Full Machine Learning Week 8-Track Agenda 2020

Predictive Analytics World

May 31-June 4, 2020 – Caesars Palace, Las Vegas


This page shows the full 8-track agenda for the five co-located conferences at Machine Learning Week. A Machine Learning Week Ticket is required for full access. To view the agenda for one individual conference, click here: PAW Business, PAW Financial, PAW Healthcare, PAW Industry 4.0, or Deep Learning World.

Session Levels:

Blue circle sessions are for All Levels
Red triangle sessions are Expert/Practitioner Level

Pre-Conference Workshops - Sunday, May 31st, 2020

8:30 am
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

This one day workshop reviews major big data success stories that have transformed businesses and created new markets. Click workshop title above for the fully detailed description. 

Session description
Instructor
Marc Smith
Chief Social Scientist
Connected Action Consulting Group
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

Gain experience driving R for predictive modeling across real examples and data sets. Survey the pertinent modeling packages.  Click workshop title above for the fully detailed description. 

Session description
Instructor
Robert MuenchenUniversity of Tennessee
Manager of Research Computing Support
University of Tennessee
4:30 pm
End of Sunday Pre-Conference Training Workshops
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Pre-Conference Workshops - Monday, June 1st, 2020

8:30 am
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

This one-day session surveys standard and advanced methods for predictive modeling (aka machine learning). Click workshop title above for the fully detailed description. 

Session description
Instructor
John Elder Ph.D.Elder Research
Founder & Chair
Elder Research
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

This one-day introductory workshop dives deep. You will explore deep neural classification, LSTM time series analysis, convolutional image classification, advanced data clustering, bandit algorithms, and reinforcement learning. Click workshop title above for the fully detailed description. 

Session description
Instructor
James McCaffreyMicrosoft
Senior Scientist Engineer
Microsoft
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

Python leads as a top machine learning solution – thanks largely to its extensive battery of powerful open source machine learning libraries. It’s also one of the most important, powerful programming languages in general. Click workshop title above for the fully detailed description. 

Session description
Instructor
Clinton BrownleyWhatsApp
Data Scientist
WhatsApp
Pre-Conference Training Workshop

Full-day: 8:30am – 4:30pm

Machine learning improves operations only when its predictive models are deployed, integrated and acted upon – that is, only when you operationalize it.  Click workshop title above for the fully detailed description. 

Session description
Instructor
James TaylorDecision Management Solutions
CEO
Decision Management Solutions
4:30 pm
End of Monday Pre-Conference Training Workshops
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Day 1 - Tuesday, June 2nd, 2020

8:00 am
Registration
Networking Breakfast
Registration & Networking Breakfast
Registration & Networking Breakfast
Registration & Networking Breakfast
Registration
Networking Breakfast
8:45 am
PAW Business
Eric SiegelPredictive Analytics World
Conference Founder
Predictive Analytics World
PAW Financial
Eric SiegelPredictive Analytics World
Conference Founder
Predictive Analytics World
PAW Healthcare
Eric SiegelPredictive Analytics World
Conference Founder
Predictive Analytics World
PAW Industry 4.0
Eric SiegelPredictive Analytics World
Conference Founder
Predictive Analytics World
Deep Learning World
Eric SiegelPredictive Analytics World
Conference Founder
Predictive Analytics World
8:50 am
PAW Business MACHINE LEARNING WEEK KEYNOTE
Lessons from: Lyft
Speaker
Gil ArditiLyft
Product Lead, Machine Learning
Lyft
PAW Financial MACHINE LEARNING WEEK KEYNOTE
Lessons from: Lyft
Speaker
Gil ArditiLyft
Product Lead, Machine Learning
Lyft
PAW Healthcare MACHINE LEARNING WEEK KEYNOTE
Lessons from: Lyft
Speaker
Gil ArditiLyft
Product Lead, Machine Learning
Lyft
PAW Industry 4.0 MACHINE LEARNING WEEK KEYNOTE
Lessons from: Lyft
Speaker
Gil ArditiLyft
Product Lead, Machine Learning
Lyft
Deep Learning World MACHINE LEARNING WEEK KEYNOTE
Lessons from: Lyft
Speaker
Gil ArditiLyft
Product Lead, Machine Learning
Lyft
9:15 am
PAW Business MACHINE LEARNING WEEK KEYNOTE
Lessons from: Google
Speaker
Jen GennaiGoogle
Head of Responsible Innovation, Global Affairs
Google
PAW Financial MACHINE LEARNING WEEK KEYNOTE
Lessons from: Google
Speaker
Jen GennaiGoogle
Head of Responsible Innovation, Global Affairs
Google
PAW Healthcare MACHINE LEARNING WEEK KEYNOTE
Lessons from: Google
Speaker
Jen GennaiGoogle
Head of Responsible Innovation, Global Affairs
Google
PAW Industry 4.0 MACHINE LEARNING WEEK KEYNOTE
Lessons from: Google
Speaker
Jen GennaiGoogle
Head of Responsible Innovation, Global Affairs
Google
Deep Learning World MACHINE LEARNING WEEK KEYNOTE
Lessons from: Google
Speaker
Jen GennaiGoogle
Head of Responsible Innovation, Global Affairs
Google
10:00 am
Exhibits & Morning Coffee Break
Exhibits & Morning Coffee Break
Exhibits & Morning Coffee Break
Exhibits & Morning Coffee Break
Exhibits & Morning Coffee Break
10:30 am
PAW Business Track 1: BUSINESS - Operationalization, management and best practices
Digital decisioning
10:30 am - 10:50 am
Speaker
James TaylorDecision Management Solutions
CEO
Decision Management Solutions
Project leadership
10:55 am - 11:15 am
Lessons from: Cisco
Speaker
Jennifer RedmonCisco
Chief Data Evangelist
Cisco Systems, Inc
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Model explainability/interpretability
Speaker
Dean AbbottSmarterHQ
Co-Founder and Chief Data Scientist
SmarterHQ
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
Cross-enterprise applications
10:30 am - 10:50 am
Case study: Facebook
Speaker
Mohamed FawzyFacebook
Senior Software Engineering Lead - AI Infra
Facebook
Cross-enterprise applications
10:55 am - 11:15 am
Case study: Walmart Labs and Sam's Club
Speaker
Vinod SureshWalmart Labs
Director of Product Management
Walmart Labs
PAW Financial
Insurance applications
10:30 am - 10:50 am
Case study: ESIS
Speaker
Keith HigdonESIS
President
ESIS
Risk management
10:55 am - 11:15 am
Case study: Swiss Reinsurance Company
Speaker
Christian ElsasserSwiss Re
Manager Data Analytics
Swiss Reinsurance Company Ltd
PAW Healthcare
Case Study: Cedars-Sinai Medical Center
Speaker
Michael ThompsonCedars-Sinai Medical Center
Executive Director, Enterprise Data Intelligence
Cedars-Sinai Medical Center
PAW Industry 4.0 KEYNOTE
Speaker
Terry MillerSiemens
Global Digital Strategy and Business Development
Siemens
Deep Learning World KEYNOTE
Case Study: Standard Cognition
Speaker
Sean HendryxStandard Cognition
Machine Learning Engineer
Standard Cognition
11:15 am
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
11:20 am
PAW Business Track 1 - BUSINESS - Operationalization, management and best practices
Gaining stakeholder buy-in
11:20 am - 11:40 am
Lessons from: FedEx
Speaker
Clayton ClouseFedEx
Senior Data Scientist
FedEx
Pitfalls and best practices
11:45 am - 12:05 pm
Speaker
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Machine learning automation
Case study: Facebook
Speaker
Clinton BrownleyWhatsApp
Data Scientist
WhatsApp
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
Analytics in retail
11:20 am - 11:40 am
Case study: Walmart
Speaker
Hamza FarooqWalmart Labs
Principal Data Scientist
Walmart Labs
Marketing applications; reinforcement learning
11:45 am - 12:05 pm
Case study: Samsung
Speaker
Venkata PakkalaSamsung
Staff Data Scientist
Samsung
PAW Financial
Long-term risk management
11:20 am - 11:40 am
Case study: Safety National Casualty
Speakers
Carrie Lu Ph.D.Safety National Casualty Corporation
Senior Data Scientist
Safety National Casualty Corporation
William WIlkinsSafety National Casualty Corporation
Chief Risk and Data Analytics Officer
Safety National Casualty Corporation
Real-time architecture (streaming analytics)
11:45 am - 12:05 pm
Case study: ING
Speaker
Bas GeerdinkAizonic
CTO
Aizonic
PAW Healthcare
Case Study: Mayo Clinic
Speakers
Todd DeweesMayo Clinic
Associate Professor of Biostatistics, Radiation Oncology
Mayo Clinic
Michael GolafsharMayo Clinic
Statistical Programmer Analyst
Mayo Clinic
PAW Industry 4.0
Speaker
Rajagopalan ChandrasekharanGE Global Research
Senior Engineer
General Electric
Deep Learning World Track 1: Techniques and Results
Case Study: Facebook
Speaker
Jason GauciFacebook
Engineering Manager
Facebook
Deep Learning World Track 2: Large Scale Deployed Deep Learning
Case Study: Walmart Labs
Speaker
Chhavi YadavWalmart Labs
Data Scientist
Walmart Labs
12:05 pm
Lunch
Lunch
Lunch
Lunch
Lunch
1:30 pm
PAW Business SPECIAL PLENARY SESSION
Speaker
John Elder Ph.D.Elder Research
Founder & Chair
Elder Research
PAW Financial KEYNOTE
Lessons from: Manulife
Speaker
Richard LeeManulife
Director of Data Science, US EOIT Advanced Analytics & AI
Manulife
PAW Healthcare KEYNOTE
Speaker
Taylor DavisKLAS
VP of Research
KLAS
PAW Industry 4.0 SPECIAL PLENARY SESSION
Speaker
John Elder Ph.D.Elder Research
Founder & Chair
Elder Research
Deep Learning World Track 1: Techniques and Results
Case Study: LinkedIn
Speakers
Sandeep JhaLinkedIn
Staff Technical Program Manager
LinkedIn
Jun JiaLinkedIn
Senior Staff Software Engineer
LinkedIn
Deep Learning World Track 2: Large Scale Deployed Deep Learning
Case Study: Genesys Telecommunication Labs
Speaker
Anthony AlfordGenesys
Lead Software Engineer
Genesys
2:35 pm
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
2:40 pm
PAW Business Track 1: BUSINESS - Operationalization, management and best practices
Cross-enterprise management
2:40 pm - 3:00 pm
Lessons from: Google
Speaker
Richard DuttonGoogle
Head of Machine Learning for Corporate Engineering at Google
Google
Cross-enterprise management
3:05 pm - 3:25 pm
Lessons from: LinkedIn
Speaker
Priyanka GaribaLinkedIn
Head of Artificial Intelligence Technical Program Management
LinkedIn
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Uplift modeling, marketing analytics
Case study: Sam's Club
Speaker
Markus DmytrzakSam’s Club
Director, Advanced Analytics and Decision Sciences
Sam's Club
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
Product recommendations, analytics in the entertainment industry
2:40 pm - 3:00 pm
Case study: Fadango
Speaker
Reeto MookherjeeFandango
Vice President, Data, Analytics and Business Intelligence
Fandango
ML in AdTech
3:05 pm - 3:25 pm
Case study: 33Across and SOVRN
Speaker
Allen YuLineate
Director of AI
Lineate
PAW Financial
Operationalization
2:40 pm - 3:00 pm
Case study: Donnelley Financial Solutions
Speaker
Naveed AsemDonnelley Financial Solutions
Chief Data and Analytics Officer
Donnelley Financial Solutions
Transaction analytics, ML for audit support
3:05 pm - 3:25 pm
Speaker
Leslie BarrettBloomberg
Senior Software Engineer
Bloomberg LP
PAW Healthcare
Reinventing Primary Care Medicine
Speaker
Vickie RiceCareATC, Inc.
Vice President of Innovative Strategies
CareATC, Inc.
Deep Learning World Track 1: Techniques and Results
Case Study: Shell
Speaker
Mohamed SidahmedShell Oil Company
Machine Learning and AI Manager
Shell
Deep Learning World Track 2: Large Scale Deployed Deep Learning
Case Study: eBay
Speaker
Kumaresan ManickavelueBay
Sr. Product Manager, NLP
eBay
3:25 pm
Exhibits & Afternoon Break
Exhibits & Afternoon Break
Exhibits & Afternoon Break
Exhibits & Afternoon Break
Exhibits & Afternoon Break
3:55 pm
PAW Business Track 1 - BUSINESS - Operationalization, management and best practices
Analytics strategy
3:55 pm - 4:15 pm
Lessons from: Freewheel, A Comcast Company
Speaker
Bob BressComcast Cable
Vice President of Analytics & Business Intelligence
Freewheel, A Comcast Company
Project leadership
4:20 pm - 4:40 pm
Speaker
Robert Grossman
Managing Partner
Analytic Strategy Partners LLC
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Uplift modeling, marketing analytics
Case study: CVS
Speaker
John GaoWorkHuman
Senior Manager
WorkHuman
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
Cybersecurity applications
3:55 pm - 4:15 pm
Case study: McAfee
Speaker
Celeste FralickMcAfee
Chief Data Scientist, Senior Principal Engineer
McAfee
Building data science capacity
4:20 pm - 4:40 pm
Case study: Canada Energy Regulator
Speaker
Shingai ManjengwaFireside Analytics
Chief Executive Officer
Fireside Analytics Inc.
PAW Financial
Risk management
3:55 pm - 4:15 pm
Case study: Bloomberg
Speaker
Alex SanchezBloomberg
Global Head of Risk Strategy and Analytics
Bloomberg
Algorithmic trading
4:20 pm - 4:40 pm
Cse study: Bloomberg
Speaker
Chakri CherukuriBloomberg
Senior Quantitative Researcher
Bloomberg
PAW Healthcare
Case Study: Eli Lilly and Company
Speaker
Yu ChenEli Lilly & Company
Research Advisor
Eli Lilly & Company
PAW Industry 4.0 KEYNOTE
Speaker
Andrei KhurshudovCaterpillar
Director, Advanced Analytics
Caterpillar Digital
Deep Learning World Track 1: Techniques and Results
Case study: REI Systems
Speakers
Zulfiqar AhmedREI Systems
REI Systems
Nikolay SorokinREI Systems
Data Scientist
REI Systems
Deep Learning World Track 2: Large Scale Deployed Deep Learning
Case Study: Facebook
Speaker
Manoj Kumar KrishnanFacebook
Software Engineer and Tech Lead
Facebook
4:40 pm
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
4:45 pm
PAW Business Track 1: BUSINESS - Operationalization, management and best practices
Management
4:45 pm - 5:05 pm
Lessons from: Xerox PARC
Speaker
Mark CramerPARC, a Xerox Company
Applied AI Product Management
Xerox at PARC
Analytics culture and leadership
5:10 pm - 5:30 pm
Lessons from: AppFolio
Speaker
Michael GaltressAppfolio
Director, Business Analytics & Insights
Appfolio
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Uplift modeling, marketing analytics
Lessons from: Fidelity
Speaker
Victor LoFidelity Investments
AI and Data Science Center of Excellence Leader, Workplace Investing
Fidelity Investments
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
Customer feedback, text analytics
Case study: Google
Speaker
Peter GrabowskiGoogle
Software Engineering Manager
Google
PAW Financial
Algorithmic trading
Case study: Goldman Sachs
Speakers
Andreas PetridesGoldman Sachs
Quantitative Researcher
Goldman Sachs
Michael SteliarosGoldman Sachs
Managing Director
Goldman Sachs
PAW Healthcare
Case Study: Blood Supply Management and Forecasting
Speakers
Kelley CountsOneBlood
Data Scientist
OneBlood
Karl RexerRexer Analytics
President
Rexer Analytics
Deep Learning World Track 1: Techniques and Results
Case study: DeepScale (a Tesla company)
Speaker
Ilke DemirDeepScale (a Tesla company)
Senior Research Scientist
DeepScale (a Tesla company)
Deep Learning World Track 2: Large Scale Deployed Deep Learning
Case Study: Adobe
Speaker
Piyush ChandraAdobe Systems
Sr. Product Manager, Conversational Automation
Adobe
5:30 pm
Networking Reception
Networking Reception
Networking Reception
Networking Reception
Networking Reception
7:00 pm
End of first Conference Day
End of first Conference Day
End of first Conference Day
End of first Conference Day
End of first Conference Day
Day 2 - Wednesday, June 3rd, 2020

8:00 am
Registration
Networking Breakfast
Registration & Networking Breakfast
Registration & Networking Breakfast
Registration & Networking Breakfast
Registration & Networking Breakfast
8:45 am
PAW Business KEYNOTE
Lessons from: GM
Speaker
A Charles ThomasGeneral Motors - GM
Chief Data & Analytics Officer
General Motors
PAW Financial
Mei Najim
CSPA, Founder and Lead Data Scientist
Advanced Analytics Consulting Services, LLC
PAW Healthcare
Jeff DealElder Research
Chief Operating Officer
Elder Research
PAW Industry 4.0 KEYNOTE
Lessons from: GM
Speaker
A Charles ThomasGeneral Motors - GM
Chief Data & Analytics Officer
General Motors
Deep Learning World
Luba Gloukhova
Consultant & Speaker
8:55 am
 
PAW Financial KEYNOTE
Lessons from: Fidelity
Speaker
Victor LoFidelity Investments
AI and Data Science Center of Excellence Leader, Workplace Investing
Fidelity Investments
PAW Healthcare KEYNOTE
Speaker
John Elder Ph.D.Elder Research
Founder & Chair
Elder Research
 
Deep Learning World Track 1: Techniques and Results
Case Study: Samsung
Speaker
Lin SunSamsung
Head of Perception
Samsung
10:00 am
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
10:05 am
PAW Business Track 1 - BUSINESS - Operationalization, management and best practices
10:05 am - 10:25 am
Speaker
Michael SimonCIA
Chief of Analytics
CIA
Presenting modeling results
10:30 am - 10:50 am
Lessons from: ConstantContact
Speaker
Kristen KehrerData Moves Me
Founder
Data Moves Me
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Model explainability
Case study: Paychex
Speaker
Satish PrabhuPaychex
Data Scientist
Paychex
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
ML for social good
10:05 am - 10:25 am
Speaker
Anasse Bari Ph.D.New York University
Clinical Assistant Professor of Computer Science
New York University
PAW Financial
Project management
10:05 am - 10:25 am
Case study: Wells Fargo
Speaker
Nathan SusanjWells Fargo
Vice President, Data Science Manager
Wells Fargo
Enterprise deployment
10:30 am - 10:50 am
Speaker
Sravan KasarlaThrivent
Chief Data Office
Thrivent
PAW Healthcare
Case Study: NorthShore University Health System
Speaker
Daniel Chertok PhDNorthShore University HealthSystem
Sr. Data Scientist
NorthShore University HealthSystem
PAW Industry 4.0
Speaker
Samira GolsefidPayPal
Principal Data Scientist
PayPal Inc.
Deep Learning World Track 1: Techniques and Results
Case Study: Verizon
Speakers
Bryan Larish Ph.D.Verizon
Director of Technology
Verizon
Said SoulhiVerizon
Distinguished Member of the Technical Staff
Verizon
10:50 am
Exhibits & Morning Coffee Break
Exhibits & Morning Coffee Break
Exhibits & Morning Coffee Break
Exhibits & Morning Coffee Break
Exhibits & Morning Coffee Break
11:20 am
PAW Business Track 1: BUSINESS - Operationalization, management and best practices
Algorithmic fairness; ethics
11:20 am - 11:40 am
Speaker
Natalia ModjeskaInfo-Tech Research Group
Director, Research, DnA (Data & Analytics)
Info-Tech Research Group
Algorithmic fairness; ethics
11:45 am - 12:05 pm
Case study: Canada Post
Speaker
Allan SammyCanada Post
Director, Data Science and Audit Analytics
Canada Post
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Modeling methods
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
Churn modeling
11:20 am - 12:05 pm
Speaker
Gilad BarashDstillery
VP of Analytics
Dstillery
Churn modeling
11:45 am - 12:05 pm
Case study: Wix
Speaker
Gil ReichWix
Data Developer
Wix
PAW Financial
The cyborg effect
11:20 am - 11:40 am
Speaker
Richard BoireEnvironics Analytics
Senior Vice President
Environics Analytics
Financial applications; transactional data
11:45 am - 12:05 pm
Case study: Visa
Speaker
Abhishek Joshi ‘AJ’Visa
Senior Director
Visa Consulting & Analytics
PAW Healthcare
Cancer Prediction
Speaker
Bob NisbetUniversity of California, Irvine Extension
Instructor
University of California, Irvine
Deep Learning World Track 1: Techniques and Results
Case Study: The Vanguard Group
Speaker
Vishal HawaThe Vanguard Group
Principal Scientist
The Vanguard Group
12:05 pm
Lunch
Lunch
Lunch
Lunch
Lunch
1:15 pm
PAW Business KEYNOTE
Lessons from: Kennesaw State University
Speaker
Jennifer Lewis PriestleyKennesaw State University
Professor of Applied Statistics and Data Science
Kennesaw State University
PAW Financial
Client transaction optimization
Case study: Charles Schwab
Speaker
Jodi BlombergCharles Schwab
Managing Director, Enterprise Analytics
Charles Schwab
PAW Healthcare
Deep Learning World Track 1: Techniques and Results
Case Study: Nike
Speaker
James NormanNike
Lead Software Engineer
Nike
2:10 pm
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
 
2:15 pm
PAW Business
Moderator
James TaylorDecision Management Solutions
CEO
Decision Management Solutions
PAW Financial
Moderator
Mei Najim
CSPA, Founder and Lead Data Scientist
Advanced Analytics Consulting Services, LLC
PAW Healthcare
Case Study: West African Ebola Outbreak
Speaker
Colleen Farrelly
Co-Founder & Chief Scientist
Quantopo LLC
Deep Learning World Track 1: Techniques and Results
Case Study: eBay Corporation
Speaker
Navid ImanieBay
Applied Researcher
eBay
3:00 pm
Exhibits & Afternoon Break
Exhibits & Afternoon Break
Exhibits & Afternoon Break
Exhibits & Afternoon Break
Exhibits & Afternoon Break
3:30 pm
PAW Business Track 1 - BUSINESS - Operationalization, management and best practices
Industry/University Partnerships
3:30 pm - 3:50 pm
Lessons from: Hanesbrand
Speakers
Haya AjjanElon University
Associate Professor of MIS, Director of the Center for Organizational Analytics,
Elon University
Ben Martin Ph.D.Hanes
Chief Data Analytics Officer
Hanesbrands Inc
Team building
3:55 pm - 4:15 pm
Lessons from: MINDBODY, Inc
Speaker
Charlie LewisMINDBODY
Senior Manager, Business Intelligence
MINDBODY, Inc
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Data engineering
Case study: Google
Speaker
Karl WeinmeisterGoogle
Developer Advocacy Manager
Google
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
Workforce analytics
3:30 pm - 3:50 pm
Case study: Bristol-Myers Squibb
Speakers
Jason FelicianoBristol-Myers Squibb
Associate Director of HR Analytics
Bristol-Myers Squibb
Emma VazirabadiBristol-Myers Squibb
Associate Director of People Insights & HR Analytics
Bristol-Myers Squibb
Workforce analytics
3:55 pm - 4:15 pm
Case study: Mercer
Speaker
Haig NalbantianMercer
Senior Partner, Co-leader Mercer Workforce Sciences Institute
Mercer
PAW Financial
Portfolio analytics; data sources
Speaker
Anasse Bari Ph.D.New York University
Clinical Assistant Professor of Computer Science
New York University
PAW Healthcare
3:30pm - 3:50pm
Addressing Bias
Speaker
Zeydy Ortiz
CEO
DataCrunch Lab
3:55pm - 4:15pm
Child Behavioral Healthcare
Speaker
Halim AbbasCognoa
Vice President of Data Science
Cognoa
Deep Learning World Track 1: Techniques and Results
Case Study: Verizon
Speaker
Shams ZamanVerizon
Principal Data Scientist
Verizon
4:15 pm
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
5-minute transition between sessions
4:20 pm
PAW Business Track 1: BUSINESS - Operationalization, management and best practices
Data management and data preparation
4:20 pm - 4:40 pm
Lessons from: BP
Speaker
Cetin Karakus
Global Head of Quant Technology and Analytics Core Strategies
BP
Pitfalls and best practices
4:45 pm - 5:05 pm
Lessons from: Caesars Entertainment
Speaker
Josh FrankCaesars Entertainment
Vice President-Gaming Data Science & Fraud Analytics
Caesars Entertainment
PAW Business Track 2 - TECH - Machine learning methods & advanced topics
Modeling methods
4:20 pm - 4:40 pm
Case study: Cisco
Speaker
Kumaran PonnambalamCisco
Analytics Architect
Cisco Systems, Inc
Data preparation
4:45 pm - 5:05 pm
Case study: Dow Chemical
Speaker
Paul SpeakerThe Dow Chemical Company
Senior Data Scientist
The Dow Chemical Company
PAW Business Track 3 - CASE STUDIES - Cross-industry business applications of machine learning
Consumer reimbursement claims
4:20 pm - 4:40 pm
Case study: GIVT (EU flight claims)
Speaker
Piotr Wygocki Ph.D.MIM Solutions
​Co-founder
MIM Solutions
Supply chain management
4:45 pm - 5:05 pm
Case study: ChannelAdvisor
Speaker
Kevin FeaselChannelAdvisor
Engineering Manager, Predictive Analytics
ChannelAdvisor
PAW Financial
Credit scoring
Case study: Vision Fund International
Speaker
Aric LaBarrInstitute for Advanced Analytics at NC State University
Associate Professor of Analytics
Institute for Advanced Analytics at NC State University
PAW Healthcare
Case Study: Capital District Physicians’ Health Plan
Speaker
Matthew PietrzykowskiCapital District Physicians’ Health Plan
Principal Data Scientist
Capital District Physicians' Health Plan
PAW Industry 4.0
Speaker
Rohit KewalramaniKPIT Technologies
Data Scientist
KPIT Technologies
Deep Learning World Track 1: Techniques and Results
Case Study: Google
Speaker
Patrick MillerGoogle
Software Engineering Manager
Google
5:05 pm
End of second Conference Day
End of second Conference Day
End of second Conference Day
End of second Conference Day
End of second Conference Day
CloseSelected Tags:

Post-Conference Workshops - Thursday, June 4th, 2020

8:30 am
Post-Conference Training Workshop

Full-day: 8:30am – 4:30pm

This one-day session reveals the subtle mistakes analytics practitioners often make when facing a new challenge (the “deadly dozen”), and clearly explains the advanced methods seasoned experts use to avoid those pitfalls and build accurate and reliable models.  Click workshop title above for the fully detailed description.

Session description
Instructor
John Elder Ph.D.Elder Research
Founder & Chair
Elder Research
Post-Conference Training Workshop

Full-day: 8:30am – 4:30pm

Gain the power to extract signals from big data on your own, without relying on data engineers and Hadoop specialists. Click workshop title above for the fully detailed description.

Session description
Instructor
James Casaletto
PhD Candidate
UC Santa Cruz Genomics Institute and former Senior Solutions Architect, MapR
Post-Conference Training Workshop

Full-day: 8:30am – 4:30pm

This workshop dives into the key ensemble approaches, including Bagging, Random Forests, and Stochastic Gradient Boosting. Click workshop title above for the fully detailed description.

Session description
Instructor
Dean AbbottSmarterHQ
Co-Founder and Chief Data Scientist
SmarterHQ
Post-Conference Training Workshop

Full-day: 8:30am – 4:30pm

During this workshop, you will gain hands-on experience deploying deep learning on Google’s TPUs (Tensor Processing Units) at this one-day workshop, scheduled the day immediately after the Deep Learning World and Predictive Analytics World two-day conferences.  Click workshop title above for the fully detailed description.

Session description
4:30 pm
End of Post-Conference Training Workshops
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