Data Science Expo

Saturday, May 18th | Pasadena Convention Center

Get Tickets Partner

Deep Learning

Machine Learning

Predictive Analytics

Natural Language Processing

Data Visualization

AI Research

Presented By

Participation From

...

Speakers

...

Sophie Lellis-Petrie


Data Scientist

Warner Bros. Entertainment

...

Sophie Lellis-Petrie


Data Scientist

Warner Bros. Entertainment

Combines descriptive and inferential statistics in order to have a holistic understanding of the data in order to fit the best models to the data. Has a Bachelor of Science in Statistics from the University of California, Los Angeles and pursuing Masters of Applied Statistics with strong foundation in statistics applied knowledge in capstone courses in multiple disciplines. Continues to grow statistics portfolio in the Work Force Analytics group in Warner Brothers.

...

Mc Kenna Walsh


Head of Business Development

NASA AMES Robotics Lab

...

Mc Kenna Walsh


Head of Business Development

NASA AMES Robotics Lab

Mc Kenna grew up in the heart of the silicon valley allowing her to be one of the original digital natives, giving an unusual perspective and relationship to technology. After finishing college in 2.5 years with a degree in economic policy, she went to work for a Private Equity REIT based in Latin America eventually running their business development. During that time she moved back to the Bay Area and started to help run the NASA AMES Robotics Lab, as the #1 robotics education program in the world the focus was about setting the example of what was possible and finding ways to help make those resources scalable to students around the world. She returned to the tech world full time when she started working for Tim Draper, helping with his Draper University program and as a partner at a seed investment fund where he was the primary LP. While working for Tim, she got heavily involved in the "Crypto" space, focusing on the applications of Blockchain, rather than the speculative asset class. Her writings on Venture Captial and technology have been published in Forbes, Adweek, and I.N.C, as well as being one of the top writers on Quora. More recently she was a co-founder of an AI company with a focus on creating tools to empower creatives to tell dynamic narratives. Currently, she is the Head of Business Development for VentureDevs and consults and advises for both startups and investment groups.

...

Patrick Prothro


Data Scientist

Latham & Watkins

...

Patrick Prothro


Data Scientist

Latham & Watkins

There is an interesting story behind all data. Whether it be sports, education, etc. I'm always looking to find the meaning behind the numbers. Analyze, visualize, and explain what is going on behind the scenes. It's always been a passion of mine to find the unique answers to a puzzle with multiple solutions. Using data I've been able to find those unique answers that many may have overlooked in order to improve business efficiency.

My specialties include using a broad spectrum of software programs , advanced statistics, and an acumen for problem solving to find the answers buried in a company's data. I am currently an analyst at an E-Commerce Company and plan to enter the field of Machine Learning and Data Science.

...

Jingyi Jessica Li


Assistant Professor

University of California

...

Jingyi Jessica Li


Assistant Professor

University of California

Jingyi Jessica Li is an Assistant Professor in the Department of Statistics and the Department of Human Genetics at University of California, Los Angeles (UCLA). She is also a faculty member in the Interdepartmental Ph.D. Program in Bioinformatics and a member in the Jonsson Comprehensive Cancer Center (JCCC) Gene Regulation Research Program Area. Prior to joining UCLA in 2013, Jessica obtained her Ph.D. degree from the Interdepartmental Group in Biostatistics at University of California, Berkeley. Jessica received her B.S. (summa cum laude) from the Department of Biological Sciences and Technology at Tsinghua University, China in 2007. Jessica and her students focus on developing statistical and computational methods motivated by important questions in biomedical sciences and abundant information in big genomic and health related data. On the statistical methodology side, her research interests include association measures, high-dimensional variable selection, and classification metrics. On the biomedical application side, her research interests include next-generation RNA sequencing, comparative genomics, and information flow in the central dogma. Jessica is the recipient of the Hellman Fellowship (2015), the PhRMA Foundation Research Starter Grant in Informatics (2017), the Alfred P. Sloan Research Fellowship (2018), and the Johnson & Johnson WiSTEM2D Math Scholar Award (2018).

...

Nick Acosta


Developer Advocate

IBM

...

Nick Acosta


Developer Advocate

IBM

Before becoming an AI 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 with other data scientists of various communities, startups, and enterprises in order to help them succeed on IBM’s data science platform. He has a strong interest in data science education and all things Kardashian.

Who Should Attend

The Data Science Expo is for data scientists, business analysts, researchers, educators, students, developers, and tool creators.

Data scientists

Developers and Programmers

Students

Educators

Business Analysts

Geeks

And MORE!

AGENDA


8:55AM - 9:00AM

Opening Remarks and Announcements


9:00AM - 9:25AM

The Interview Process of Becoming a Data Scientist - Patrick Prothro (Latham & Watkins)


9:30AM- 9:55AM

Boosting Your Model with Machine Learning - Sophie Lellis-Petrie (Warner Bros. Entertainment)


9:55AM - 10:15AM

Coffee Break


10:15AM - 10:40AM

The Right Way to Approach Data in Business - Mc Kenna Walsh (VentureDevs)


10:40AM - 11:05PM

Machine Learning Pipeline with PySpark- Jayesh Patel


11:30AM - 1:00PM

Lunch Break


1:00PM - 1:50PM

Choosing The Right Cloud: A Machine Learning Approach - Nick Acosta (IBM)


2:00PM - 3:00PM

Personalizing User Experience With Machine Learning - Veer Gupta


3:15PM - 3:55PM

How To Get a Job in Data Science - Rajesh Mukherjee


4:30PM - 5:30PM

How To Control The More Severe Type of Error in Binary Classification- Jingyi Jessica Li (UCLA)


Get the latest news, offers, and more about the Data Science Expo and the topic of software development.

May 18th, 2019

Convention Center
Pasadena, CA