June 10 - 11, 2020

DATAx SAN FRANCISCO 2020 SPEAKERS

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Ankit Mangal

Associate Director, Web Analytics
Wayfair

Asma Farooq

Product Lead Machine Learning
Ebay

Austin Sun

Senior Data Architect & Director of Data Engineering in Advanced Analytics
American Tire Distributors

Bhargav Raman

CEO
Medpixels

Binwei Yang

Distinguished Engineer, Merchant Technology Data Science
Walmart

Carlo Lipizzi, Ph.D.

Graduate Engineering Management & Systems Analytics Program Director School of Systems and Enterprises
Stevens Institute of Technology

Carlos Jose Fonseca

SVP Data & Services. Sales Strategy and Solutions Financial
Mastercard

Cathy Tanimura

Sr. Director, Analytics & Data Science
Strava

Chase Kusterer

Professor, Advanced Analytics & Research
Hult International School

Chintan Shah

Vice President of Data Science and Analytics
HYLA, Inc. (“HYLA Mobile”)

Daniel Gremmell

Vice President, Data Science
Plated

DJ Patil

Head of Technology
Devoted Health

Haftan Eckholdt

Chief Data Officer & Chief Science Officer
Understood.org

Jessica B. Lee, Partner

Co-Chair, Privacy, Security & Data Innovations
Loeb & Loeb

Mario Vinasco

Director BI and Analytics
Credit Sesame

Meghan Anzelc

Head of Data and Analytics
Spencer Stuart

Michele Ceru

Data Architect
American Tire Distributors

Michelle Finneran Dennedy

Chief Executive Officer
DrumWave

Morgan Cundiff

Data Scientist
ShopRunner

Dr. Nels Lindahl

Director, Clinical Decision Systems
CVS Health

Sherin Mathews

Senior Data Scientist
Mcafee

Qiaolin Chen

Director of Data Science
Tencent Games

Romy Hussain

Director of Healthcare Economics and Data Science
Johns Hopkins Healthcare

Ronak Shah

Head of Data Engineering
Coursera

Theresa Melvin

Chief Architect, AI-Driven Big Data Solutions
Hewlett Packard Enterprise

Thomas Vincent

Head of Data Science
Getty Images

Vanitha Lucas

Board Member
Viz for Social Good

Vin Vashishta

Data Scientist, Strategist, Author
V2 Machine Learning Consulting

Wade Schulz, MD, PhD

Assistant Professor of Laboratory Medicine & Computational Healthcare Researcher
Yale University School of Medicine
Currently leading Wayfair’s applied data science team within web analytics, Ankit is an established leader in the analytics space with experience across e-commerce retail, financial services and healthcare industries. Statistician by trade, Ankit focuses on monetizing complex machine learning algorithms and massive datasets.
Austin Sun has academic backgrounds in both Business and Computer Science. He has two Master’s degrees and two Bachelor’s degrees. He has studied at Rice University, Georgetown University, George Washington University, and the University of Texas at Austin.

Austin Sun, working at American Tire Distributor (ATD), is a Senior Data Architect and Director of Data Engineering in Advanced Analytics. ATD is one of the largest auto aftermarket dealers in North America, with 5,000 employees and more than 140 distribution centers, and operates the largest tire distribution e-commerce website (tirebuyers.com). Austin is responsible for supervising company data assets, data governance, data architecture, MDM, data factory, data warehouse, Big Data, data security, and Blockchain technology. Before joining ATD, Austin worked at CGG, which is a leader in the geophysical industry, as a software engineer lead.
Bhargav Raman, MD leads multiple lives as a practicing clinician, computer and data scientist, healthcare economist, startup adviser, entrepreneur and a new father. He obtained dual-degrees in Computer Science and Biological Sciences and his MD from Stanford University. During his academic career, he did fundamental research in computer aided diagnosis, quantitation and therapy planning resulting in multiple publications. His company, MedPixels rethinks the economics of radiology at a fundamental level, maintaining quality while using data to reduce costs and increase revenue. At Oration, he built systems that used data to provide patients and employers an opportunity to make significant savings in pharmacy spend. At Carrum Health, he built data ingestion and analytics pipelines, using deep learning to gain valuable insights on their populations. He is currently also Product Lead and Medical Director at VIVIO, a startup focused on using clinical trial and observational data to increase real world cost-effectiveness of specialty therapeutics.
Binwei Yang is an engineer with more than 20 years of professional experience of creating massively scalable customer-facing applications. He was a founding member of the Computer Vision group at Walmart Labs and led the technical development of the many products that came from this effort including Visual Search on Hayneedle, models for Trust and Safety, and visual attributes for Retail Graph. Binwei graduated from University of Southern California with a Master in Computer Engineering and Ph.D. in Physics. He is passionate about becoming a lifelong learner and equipping youth in underserved communities with high-tech skills. He is currently the architect and technical lead for Retail Graph as well as the technical lead for computer vision and imagery-based AI components.
Prof. Lipizzi is a Machine Learning and Data Science Professional serving Academia and Private sector.
At the School of Systems and Enterprises of the Stevens Institute of Technology is an Industry Professor teaching Data Science and is the program lead of the Engineering Management and Systems Analytics graduate programs. As a member of the Systems Engineering Research Center, he manages research projects on a convergent use of Natural Language Processing, Machine Learning, Data Mining and Data Visualization for about $2.7 million/year.
Prof. Lipizzi has a Ph.D. in Engineering Management from Stevens, an Executive Management Degree from IMD, Lousanne, CH, and a Master equivalent in mathematics (“Laurea in Scienze Matematiche”) from the University of Rome, Italy.
His research focus is on Machine Learning and Data Science and in particular on building quantitative solutions based on Natural Language. Most of his past research activities have been centered on Social Media as a backchannel for real life activities, extracting semantic and metrics to analyze conversations.
Leveraging on more than 25 years of international experience as a consultant, entrepreneur and executive in the USA, EU and Brazil, he is also developing a consulting practice on NLP and Quantitative-Social Analysis.
Cathy Tanimura is Sr. Director of Analytics & Data Science at Strava. She has a passion for leveraging data in multiple ways: to help people make better decisions; to tell stories about companies and industries; and to build great product experiences. She previously led data teams at Okta, Zynga, and StubHub.com
Chintan Shah is the Vice President of Data Science and Analytics at Hyla. He and his team lead the Analytics, Data Science, Machine learning and Artificial Intelligence practice within HYLA and is responsible for development of HYLA Analytics platform (Device IQ) that provides customers with actionable insights in the domain of mobile device lifecycle.
He has over 16 years of experience building, and leading organizations centered on Analytics, Predictive Modeling, Machine learning and Artificial Intelligence. In his various roles, he developed and executed on enterprise information management, information delivery and data monetization strategies. Prior to Joining HYLA, Chintan led the data warehousing and business intelligence team at Verizon.
Chintan has MS in Computer and Information Systems from Southern Illinois University and Business Data Mining certificate from Oklahoma State University
Daniel Gremmell is the VP of Data Science at Plated and CEO at Business Science Solutions, LLC. He is an experienced data science leader focused on generating value in the form of product enhancements or process automation through data science. Daniel has an MS in Statistics from Rochester Institute of Technology, an MS in Manufacturing Engineering from Kettering University and a BS in Operations Management from Rutgers. He started off his career working in operations for businesses from multiple industries including consumer goods, aerospace and automotive with companies such as Crane Aerospace and Volkswagen. Holding multiple positions in supply chain, manufacturing and distribution, Daniel is a Six Sigma Black Belt and helped implement process savings with data resulting in large operational savings. Daniel later transitioned into data science and has set up numerous data science organizations in different industries. Daniel has worked on numerous projects in marketing, content, operations and product to implement data science and machine learning in large organizations with applications in supply chain forecasting, marketing segmentation and optimization, product recommendations and text prediction. Daniel’s passion lies in solving challenging problems and building machines to make decisions in the value chain resulting in numerous autonomous entities that optimize a consumer experience and reduce employee overhead.
DJ Patil is an American mathematician and computer scientist who served as the Chief Data Scientist of the United States Office of Science and Technology Policy from 2015 to 2017. He previously served as the Vice President of Product at RelateIQ, which was acquired by Salesforce.com, as Chief Product Officer of Color Labs, and as Head of Data Products and Chief Scientist of LinkedIn. His father, Suhas Patil, is a venture capitalist and the founder of Cirrus Logic.

On February 18, 2015, the White House announced Patil the first U.S. Chief Data Scientist (Deputy Chief Technology Officer for Data Policy and Chief Data Scientist). In addresses to the public, Patil states that “The mission of the U.S. Chief Data Scientist, simply put, is to responsibly unleash the power of data to benefit all Americans” and, in addition, that his team’s priority to do so by making data.

In his tenure, Patil helped launch the White House’s Police Data Initiative as well as the White House’s Data-Driven Justice Initiative, collecting data on police activities, and worked on the Precision Medicine Initiative, aiming to build the largest database on genetic information.

Prior to the White House, he has held roles at Skype, PayPal, and eBay. As was a member of the faculty at the University of Maryland, he helped start a major research initiative on numerical weather prediction. As an AAAS Science & Technology Policy Fellow for the Department of Defense, Dr. Patil directed new efforts to leverage social network analysis and the melding of computational and social sciences to anticipate emerging threats to the US. He has also co-chaired a major review of US efforts to prevent bioweapons proliferation in Central Asia and co-founded the Iraqi Virtual Science Library (IVSL)

Haftan Eckholdt, PhD. is Chief Data Officer & Chief Science Officer at Understood.org, providing digital solutions to people who think and learn differently, their parents, their educators, and their employers. His career began with research professorships in Neuroscience, Neurology, and Psychiatry followed by industrial research appointments at companies like Albertsons, Amazon, and AIG. He holds graduate degrees in Biostatistics and Developmental Psychology from Columbia and Cornell Universities. In his spare time he thinks about things like chess and cooking and cross country skiing and jogging and reading. When things get really really busy, he actually plays chess and cooks delicious meals and jogs a lot. Born and raised in Baltimore, Haftan has been a resident of Kings County, New York since the late 1900’s
Jessica Lee helps companies in the U.S. and around the world launch, market and monetize their digital products and content. She provides strategic privacy counselling to clients leveraging data in connection with programmatic and addressable advertising, voice technology, location-based tracking, smart devices and wearables, as well as emerging technologies, such as artificial intelligence and facial recognition.
Jessica has assisted dozens of organizations design their privacy programs and operationalize U.S. and international privacy and data security requirements, including the General Data Protection Regulation (“GDPR”), and, more recently, the California Consumer Privacy Act (“CCPA”). Jessica works closely with companies in the adtech, e-commerce, and entertainment space, as well as clients in more heavily regulated sectors, such as healthcare and financial services. Jessica has a deep understanding of her clients’ business interest and needs, and clients value her practical and efficient approach to counselling.
Named one of Crain’s Notable Women in Law for 2019 and Law Catalyst by the Council of Urban Professionals, Jessica is routinely called upon to speak on the privacy and cybersecurity concerns in advertising, media, adtech, and health tech. She recently testified before the California Senate Judiciary Committee on the impacts of privacy regulation on the business community.
Jessica sits on the Diversity Committee of Loeb & Loeb and is the national chair of Loeb’s affinity group for attorneys of color. She is also sits on the firm’s Pro Bono Committee and contributes her time to a number of community service projects and mentorship initiatives.
Mario Vinasco has over 15 years of progressive experience in data driven analytics with emphasis in machine learning and data scence programming creatively applied to eCommerce, advertising, customer acquisition/retention and marketing investment. Mario specializes in developing and applying leading edge business analytics to complex business problems using big data and predictive modeling platforms. Mario holds a Masters in engineering economics from Stanford University and currently works as Director of Analytics and Data Science at Credit Sesame a disruptive FinTech company in the San Francisco Bay Area, responsible for customer management, retention and prediction. Until recently, Mario worked for Uber Technologies applying data science to marketing investment optimization, advanced segmentation of customers by propensity to act, churn, open email and the set up sophisticated experiments to test and validate hypothesis. At Facebook in the marketing analytics group he was responsible for improving the effectiveness of Facebook’s own consumer-facing campaigns. Key projects included ad-effectiveness measurement of Facebook’s brand marketing activities, and product campaigns for key product priorities using advanced experimentation techniques.
Prior roles included VP of business intelligence in digital textbook startup, people analytics manager at Google and eCommerce Sr manager at Symantec.
As Head of Data and Analytics, a recently created global and firm-wide role, Dr. Meghan Anzelc is responsible for building and implementing a strategy and roadmap to advance the data and analytics capabilities at Spencer Stuart. She works with colleagues across the firm to understand their challenges and the potential opportunities for data and analytics to have a positive impact on the organization and on Spencer Stuart’s products and services for the firm’s clients. Prior to joining Spencer Stuart, Dr. Anzelc held a number of leadership roles in data and analytics in the insurance industry, most recently serving as Chief Analytics Officer for AXIS Capital. Dr. Anzelc holds a Master’s and PhD in Physics from Northwestern University and a Bachelor’s in Physics from Loyola University Chicago. She is also on the board of the Chicago Literacy Alliance, a non-profit dedicated to the vision of a 100% literate Chicago.
Michele Ceru is a data engineer/data architect graduated from New York University with a master in data science. Previous to that he studied theoretical physics focusing on models of effective interaction to model the nuclear matter inside neutron stars at the Sapienza University of Rome in Italy. At ATD he works as a data architect building ETL processes to load data on Google Cloud Platform to support data science projects. He also studied classical piano music performance and still plays in his free time, switching from the laptop’s keyboard for work to the piano one for fun.
My work has included a number of positions and side projects that all advance the respect for human information. We work to raise awareness and create tools that promote quality, integrity, respect and asset level possibilities for information assets. I have a passion for building better technology that matters. I also work closely with families, executives, innovators and dreamers at all levels and in businesses & organizations at all stages to support the combination of policy, practice and tools.
Morgan is a Data Scientist working at ShopRunner. The company helps retailers band together in a time of free, fast shipping and large technical needs. Her Data Science projects there range from computer vision, color identification, to outfit recommendations. She has a varied background having worked in Biology, Software Engineering, and Machine Learning. She received a B.Sc. from UC San Diego in Computer Science with a specialization in Bioinformatics. She is passionate about cross-functional projects and making Data Science accessible for everyone who can benefit from it.
Dr. Nels is a clinical systems IT director at a fortune 10 company, the author of Graduation with Civic Honors, an avid writer, tech chaser, sports card collector, and a major TensorFlow enthusiast.
Sherin Mathews is a senior data scientist within the Office of the CTO for McAfee. In this role she creates and develops new machine learning models to improve and increase the effectiveness of cybersecurity products. Sherin is a repeated and requested industry speaker on her research papers in areas of signal and image processing, machine Learning, computer vision, artificial intelligence and cybersecurity. Prior to her role at McAfee, Sherin held research positions at Canon Inc. and Intel Corporation. Sherin has a BSEE degree, with honors, from the University of Mumbai and a MS in Electrical and Computer Engineering focused in Signal Processing and Wireless Communication from State University of New York, College at Buffalo. Additionally Sherin has a MSEE in Software Engineering & Signal Processing and a PhD in Machine Learning and Signal Processing from the University of Delaware. She is a past recipient of the University of Delaware Professional Development Award and received ninth place in the prestigious IEEE GRSS Data Fusion Contest. She has received numerous other awards for her outstanding performance across different projects and has several patents pending.
Qiaolin Chen, Director of Data Science Tencent Games, is a Ph.D. Data scientist with 10 years’ experience in machine learning and predictive modeling, specializing in Machine Learning, Big Data and AI. Qiaolin earned her Bachelor’s Degree from Peking University and Ph.D.’s Degree in Biostatistics from UCLA. Prior to joining Tencent, she worked as a Lead Data Scientist at an AI company in New York, providing data science solutions across industry for Fortune 500 companies, and as a Principal Statistician at Novartis. Qiaolin’s expertise is on major aspects of Data Science including machine learning, business intelligence, recommendation system, NLP and knowledge graph.
Ronak is a data leader with more than 10 years of experience in data related areas. At present, Ronak leads the Data Engineering group at Coursera, where his team is responsible for democratizing Coursera’s data for internal and external audiences to accomplish Coursera’s mission of transforming lives through learning. In addition, he has worked in various positions at several well-recognized growth companies like Amazon, Glassdoor, and Citrix. He holds a Master’s degree in Computer Science from the University of Southern California and passionate about giving back to the community.
Theresa Melvin, J.D., is the Global Chief Architect for HPE ’s A I -Driven Big Data Solutions , as well as the Big Data and AI Lead for HPE’s Open Source Profession. Ms. Melvin runs the Full Stack Data Science Lab, an arm of HPE ’s larger AI Lab, which falls under the company’s advanced research organization, Hewlett Packard Labs. In this role, Ms. Melvin works closely with the extreme -scale community to develop and incubate custom AI -Driven Solutions in order to accelerate innovation and growth for these strategic accounts
As Head of Data Science at Getty Images, Thomas Vicent utilizes data to optimize Getty Images’ understanding of the customer lifecycle and leads the organization in the use of data science and engineering across the business. An experienced statistician and data scientist, Thomas works with Getty Images’ Global Demand Generation, Digital Marketing and Sales teams to help maximize revenue, and ensure that both internal and third-party data are leveraged in the most appropriate and efficient way. Prior to this role, Thomas worked as a Senior Data Science Engineer & Technical lead at DigitalOcean where he was instrumental in overseeing a variety of machine learning based projects focused on Customer Service, Fraud Detection and Marketing/Sales. Thomas also worked as a Data Scientist at Dow Jones, where he designed customer-centric machine learning pipelines and created a customized search algorithm as a product to replace third-party tools. Thomas obtained a Ph.D. in Biostatistics from the University of Bristol, which was preceded by an MSci in Mathematics & Physics and an MRes in Complexity Sciences.
Vanitha considers herself to be a data and analytics philanthropist. Strongly believing in the power of data and analytics to serve the greater good; she is dedicating herself to raising awareness and influencing change on societal issues. Vanitha volunteers on the Board of Viz for Social Good and leads the Toronto chapter. Viz for Social Good works with mission driven organization to analyze their data and create informative and beautiful data visualizations.
Vanitha has a wealth of experience in Financial Services developing data strategies, delivering enterprise data management solutions and enabling business intelligence and analytics to drive business outcomes. She is currently Director, Retail Distribution Analytics and Data at CIBC.
Vin Vashishta has been recognized since 2015 as a top voice and expert in data science and machine learning. He’s been published in the mainstream Fast Company and Silicon Republic as well as industry specific KD Nuggets and Open Data Science. Before that I published on competitive analysis and intelligence. Vin has spoken at conferences, at business seminars and in academia for the last 7 years. Over 20 years of hands on and leadership roles in technology. The last 9 years in data science and machine learning. He has brought products to market with annual revenues in the $100s of millions. An applied data science and machine learning practitioner. He also teaches companies how to build machine learning capabilities and integrate the new technology into products and their business. He occasionally evaluates machine learning products for VCs and businesses.
Dr. Schulz is an Assistant Professor of Laboratory Medicine and computational health care researcher at Yale School of Medicine. He is the Director of Informatics for the Department of Laboratory Medicine, Director of the CORE Center for Computational Health, and Medical Director of Data Science for Yale New Haven Health System. He is responsible for managing the analytics infrastructure for Yale New Haven Health, the validation of clinical predictive models, and regulatory oversight for laboratory informatics. Dr. Schulz is also a founding member of the Association for Computational Health, which is focused on developing data models, tools, and best practices to support real-time clinical predictive modeling.