* Key insights from the fight against Cancer using AI
* The role of Natural Language Processing in the new paradigm
* How to adapt traditional AI & ML methods to current challenges
* The use of graph structures to simplify problems
* The role of High-Performance Computing and how analysts can participate
* How software packages simultaneously liberate and constrain the field of Data Science

Speakers
avatar for Brian Dolan

Brian Dolan

Chief Scientist, Co-Founder, Deep 6 AI
Brian Dolan is well-known in the data community as a leading mathematician, data scientist, and analyst with more than 20 years of hands-on experience, including high-profile work in the US Intelligence Community, Northern Trust Bank, and Havas Media, Brian also headed up data scientist... Read More →


Sunday October 22, 2017 9:45am - 10:15am PDT
Room B Room B

10:20am PDT

Keynote: Battling Skynet: The Role of Humanity in Artificial Intelligence
The Artificial Intelligence revolution is simultaneously exhilarating and frightening. Human beings will be able to achieve unprecedented advances in every industry, from medicine to manufacturing. However, we fear to become irrelevant as robots are able to perform our tasks better than us. How can humanity survive in a world of robots?

Speakers
avatar for Rumman Chowdhury

Rumman Chowdhury

Senior Manager, Accenture AI
Dr. Chowdhury's passion lies at the intersection of artificial intelligence and humanity. She comes to data science and Artificial Intelligence from a quantitative social science background. At Accenture AI, she works on responsible implementations of enterprise AI. She has been featured... Read More →


Sunday October 22, 2017 10:20am - 10:50am PDT
Room D Room D

10:20am PDT

Deep Learning in Spark with BigDL
As Deep Learning architectures grow in popularity, companies are beginning to use it with their existing data to gain deeper insights. BigDL enables companies with existing Spark clusters to run Deep Learning jobs where the data sits. You no longer have to export your data outside of Spark. Real-time deep learning pipelines are now possible too! In this talk, Dave will explore the common Neural Network models used by companies who already have Hadoop or Spark clusters.

Speakers
avatar for Dave Nielsen

Dave Nielsen

Sr. Developer Advocate - Trust Analytics Platform, Intel Corporation
As a Technical Program Manager in the Big Data Technologies group at Intel, Dave oversees partnerships and programs that help customers find out about and get started with Deep Learning in Spark. Prior to Intel, Dave ran Developer Relations at companies like Redis Labs, Strikeiron... Read More →


Sunday October 22, 2017 10:20am - 10:50am PDT
Room C Room C

10:20am PDT

Machine Learning & Data Science in the Age of the GPU: Smarter, Faster, Better
Companies are exploring data in ways we once only associated with science fiction films. Data scientists and analysts live in a world with access to a plethora of tools to analyze and visualize this data - but considering the vast amount of data businesses collect and the machine learning limitations of CPU compute capacity, end users are forced to design their structures and systems with limitations. 

Until now. Graphic Processing Units (GPUs) have stepped in to massively advance and parallel machine learning, data science and analytics for companies both small and large. Equipped with the ability to render graphics instantly, GPUs are computing, exploring and visualizing billions of rows of data in milliseconds - all on one chip. 

As a result, the ability to analyze data and run queries in real-time is giving machine learning algorithms the tools to become even smarter and faster, and is giving companies in industries like financial services, government, retail, adtech and telecommunications the types of tools to compete more effectively, respond more rapidly and tackle challenges they previously considered too hard for their legacy compute platforms. 
In this talk, Todd Mostak will explore the capabilities and applications of GPUs to advance and accelerate machine learning and data visualization. From design to interactivity to user experience, Todd will reveal how this technology is producing faster, measurable and more significant outcomes for businesses today.

Speakers
avatar for Aaron Williams

Aaron Williams

VP, Global Community at MapD
Aaron is responsible for MapD’s developer, user and open source communities. He comes to MapD with more than two decades of previous success building ecosystems around some of software’s most familiar platforms. Most recently he ran the global community for Mesosphere, including... Read More →


Sunday October 22, 2017 10:20am - 10:50am PDT
Room E Room E

10:20am PDT

Pioneering the Worlds First Public Data Utility
Offering a new take on the long standing excitement over smart cities, ARGO offers unique public data infrastructure that integrates mission critical datasets to deploy analytics that support municipal managers in moving the needle on important public problems. In building this new public data infrastructure, ARGO proceeds from a fundamental conviction in the importance of public service, an appreciation for historical context in pioneering the new and a pragmatic ethos embracing the “art of the possible” with an “instruction to deliver.” Our core founding team graduated together from New York’s Center for Urban Science and Progress (“CUSP”), a core node in the rapidly maturing smart cities movement.ARGO’s Kraken public data infrastructure builds from its successful integration of water use and contextual information across California’s 410 major urban water retailers, powering the first ever assessment of Governor Brown’s statewide water efficiency targets for 4% of what the state budgeted. Uniquely, ARGO develops and deploys open source analytics in deep collaboration with municipal partners, iterating and even committing code together. Those analytics have already saved over $20 million for participating water utilities and are powering the transformation of the water industry.

Speakers
avatar for Patrick Atwater

Patrick Atwater

Founder and Water Project Manager, Advanced Research in Government Operations
Patrick Atwater serves as project manager for the California Data Collaborative, a coalition of water utilities working together to share metered water use data and ensure water reliability. He has worked as a consulting data engineer for a multi-million dollar venture-backed startup... Read More →


Sunday October 22, 2017 10:20am - 10:50am PDT
Room F Room F

10:20am PDT

Data Analytics Drives FinTech
I have spent the past 14 years in leadership positions at fin-tech companies, always with data and analytics at the core of my job and my companies' success. Few industries stand to gain as much from the benefits of big data as fin tech, and few industries have a greater need for world-class talent in this area.

In my experience at Green Dot, we helped build the world's largest issuer of prepaid debit cards, using data to battle international fraud rings and develop winning pricing and marketing strategies.

At Klarna, we leveraged data to make underwriting decisions based on the smallest possible number of keystrokes, changing the way that millions of people shop online.

Scratch Financial is changing the way that Americans access to credit at the point of sale by bringing real-time underwriting and financing to the veterinary industry.

I look forward to sharing my insights with the next generation of data scientists.

Speakers
avatar for John Keatley

John Keatley

CEO, Co-Founder, Scratch Financial
John Keatley is the Co-Founder and CEO of Scratch Financial, a point-of-sale lender that aims to help merchants increase sales and help consumers quickly and easily obtain low-cost financing for high ticket price items. Scratch is initially focused on the veterinary care segment with... Read More →


Sunday October 22, 2017 10:20am - 10:50am PDT
Room G Room G

10:20am PDT

(Speaker Cancelled)Potential Solutions from Precision Medicine for the Crisis of Chronic Disease
Chronic health problems such as cardiovascular disease, diabetes, obesity, cancer and kidney disease account for more than 75% of the nation's $2.7 trillion in annual spending for medical care. 80% of their onset can be avoided if individual biomarker-guided targeted early prevention is implemented. However current risk stratification and prediction tools used by healthcare industry today only capture about less than 25% high-cost patients at the very late full-blown stage of a disease. That is why current care or disease management programs failed to bend the cost curve, and HC cost still grows at an unsustainable speed.

Genetic risk biomarker integrated modeling can improve accurate risk estimation & prediction and will optimize intervention at the right time with the right patients and can achieve maximum ROI.

Precision medicine will revolutionize HC from sick care to prevention and health preservation.What is needed and how these discoveries will be used to speed up this transformation and consequent cost saving from these potentially reduced chronic diseases will be explored.

Speakers
avatar for Frank Song

Frank Song

Sr. Director, Healthcare Informatics, Human Longevity, Inc.
Frank joined Human Longevity, Inc. in 2016 as a thought leader and SME to support human genome research-based product development for life insurance and HC industry. Frank was the executive director of enterprise analytics at HCSC – a five states BCBS health plan, where he led the... Read More →


Sunday October 22, 2017 10:20am - 10:50am PDT
Room B Room B

10:55am PDT

Deep Learning for Ad Mix Optimization
Online advertising is a highly dynamic and non-linear problem, which makes changes unpredictable, controls unreliable, and the data is often incomplete or censored. Deep learning can address these challenges and can generate optimal ad mixes.

Speakers
avatar for Neal Fultz

Neal Fultz

Principal Data Scientist, System1
Neal Fultz is the Principal Data Scientist at System1 (a Venice ad-tech startup), the Owner-Operator of NJNM Consulting (a boutique statistical consultancy), and the author of several open-source R and Python packages for Bayesian inference and optimization.


Sunday October 22, 2017 10:55am - 11:25am PDT
Room D Room D

10:55am PDT

Persuasion Modeling
Political campaigns in the U.S. have made extensive use of persuasion modeling in recent election cycles. These same modeling approaches are now making their way into commercial applications. In this presentation, I discuss political persuasion modeling, and present case studies from recent political campaigns. I'll then turn to potential commercial applications, and discuss best practices for data security, modeling, validation, and evaluation.

Speakers
avatar for Michael Alvarez

Michael Alvarez

Professor, Caltech
A professor of political science at Caltech, R. Michael Alvarez has extensive research and professional experience in statistics, research methodology, and data science. His research has focused on data science as applied to survey methodology, political behavior, electoral campaigns... Read More →


Sunday October 22, 2017 10:55am - 11:25am PDT
Room C Room C

10:55am PDT

Algorithmic Content Augmentation: Applying Data Science to Internet Media
With increasing competition for internet traffic, content creators and publishers are looking for new ways to enhance user experiences. With Career Trend (careertrend.com), we wanted to provide unique, data-infused tools, and present data in a way that is new and useful to users.
We algorithmically created 340 occupation landing pages infused with data spanning several government agencies and different classification systems. We present occupation data as a time series, comparing past predictions with actual data collected, a way these data have not been presented before. An example of one of these pages is here (careertrend.com/software-developers.html), with a full listing here (careertrend.com/nav-occupations.html). We surface links to related occupations on each article page using document similarity techniques.

In addition we created unique tools like the career word cloud quiz (careertrend.com/quiz.html) using a recursive clustering algorithm which enforces (roughly) equal cluster sizes to improve the usability of the quiz.

Career Trend is powered by looking for new ways to extract value and insight from data, from presenting disparate data in a new way to inventive use of machine learning tools like clustering.

Speakers
avatar for Matthew Theisen

Matthew Theisen

Software Engineer, Leaf Group
I'm currently a software engineer at Leaf Group working on web content and analytics. I look for ways to algorithmically understand and enhance user experiences on our content channels. This includes article recommendation, finding related images, and infusing data into content pages.In... Read More →


Sunday October 22, 2017 10:55am - 11:25am PDT
Room E Room E

10:55am PDT

“Full Stack” Data Science with R for Startups: Production-ready with Open-Source Tools
In the past 5 years, there has been a rapid evolution of the ecosystem of R packages and services. This enables the crossover of R from the domain of statisticians to being an efficient functional programming language that can be used across the board for data engineering, analytics, reporting and data science.
We’ll illustrate how startups and medium-size companies can use R (or other languages) as a common language for i) engineering functions such as ETL and creation of data APIs, ii) analytics through scalable real-time reporting dashboards and iii) the prototyping and deployment of ML models. Along the way, we’ll specifically identify open-source tools that allow scalable stacks to be built with minimal budgets. The efficiency gained enables small to mid-size teams to provide diverse lateral intelligence across a company.

Speakers
avatar for Ajay Gopal

Ajay Gopal

Chief Data Scientist, SelfScore Inc
Ajay is a DTLA resident who's building his second FinTech Startup Data Science team as Chief Data Scientist at SelfScore. Before that, he built and grew the data science & digital marketing automation functions at CARD.com - a Santa Monica FinTech Startup. In both roles, he has built... Read More →


Sunday October 22, 2017 10:55am - 11:25am PDT
Room F Room F

10:55am PDT

How data science is transforming wealth management
I will provide my insights and observations on how data science is changing how advisors understand clients, risk (what totum does), investment strategies, and practice management.

Speakers
avatar for Min Zhang

Min Zhang

CEO and co-founder, Totum
Min Zhang, CFA is CEO and co-founder of Totum Wealth.  Min brings over 10 years of institutional investing experience to transform wealth management.  Previously, Min was Director of Investment Risk Management at Pacific Life and VP in Asset Allocation Product Management at PIMCO... Read More →


Sunday October 22, 2017 10:55am - 11:25am PDT
Room G Room G

10:55am PDT

Intro to Healthcare Analytics
I would discuss My role at Anthem. I take the lead in supporting the provider analytics contacting the team in California. The tools I develop guide cost of care initiatives, contracting renewals, and programming initiatives for internal and external consults.

Through the development of preliminary analytical tools like plug and play models and predictive trend reports, we can deep dive into concrete details questions that help us discover trends within membership, facilities, and doctors.

As a novice to this analytic data world, with only two years of experience, the possibility of how I can utilize my skills and use data science to improve healthcare is a great passion of mine.

Speakers
avatar for Griselda Vargas

Griselda Vargas

Health Care Analytics, Anthem
I was born in raised in South Los Angeles and have always had a passion for technology. I worked in nonprofit sector creating technology tools for community college vocational training program which included healthcare administration. As I became more curious about healthcare, I worked... Read More →


Sunday October 22, 2017 10:55am - 11:25am PDT
Room B Room B

11:30am PDT

Hot Dog, Not Hot Dog! Generate new training data without taking more photos.
If you've been a Silicon Valley TV show enthusiast like I am then you've heard about the "hot dog, not hot dog" app.It's true that getting great training data is one of the most arduous tasks but there are simple and proven techniques to generate training data at the comfort of your ergonomic chair without involving a class of college students.

I will share what I've done for one of the self-driving car projects where I generated more image data before feeding it to the Neural Network algorithm for classification.

Speakers
avatar for Annie Flippo

Annie Flippo

Manager of Analytics and Lead Data Scientist, Thinknear by Telenav
Annie is a software engineer, product/project/people manager, and a data scientist. She focuses on the application of machine learning techniques to extract insights in the areas of marketing, media, publishing and consumer behavior. She is an advocate of the STEM for women & minority... Read More →


Sunday October 22, 2017 11:30am - 12:00pm PDT
Room D Room D

11:30am PDT

Operationalizing your Data Lake: Get Ready for Advanced Analytics
Data without analytics are wasted resources. Analytics without a modern data architecture is useless. With next-gen capabilities like machine learning and automation emerging, how do you set yourself up for success?

Many enterprises are finding success with an architecture that has a data lake at the core because a data lake offers the agility and scalability that is required for big data. However, not all data lakes are able to deliver analytics at the speed needed to make a disruptive difference among their competition.

With a majority of Hadoop implementations failing to make it to production, it is critical to add a big data management platform to operationalize, automate and optimize your data lake for success.

Speakers
PP

Parth Patel

Big Data Solutions Engineer, Zaloni
He has extensive experience in architecting analytics-ready next-generation data lakes incorporating on-premise or public cloud (AWS, Azure, GCP) infrastructure to meet enterprise needs. Previous experience in network solutions architecting for Orologic, and Vitesse; and technology... Read More →


Sunday October 22, 2017 11:30am - 12:00pm PDT
Room C Room C

11:30am PDT

Best Practices in Data Partnerships Between Mayor's Office and Academia
In this session, we will share 3 to 5 best practices anchored around stories from the partnership between the Mayor's Office of Budget & Innovation, top-tier universities, community groups and professional organizations.

Speakers
avatar for Juan Vasquez

Juan Vasquez

Data Programs Manager, Business Experience Unit, Los Angeles Office of Finance
I am a communications professional currently working at the LA Mayor's Office with the Operations Innovation Team.My role merges data analysis and storytelling, a healthy dose of partnership building, and a wealth of public speaking and project management.In past lives, I've been... Read More →


Sunday October 22, 2017 11:30am - 12:00pm PDT
Room E Room E

11:30am PDT

Practical Machine Learning at Work
I'd like to present basics of machine learning that I used at the previous company and how I used machine learning to improve company performance.

Speakers
avatar for Phillip Kim

Phillip Kim

Data Scientist, Banking & Quantitative Solutions
UCLA Math graduate. Wall Street Analyst & Head of data analytics at the previous company.


Sunday October 22, 2017 11:30am - 12:00pm PDT
Room G Room G

11:30am PDT

Healthcare Data Analytics Landscape
What is Analytics Landscape? Throughout the year and have spoken to many and the answer is simply building a data warehouse, and it will solve organization analytics needs. The true is Data warehouse is not analytics platform, and data warehouse simply is the way to integrate data from multiple sources, as simple as that.

What about BI? BI or Business Intelligence simply just a reporting tools to deliver content to your user instead provide insight. In reality, that almost no one in your organization understands statistical result. What is missing is how you deliver the statistical result to your user, not just through reporting tools, but also allowing your audience to be able to connect the dot and that is what I call provide insight. The same mythology also applies to building healthcare data analytics landscape.

Speakers
avatar for Hooi Nee Goh

Hooi Nee Goh

Kaiser Permanente, Lead Data Architect
I specialize in Healthcare Data Analytics landscape, with approximate 15 years of data warehouse and business intelligence experience. I have a great opportunity joined Davita Medical group (formerly is Healthcare Partners), about eight years ago and fell in low with the complexity... Read More →


Sunday October 22, 2017 11:30am - 12:00pm PDT
Room B Room B

11:30am PDT

Data Science Innovation in Fintech Startup
Questions:
1) Could you give us a brief introduction about your company?
2)     How have you applied advanced data analytical tools in the Fintech industry? For example, do you find advanced machine learning tools like deep learning, XP boost more useful? Or is it more relevant to gather more information by expanding the alternative data source?
3)     How did you find the opportunities where the traditional financial companies do not cover?
4)     What are the most useful data analysis skills in your companies?
5)     Hi, Ken, there are many rebate websites on the market. What is your advantage in this industry?
6)     Hi, Zhiyao, you worked at Capital One before. What is the big difference between working in a startup and banking industry?
7)     What is your vision for the company and its niche market?
8) How do you view the potential competition from similar startup competitors? Or in the more extreme case some AI/internet giants like Amazon and Facebook are trying to do similar things what would be your strategy for your company. At least I have heard Amazon once was interested in buying capital one to get into the consumer credit market.
8)     How is your opinion about the development of Fintech in the US? Which specific fields do you think has the best potentials?
9)     There are a lot of Fintech unicorn companies in China. What are the differences between the Fintech inChina and US? Population concentration is one factor and how about the “universal” use of what and social media?

Speakers
avatar for Ken Lian

Ken Lian

Founder & CEO, Founder & CEOMoolah Science
Founder & CEO of Moolah Science, ex-Honey BD Director. Author of Adventures Crossing the U.S.A. by Tandem Bike
avatar for Zhiyao Pei

Zhiyao Pei

Business Analytics Manager, Payoff


Sunday October 22, 2017 11:30am - 12:10pm PDT
Room F Room F

12:00pm PDT

Lunch Break
Sunday October 22, 2017 12:00pm - 1:00pm PDT
Room D Room D

12:00pm PDT

Lunch Break
Sunday October 22, 2017 12:00pm - 1:00pm PDT
Room C Room C

12:00pm PDT

Lunch Break
Sunday October 22, 2017 12:00pm - 1:00pm PDT
Room E Room E

12:00pm PDT

Lunch Break
Sunday October 22, 2017 12:00pm - 1:00pm PDT
Room F Room F

12:00pm PDT

Lunch Break
Sunday October 22, 2017 12:00pm - 1:00pm PDT
Room G Room G

12:00pm PDT

Lunch Break
Sunday October 22, 2017 12:00pm - 1:00pm PDT
Room B Room B

1:00pm PDT

State of AI/ML in Real Estate
The real estate industry is generating terabytes of data, but till this day a tiny percentage is being utilized or processed. Currently, we have a huge spike in interest real estate analytics field – from multiple startups in the field with multi-million funding to top prize competitions on Kaggle.

In this talk, we are going to discuss popular approaches to model real estate markets and also explore the most promising AI/ML techniques for the field

Speakers
avatar for Anton Polishko

Anton Polishko

CTO, ZULLOO Inc
Anton is a published author of predictive modeling algorithms with application in computational biology. Anton received his Ph.D. in Computer Science from UC Riverside, Master of Science in Finance and honored Master of Science in Applied Mathematics from Taras Shevchenko National... Read More →


Sunday October 22, 2017 1:00pm - 1:30pm PDT
Room E Room E

1:00pm PDT

Lending with Alternative Data
The mission of Tala is to provide financial access, choice, and control to the unbanked or under-banked population in the developing world. Our primary product is a short-term loan applied for through our mobile app. In the developing world, we face the challenge that almost none of our applicants have any traditional credit bureau data. Instead, we use a wide variety of behavioral data from their mobile phones with machine learning to underwrite our customers.

In this talk, we'll discuss some of the interesting feature engineerings we use to predict credit performance, as well as a few challenges our data science team has faced. One challenge we've faced is the "cold start" problem when we enter a new market. In this talk, I'll discuss a transfer learning approach to addressing this challenge. Second, we'll discuss some of the microeconomic and macroeconomic insights we can find from this dataset with the recent Kenyan election as an example. Finally, we'll discuss some of the ethics involved in using personal mobile data to make underwriting decisions.


Speakers
avatar for Ian Parrish

Ian Parrish

Data Science Manager, Tala
Ian Parrish is a senior data scientist and manager at Tala. In this role, he leads efforts to build our credit modeling and fraud detection efforts. Prior to coming to the data science world, Ian worked in computational astrophysics using supercomputer to study galaxy clusters and... Read More →


Sunday October 22, 2017 1:00pm - 1:30pm PDT
Room G Room G

1:00pm PDT

Generating Creative Works with AI
In addition to classification and regression capabilities, AI, in particular, Deep Learning can be used for generating new data. A trained deep neural network can be sampled, in different layers, to generate novel data. There has been work in generating "alien-looking" images, novel sounds and text in this way. The challenge in utilizing this technique for creative purposes is shaping the generated samples to fit a user's, or the general audiences' tastes.

I'll be presenting our approach, at EndCue, in utilizing variational auto-encoders, with active learning to elicit user preferences, to generate scripts, dialogues, and speech.

I'll present how we have used these techniques to produce a series of the world's first movies written by AI. I'll also show how we have used these generative AI methods to create a platform for story tellers, to augment their creative process.

Speakers
avatar for Debajyoti (Deb) Ray

Debajyoti (Deb) Ray

CTO, EndCue
Debajyoti (Deb) Ray and his team of Data Scientists and Engineers are building End Cue’s AI platform for analyzing and generating original content.Previously, Deb was the Chief Data Officer for VideoAmp, a cross-screen digital video, and TV advertising platform, where he continues... Read More →


Sunday October 22, 2017 1:00pm - 1:45pm PDT
Room D Room D

1:00pm PDT

Machine Learning in Healthcare and Life Science
AI and ML opportunities and challenges in Pharmaceutical and Life Sciences, focus on use cases in drug discovery, clinical development, and real-world evidence.

Speakers
avatar for Andrew Zhang

Andrew Zhang

Big Data Analytics Solution Architect, IBM
Andrew Zhang is a solution architect with IBM Analytics, his specialty is data science, machine learning and open source technologies such as Apache Spark and Hadoop. He consults clients in healthcare, life sciences, and public sector and provides cloud analytics solutions with IBM... Read More →


Sunday October 22, 2017 1:00pm - 1:50pm PDT
Room C Room C

1:40pm PDT

Interpretable Machine Learning for Human Behavioral Data
Understanding the mechanisms and drivers of human behavior is a difficult problem, accentuated by the heterogeneous nature of human behavioral data. This poses major issues for our ability to model and understand social systems, with important implications for design, testing and interventions in such systems.In this talk, I will present a statistical methodology to understand human behavior that quantifies feature importance, feature correlations and the level of predictability in human behavior data.

This methodology is highly interpretable, utilizing the R2 coefficient of determination to measure both the predictability of a system and the cumulative contribution of each feature towards this overall predictability. Our approach is non-parametric and free of any functional form, thus allowing for the capturing of non-linear and heterogeneous data which regularly occurs in human behavioral dynamics.

To illustrate, I will show our applications of this approach to various domains including the analysis of human performance in the Stack Exchange online forum and information sharing in the Twitter and Digg online social networks. In the case of information sharing on Twitter, for example, we show how our method effectively uncovers correlations among both individual-based features and information-based features, presenting a hierarchy of features that cumulatively explain human behavior in this social system.

Speakers
avatar for Peter Fennell

Peter Fennell

Postdoctoral research fellow, USC Information Sciences Institute
Dr. Peter Fennell is a James S. McDonnell Postdoctoral Fellow at the Information Sciences Institute, University of Southern California. His research examines human behavior and social networks and developing statistical and machine learning methods to understand and model such systems... Read More →


Sunday October 22, 2017 1:40pm - 2:10pm PDT
Room E Room E

1:40pm PDT

Data Architecture (i.e., normalization / relational algebra) and Database Security
The importance of precise data structures when handling, processing and manipulating mass amounts of data.  As data has become key in the operations of virtually all companies around the world, having the data easily maintained and utilized has become pivotal.

Companies often live or die in today’s business climate by their ability to manipulate their data to their company’s competitive advantage.  As such it becomes paramount that this enterprise critical data be placed into well-organized structures that are intuitive for developers to work on.

Speakers
avatar for Samuel Berger

Samuel Berger

CIO, CLEAR Information, Inc.
Fintech entrepreneur and developer as well as a data scientist working with financial mass data projects since 1989. He started in these fields in 1989 with SBIC. Used technology and massive amounts of data to predict the world’s largest financial market. His systems earned his... Read More →


Sunday October 22, 2017 1:40pm - 2:30pm PDT
Room G Room G

1:55pm PDT

Learning to learn Model Behavior: How to use "human-in-the-loop" to explain decisions.
The adoption of Machine Learning or Statistical Models in solving real-world problems has increased exponentially, but users still struggle to derive full potential of the predictive models. There is still a dichotomy between explainability and model performance while choosing the algorithm. Linear Models / Simple Decision Trees are often preferred over more complex models such as Ensembles or Deep Learning models when operationalizing models for ease of interpretation which often results in loss of accuracy.

But, is it necessary to accept a trade-off between model complexity and interpretability?Being able to interpret and explain a model globally faithfully helps in understanding feature contribution on predictions and model variability in a non-stationary environment. This enables trust in the algorithm which drives better collaboration and communication among peers. The need to understand the variability in the predictive power of a model in a human-interpretable way becomes even more important for complex models, e.g., text, image, machine translations.

In this talk, we demonstrate the usefulness of our Model Interpretation library (Skater) for evaluating models using interactiveness and usefulness of Jupiter environment and how it could help practitioners - analysts, data scientists, statisticians - understand the model behavior better without compromising on the choice of algorithm.

Speakers
avatar for Pramit Choudhary

Pramit Choudhary

Lead Data Scientist, DataScience.com
Pramit Choudhary is a Lead Data Scientist at Data Science.com. His focus is on effective ways of optimizing and applying classical (Machine Learning) and Bayesian design strategy to solve real-world problems. Currently, he is leading initiatives on figuring out better ways to explain... Read More →


Sunday October 22, 2017 1:55pm - 2:40pm PDT
Room D Room D

2:00pm PDT

MCL Clustering of Sparse Graphs
The increasing need for clustering in several scientific domains has inevitably driven the creation of innovative algorithms, each designed to perform more efficiently in certain applications. More specifically, in many applications, the data entities involved can be portrayed effectively by a graph as a collection of nodes and edges. One of the most established algorithms for graph clustering problems is the Markov Cluster Algorithm (MCL).

When dealing with large and complex datasets, the underlying graphs can easily reach proportions that independent computing systems are inadequate to deal with. Additionally, the graphs encountered are typically sparse: the number of edges is far smaller than might be possible in a fully-connected graph. Consequently, there is a concrete need for algorithms that are designed to handle sparse graph clustering utilizing distributed computing resources.

Our motivation was the development of a distributed architecture, able to accommodate large and sparse graphs, to actualize the MCL and R-MCL algorithm. The Apache Spark framework was chosen due to its ability to utilize distributed resources and its proven track record.

Although Spark is a framework capable of handling massive datasets, it currently does not provide rich support for computation with sparse matrices and sparse graphs. Hence, methods have been implemented to enable the exploitation of sparse adjacency matrices in distributed sparse matrix multiplication, a critical component of MCL. The proposed solution can handle arbitrarily large inputs, provide almost linear speed-up with the addition of computational resources and output results directly comparable to the non-distributed reference MCL implementation.

Speakers
avatar for Athanassios Kintsakis

Athanassios Kintsakis

Machine Learning Engineer, Capital One Financial
Athanassios Kintsakis is an ECE BSc/MSc graduate, and Ph.D. Candidate in the field of statistics and machine learning applied in bioinformatics at the Aristotle University of Thessaloniki. He has co-authored numerous journal publications, presented at international conferences and... Read More →


Sunday October 22, 2017 2:00pm - 2:30pm PDT
Room C Room C

2:20pm PDT

Fake News Detection Using Machine Learning and Blockchain Technology
After the 2016 US presidential election, many people shocked with the outcome, looked for the cause of the “surprising” result. Some blamed the outcome on the fake news phenomenon during the election: it painted false images of candidates for better or for worse. A majority of the most viral news articles covering the election turned out to be fake stories . We created Geppetto. Geppetto is a platform that identifies valid contents in a news article. Geppetto can accurately identify and screen fake news in real-time, using tamper-proof and cost-effective methods that preserves trust in the process. Users can communicate with the Geppetto platform in three ways; (1) as a publisher who can publish its own article on the platform, (2) as a voter to validate/dis-validate a news, (3) as a consumer who searches a news on this platform.The platform requires a database to store the newly published news and verified news by the voters. There is a veracity engine which consists of several natural language processing and machine learning models that can score the legitimacy of the articles and the reliability of validators (voters) and publishers. Because fake news evolves rapidly, the performance of any model built on the historical data can decay rapidly. To address this, we use a continuous learning (CL) algorithm to update the model continuously. The CL component requires a knowledge base to store historical data and re-evaluate the models. Geppetto uses blockchain technology to ensure the system’s data is tamper-proof and decentralized.

Speakers
avatar for Farshad Kheiri

Farshad Kheiri

Lead Data Scientist, BCG Digital Ventures
Farshad is a Lead Data Scientist at BCG DV; he has been working on several projects used machine learning including deep learning, natural language processing, and other data science techniques for several projects. On one of his last project, he has used data science and block-chain... Read More →


Sunday October 22, 2017 2:20pm - 2:50pm PDT
Room E Room E

2:40pm PDT

Data Science at City Scale
As a data scientist at the City of Los Angeles, we see a novel form of big data- that is, a novel variety of data.This talk will analyze three projects done at the city.
1) Predicting Displacement
2) Easing Traffic
3) Targeting Audits

Speakers
avatar for Hunter Owens

Hunter Owens

Data Scientist, City of Los Angeles
Hunter Owens is a Data Scientist for the City of Los Angeles. Prior to joining the City, he worked for the Center for Data Science and Public Policy, KIPP NJ and Obama for America. He spends his weekends biking around Los Angeles and making maps.


Sunday October 22, 2017 2:40pm - 3:10pm PDT
Room C Room C

2:50pm PDT

Blockchain Application in Real Estate Transactions
FundingTree is the first platform that will bring Blockchain Distributed Ledger Technology & Smart Contracts into Commercial Real Estate transactions, and all participants into a Single Delivery shared a platform to deliver Funding Solutions like never before.
The blockchain

A world of continued technological evolution, most new technology comes with the promise to improve business efficiency and profitability. The early internet dealt with intangibles – like emails. Today’s internet can deal with real assets - assets that are stored in encoded form in a network-to-network chain called the blockchain. This blockchain will not only facilitate our business dealings and assets by preventing unwanted third-party interference, fraud, and theft but, it will also, simplify and quicken processes, raise efficiency, increase transparency and reduce errors while saving users time and money.
Smart Contracts

Creating smart contracts & securing documents on the Blockchain will ensure originality, authenticity, and traceability. These fundamentals have always existed in safeguarding Real Estate transactions.

Speakers
avatar for Rayaan Arif

Rayaan Arif

Founder - Principle, FundingTree
Rayaan is the Founder of FundingTree.com. He is a serial Entrepreneur with a passion for tackling difficult problems. This passion has to lead him to find better ways to deliver Capital and Deal Flow using technology, marketing, and relationships he has cultivated over several decades.Rayaan... Read More →


Sunday October 22, 2017 2:50pm - 3:20pm PDT
Room G Room G

2:50pm PDT

Panel: What are the opportunities for AI and industry in the next 5 years?
Moderators
avatar for Kyle Polich

Kyle Polich

Host, Data Skeptic
Kyle Polich is the host of Data Skeptic, a podcast about data science, statistics, machine learning, and artificial intelligence, all through the eye of scientific skepticism. Outside of the show, he's an advisor for a few early-stage startups and consults with growth companies to... Read More →

Speakers
avatar for Frank Bell

Frank Bell

Principal, IT Strategists
Frank Bell is a Principal at IT Strategists (www.itstrategists.com), a leading business and technology consulting firm in advanced AI, web, and mobile development in Southern California. He has consulted with companies such as Yahoo, Disney, Toyota, Nissan, Deluxe, AEG, Fox, Cisco... Read More →
avatar for Pramit Choudhary

Pramit Choudhary

Lead Data Scientist, DataScience.com
Pramit Choudhary is a Lead Data Scientist at Data Science.com. His focus is on effective ways of optimizing and applying classical (Machine Learning) and Bayesian design strategy to solve real-world problems. Currently, he is leading initiatives on figuring out better ways to explain... Read More →
avatar for Annie Flippo

Annie Flippo

Manager of Analytics and Lead Data Scientist, Thinknear by Telenav
Annie is a software engineer, product/project/people manager, and a data scientist. She focuses on the application of machine learning techniques to extract insights in the areas of marketing, media, publishing and consumer behavior. She is an advocate of the STEM for women & minority... Read More →
avatar for Debajyoti (Deb) Ray

Debajyoti (Deb) Ray

CTO, EndCue
Debajyoti (Deb) Ray and his team of Data Scientists and Engineers are building End Cue’s AI platform for analyzing and generating original content.Previously, Deb was the Chief Data Officer for VideoAmp, a cross-screen digital video, and TV advertising platform, where he continues... Read More →


Sunday October 22, 2017 2:50pm - 3:40pm PDT
Room D Room D

3:00pm PDT

Ensuring Data-centric Systems are Useful and Usable
The data model you have accurately describes and predict the available dates but your stakeholders are refusing to accept their accuracy. This talk is aimed at helping data scientists understand how to maximize usefulness and usability of their work.

Speakers
avatar for Mike Oren

Mike Oren

Consultant, Independent
Mike Oren has a Ph.D. in human-computer interaction and sociology with a BA in computer science. He currently consults with Uptake and Pogorelc.


Sunday October 22, 2017 3:00pm - 3:30pm PDT
Room E Room E

3:20pm PDT

AI-Powered Future Space Exploration
Space is the final frontier whose exploration requires disrupting technology advancement in many areas including AI. In this talk we will present a historical flashback of AI's application in the past and current space exploration, explain its unique technical challenges, and describe some viable use cases and emerging opportunities of future space exploration enabled by AI as a game-changing technology.

Speakers
avatar for Yutao He

Yutao He

Sr. Research Technologist, NASA/JPL
Dr. Yutao He is currently Senior Research Technologist at NASA/Jet Propulsion Laboratory (JPL), leading the research and development of advanced computing technology for future NASA space missions. He is also an adjunct faculty member at UCLA and CSULA. His current research interests... Read More →


Sunday October 22, 2017 3:20pm - 3:50pm PDT
Room C Room C

3:30pm PDT

ICOs and cryptocurrency - what are they, what do they mean for currency
This past summer was the Summer of the ICO. In this talk, I will lay out the basic structure of cryptocurrencies, the blockchain system that underpins it, and the rise of ICOs.

I will then discuss financial, social and legal implications of cryptocurrencies. These range from the nature of fiat currency, how crypto arose, current securities and other legal issues related to ICOs and crypto, financial issues relating to the use of crypto and valuation, and social issues attendant with cryptos.

Finally, I will discuss best and worst use cases, as well as the investment tips and flags as they are becoming clear.

Speakers
avatar for Alexandra Damsker

Alexandra Damsker

CEO, Stealth fintech
I am an experienced corporate and securities attorney (SEC and international law firm trained). I've written a practitioners' text on trusts and taxation, coedited a securities treatise, as well as numerous articles on various legal subjects. These focused primarily on securities... Read More →


Sunday October 22, 2017 3:30pm - 4:00pm PDT
Room G Room G

3:40pm PDT

How Machine Learning Can Eliminate Hiring Biases and Identify the Right Candidate For a Job
Hiring the right developer for a job has been a challenge for a long time and is getting worse because of the demand. It’s a time-consuming process. According to Amazon's CTO Werner Vogels, engineers spend 30% of their time on evaluating talent; time that could be better spent on building products.

Not only that, the traditional recruiting methods, like resumes and face-to-face interviews, are susceptible to unconscious biases against candidates. These are social stereotypes about certain groups of people that are ingrained in people without poor intentions.However, these biases can cost someone their job. Machine Learning can help eliminate some of the biases that are inherently found in traditional recruiting tactics.

This talk is about how we are working to extract purely objective features from a typical technical interview and automate them through machine learning models. Ultimately, companies can eliminate bias and reduce effort in their hiring process.

Speakers
avatar for Shiv Muddada

Shiv Muddada

Engineering Manager, HackerRank
Shiv Muddada is one of the founding engineers of HackerRank and currently head engineering at its headquarters in Palo Alto. HackerRank creates opportunities for developers by helping companies find great developers based on their skills instead of pedigree.In the past five years... Read More →


Sunday October 22, 2017 3:40pm - 4:10pm PDT
Room E Room E

3:50pm PDT

Introduction to Deep Reinforcement Learning
Over the past few years, the AI community has witnessed huge breakthroughs since the development of deep reinforcement learning. For example, using reinforcement learning scientists developed software that learned how to achieve super-human skill in playing different Atari games directly from raw-pixels without being given any game-specific instructions, and the AlphaGo AI system from DeepMind used reinforcement learning to master the Go game and beat the best human champion.

Reinforcement learning is a branch of artificial intelligence that deals with teaching machines how to choose best actions to perform while facing uncertainty. It has a lot of applications in robotics, recommendation systems,  and autonomous systems such as self-driving cars.

In this tutorial, we are going to provide an explanation about reinforcement learning from the ground-up covering the fundamental theory and algorithms. We will also describe how RL meets with the powerful deep-neural networks to form "deep reinforcement learning". In addition, we will demonstrate code examples that show how to apply these algorithms to solve AI problems.

Speakers
avatar for Moustafa Alzantot

Moustafa Alzantot

PhD student in the Networked and Embedded Systems Laboratory (NESL), UCLA


Sunday October 22, 2017 3:50pm - 4:20pm PDT
Room D Room D

4:20pm PDT

Best Practices for Aggregating, Cleaning and Normalizing Data
Disparate data sources are a constant problem in text analytics. Different sources have varied document formats, dating conventions, and ways of presenting the same information. Collecting, normalizing, and building models on such data sets is a challenge that requires artful human involvement.

In this talk, I discuss my experiences, as well as popular conventions, for building human-in-the-loop machine learning systems from vast and varying data sources.

Speakers
avatar for Daniel Dandurand

Daniel Dandurand

Data Engineer, Compliance.ai
Dan was a physics Ph.D. student at UC Berkeley before making the switch to data science. He was a Data Engineering Fellow at Insight Data Science before joining Compliance.ai as a Data Engineer. Also, last year Dan spent time in China as an organizer of the global summit, Cre8, a... Read More →


Sunday October 22, 2017 4:20pm - 4:50pm PDT
Room E Room E

4:30pm PDT

AliMe Bot Platform Technical Practice - Alibaba`s Personal Intelligent Assistant in the E-commerce Field
  • With the development of AI, the companies including Google, Facebook, Microsoft, Amazon and many startups have built their own intelligent assistant or bot platform, the intelligent human-computer interaction becomes an important direction of AI. In July 2015 we built an intelligent assistant called AliMe Assistant in Alibaba, focus on three domains: customer service, shopping guide and assistant application in the e-commerce field. 
  • With the development of technology and product, in July 2016 we also published bot platform called AliMe bot platform to help merchants and enterprises which are in the e-commerce ecosystem to enhance their business. The sharing outline:
    • AliMe Bot Platform Introduction
    • Intelligent Interaction Technical Practice In Alibaba
    • The Future and The Challenge

Speakers
avatar for Chen Haiqing

Chen Haiqing

Senior Technical Expert, Alibaba
Alibaba Intelligence Innovation Center Senior Technical Expert, I have worked and studied in the field of the intelligent human-computer interaction in Alibaba for 8 years, lead the technical team to build bot platform and it has covered multi-domain scenes in Alibaba including Taobao... Read More →


Sunday October 22, 2017 4:30pm - 5:00pm PDT
Room D Room D