

Day by Day Guide to ODSC West 2019
ConferencesWest 2019posted by ODSC Team October 21, 2019 ODSC Team

Next week is ODSC West 2019 in San Francisco and it’s time to start planning your schedule in earnest. With 300+ hours of content and 100+ trainings and workshops led by our expert speakers ranging in level from beginner to advanced, we know it can be difficult to choose which sessions to attend. To facilitate this process, and provide the best possible conference experience, we’ve created recommended schedules for several different pathways based on your experience, interests, and goals.
[Read all of the articles from ODSC West 2019 speakers here!]
Newbie: (citizen data scientist)
You:
- Want in on “the sexiest job of the 21st century”
- Already know math and numbers but want to use it in a new way
- Are a programmer/analyst ready for your next adventure
- Are a student or recent graduate wondering if data science is right for you
Oct 29
9:00-1:00 | Half-Day Training: Introduction to Machine Learning with Andreas Mueller, PhD
—
2:00-6:00 | Half-Day Training: Intermediate Machine Learning with Scikit-learn with Andreas Mueller, PhD
Oct 30
9:00-1:00 | Half-Day Training: Advanced Machine Learning with Scikit-learn, Part I with Andreas Mueller, PhD
OR
9:00-1:00 | Half-Day Training: Adapting Machine Learning Algorithms to Novel Use Cases with Dr. Kirk Borne
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2:00-6:00 | Half-Day Training: Advanced Machine Learning with Scikit-learn, Part II with Andreas Mueller, PhD
OR
2:00-6:00 | Half-Day Training: From Numbers to Narrative: Turning Raw Data into Compelling Stories with Impact with Bill Shander
Oct 31
Keynotes until 10:30
—
11:00-11:45 | Talk: Model-based Learning and Optimization with Emo Todorov, PhD
and
12:00-12:45 | Talk: Machine Learning (ML) on Devices: Beyond the Hype with Divya Jain
OR
11:00-12:30 | Workshop: Machine Learning Interpretability Toolkit with Mehrnoosh Sameki, PhD
—
2:00-2:45 | Talk: Learning from Small Datasets (Few Shot Learning) with Veysel Kocaman, PhD
and
3:00-3:45 | Talk: Simplified Data Preparation for Machine Learning in Hybrid and Multi Clouds with Bin Fan, PhD
OR
2:00-3:30 | Workshop: MLOps: ML Engineering Best Practices from the Trenches with Sourav Dey, PhD
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4:15-5:00 | Talk: AI Research at Bloomberg with Dr. Anju Kambadur
and
5:15-6:00 | Talk: Help! My Classes are Imbalanced! with Samuel Taylor
OR
4:00-5:30 | Workshop: Declarative Data Visualization with Vega-Lite & Altair Kanit Wongsuphasawat, PhD
Nov 1
11:00-11:45 | Talk: Making the Best Possible Decisions with Evolutionary AI by Babak Hodjat, PhD
and
12:00-12:45 | Talk: When Your Big Data Seems Too Small: Accurate Inferences Beyond the Empirical Distribution with Gregory Valiant, PhD
OR
11:00-12:30 | Workshop: Building an Industry Classifier with the Latest Scraping, NLP and Deployment Tools with Ido Shlomo
—
2:00-2:45 | Talk: Scientific Annotation: Using Graphs to Facilitate Interdisciplinary Science with Simon Goring, PhD
and
3:00-3:45 | Talk: Causal Inference in E-Commerce Search: Tackling Small Data Challenge with Natural Experiments by Liang Wu, PhD
and
4:00-4:45 | Talk: Community-Specific AI: Building Solutions for Any Audience with Jonathan Purnell, PhD
OR
2:00-3:30 | Workshop: Causal Inference for Data Science with Vinod Bakthavachalam
and
3:45-5:15 | Workshop: Optuna: A Define-by-Run Hyperparameter Optimization Framework with Crissman Loomis
Deep Learning Enthusiast
You:
- Entry level data scientists come to you for help
- You’ve mastered machine learning and are ready to see if the hype behind reinforcement learning is real
- Data science is a lifestyle, not a job
Oct 29
9:00-1:00 | Half-Day Training: Understanding the PyTorch Framework with Applications to Deep Learning with Robert Alvarez, PhD
—
2:00-6:00 | Full-Day Training: Hands-On Introduction to LSTMs in Keras/TensorFlow with Lukas Biewald, Chris Van Pelt, and Stacey Svetlichnaya
Oct 30
9:00-1:00 | Half-Day Training: Deep Learning (with TensorFlow 2.0) with Dr. Jon Krohn
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2:00-6:00 | Half-Day Training: Reinforcement Learning with TF-Agents & TensorFlow 2.0: Hands On by Oliver Zeigermann and Christian Hidber, PhD
Oct 31
Keynotes until 10:30
—
11:00-11:45 | Talk: Model-based Learning and Optimization by Emo Todorov, PhD
and
12:00-12:45 | Talk: Troubleshooting Deep Neural Networks with Josh Tobin, PhD
OR
11:00 -12:30 | Workshop: Spark NLP: State of the Art Natural Language Processing at Scale by David Talby, PhD
—
2:00-2:45 | Talk: Incorporating Intent Propensities in Personalized Next Best Action Recommendation with Kexin Xie
and
3:00-3:45 | Talk: Visual Search on Hayneedle by Bugra Akyildiz
OR
2:00-3:30 | Workshop: How to Build a Recommendation Engine That Isn’t Movielens with Max Humber
—
4:15-5:00 | Talk: How Advanced Hyperparameter Optimization Drives Performance without Compromising Privacy with Scott Clark, PhD
and
5:15-6:00 | Talk: Mining “Concept Embeddings” from Open-Source Data to Classify Previously Unseen Log Messages with David Nellinger Adamson, PhD
OR
4:00-5:30 | Workshop: Pomegranate: Fast and Flexible Probabilistic Modeling in Python with Jacob Schreiber
Nov 1
Keynotes until 10:30
—
11:00-11:45 | Talk: EMI: Embed, Measure and Iterate with Mayank Kejriwal, PhD
and
12:00-12:45 | Talk: Combining Word Embeddings with Knowledge Engineering with Sanjana Ramprasad
OR
11:00-12:30 | Workshop: Data Harmonization for Generalizable Deep Learning Models: from Theory to Hands-on Tutorial with Gerald Quon, PhD and Nelson Johansen
—
2:00-2:45 | Talk: Planetary Scale Location-based Insights with Gopal Erinjippurath
and
3:00-3:45 | Talk: Lessons Learned Deploying a Deep Learning Visual Search Service at Scale with Scott Cronin, PhD
and
4:00-4:45 | Talk: Creating an Extensible Big Data Platform to Serve Data Scientists and Analysts – 100s of PetaBytes with Real-Time Access by Reza Shiftehfar, PhD
OR
2:00-3:30 | Workshop: Tutorial on Deep Reinforcement Learning with Pieter Abbeel, PhD
and
3:45-5:15 | Workshop: Tutorial on Deep Reinforcement Learning with Pieter Abbeel, PhD
The Decision Maker (aka XAI)
You:
- Your unofficial title is data science translator
- Your company is falling behind the AI race and it’s time to catch up
- You think “AI is neat” and now have to prove it to your boss
- Dirty text: You think hiring a data scientist can help increase revenue
Oct 29
9:30-10:05 | Keynote: Title Coming Soon! with Cassie Kozyrkov, PhD
—
10:05-10:40 | Keynote: Accelerate AI: Moving AI Off Your Roadmap and Into Your Products with Ashok Srivastava, PhD
—
11:10-11:40 | Talk: Establishing a Data and Analytics Organization with Shanthi Iyer
OR
11:10-11:40 | Talk: Enterprise Adoption of Reinforcement Learning with Dr. Ganapathi Pulipaka
—
11:50-12:20 | Talk: Robots Learning Dexterity: Robots That Learn with Peter Welinder, PhD
OR
11:50-12:20 | Talk: Designing A User-Centric AI Product with Katie Malone, PhD and Annie Darmofal
—
1:30-2:00 | Talk: Challenges of Digital Transformation and AI with Rashed Haq, PhD
OR
1:30-2:00 | Talk: Identifying and Labeling Fraudulent Store Return Activities with Henry Chen, PhD, Vidhya Raman, and Jingru Zhou, PhD
—
2:10-2:40 | Talk: Scaling 200B+ Pins Using a Mix of Machine Learning and Human Curation with Chuck Rosenberg, PhD
OR
2:10-2:40 | Talk: Race Your Facts: Making AI Work for Enterprises with Rama Akkiraju
—
2:50-3:20 | Talk: Accelerating AI-Driven Innovation in Your Enterprise with Pallav Agrawal
OR
2:50-3:20 | Talk: Sources of Bias: Strategies for Tackling Inherent Bias in AI with Harry Glaser
—
3:50-4:20 | Talk: On AI ROI: The Questions You Need to Be Asking with Kerstin Frailey
OR
3:50-4:20 | Talk: AI in Healthcare: the State of Adoption with Alex Ermolaev
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4:30-5:00 | Talk: Building AI Products: Delivery Vs Discovery with Charles Martin, PhD
OR
4:30-5:00 | Talk: Transaction Data Enrichment – an Opportunity for Business Growth and Risk Mitigation with Pramod Singh, PhD
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5:10-5:40 | Talk: Bringing AI Out of the Lab and Into Production with Irina Farooq
OR
5:10-5:40 | Talk: Weaponizing Distraction: How to Use Analytics on Call Rotations for Improving Team Focus, Onboarding New Employees, and Making Space for Career Growth with Katie Bauer
Oct 30
9:30-10:05 | Keynote: Title Coming Soon! with Dr. Anand S Rao
—
10:05-10:40 | Keynote: Title Coming Soon! with Michael I. Jordan, PhD
—
11:10-11:40 | Talk: Scaling Computer Vision in the Cloud and AI Chips with Reza Zadeh, PhD
OR
11:50-12:20 | Talk: From R&D to ROI: Realize Value by Operationalizing Machine Learning with Diego Oppenheimer
—
11:50-12:20 | Talk: Developing Machine Learning-Driven Customer-Facing Product Features with Marsal Gavalda, PhD
OR
11:50-12:20 | Talk: Harnessing AI: Data Evangelism Must Be Data-Driven with Jennifer Redmon
—
1:30-2:00 | Talk: Data-Driven Approaches to Forecasting with Javed Ahmed, PhD
OR
1:30-2:00 | Talk: The Last Frontier of Machine Learning – Data Wrangling with Alex Holub, PhD
—
2:10-2:40 | Talk: Why We Should Hire More Analysts for Data Science Teams with Benn Stancil
OR
2:10-2:40 | Talk: An Introduction to AI’s Impact in the Life Sciences with Mark DePristo
—
2:50-3:20 | Talk: Natural Language Processing: Deciphering the Message within the Message – Stock Selection Insights using Corporate Earnings Calls with Frank Zhao
OR
2:50-3:20 | Talk: Data Literacy and Democratization of Data in the 4th Industrial Revolution with Jacob Dockendorf
—
3:50-4:20 | Talk: AI in Medicine: Avoiding Hype and False Conclusions with Michael Zalis, MD
OR
3:50-4:20 | Talk: The Great Voice Migration: How Voice Will Make the Leap from Consumer to Enterprise with Omar Tawakol
—
4:30-5:00 | Talk: Building a Center of Excellence for Data Science with Michael Xiao
OR
4:30-5:00 | Talk: Beyond Conventional AI—Proven in Space, Now Available on Earth with Giovanni Gentile
—
5:10-5:40 | Talk: From Silos to Platform: Building Twitter’s Feature Marketplace with Wolfram Arnold, PhD
OR
5:10-5:40 | Talk: Deployment of Strategic AI in the Enterprise with Dr. Fernando Nunez-Mendoza
Senior Data Scientist / Researcher
- You print out articles from ArXiv.org and keep them in your briefcase
- You fondly remember when you had to compete in kaggle competitions
- Coding is still fun for you
- You need an excuse to stay in-the-loop with the latest frameworks and languages
Oct 29
9:00-1:00 | Full-Day Training: Hands-On Introduction to LSTMs in Keras/TensorFlow with Lukas Biewald, Chris Van Pelt, and Stacey Svetlichnaya
—
2:00-6:00 | Full-Day Training: Hands-On Introduction to LSTMs in Keras/TensorFlow with Lukas Biewald, Chris Van Pelt, and Stacey Svetlichnaya
Oct 30
9:00-1:00 | Tutorial: Deep Implicit Learning with Laurent El Ghaoui, PhD
—
| Workshop: Deciphering the Black Box: Latest Tools and Techniques for Interpretability with Rajiv Shah, PhD
Oct 31
Keynotes until 10:30
—
11:00-12:30 | Workshop: Advanced Methods for Explaining XGBoost Models with Brian Lucena, PhD
—
2:00-2:45 | Talk: Deploying AI for Near Real-Time Engineering Decisions with Heather Gorr, PhD
—
3:00-3:45 | Talk: Coming soon! with Sudeep Pillai, PhD
—
4:15-5:00 | Talk: AI Research at Bloomberg with Dr. Anju Kambadur
—
5:15-6:00 | Talk: AutoML at Scale: Integrating Data as Part of Hyperparameter Optimization with Moses Guttmann
Nov 1
Keynotes until 10:30
—
11:00-11:45 | Talk: Quantamental Factor Investing Using Alternative Data and Machine Learning with Arun Verma, PhD
—
12:00-12:45 | Talk: Advanced Techniques in Natural Language Understanding with FakeNews Use Cases by Michael Tamir, PhD and Jacob Baumbach
—
2:00-3:30 | Workshop: Causal Inference for Data Science with Vinod Bakthavachalam
—
3:45-5:15 | Tutorial: The Robustness Problem with Justin Gilmer, PhD
The AI Engineer
You:
- Were a software engineer in a past life
- Want to work on self-driving cars and robots
- Are ready to be an innovator
- You want to see how Google, Facebook, and Uber get ahead
Oct 29
9:00-1:00 | Half-Day Training: Programming with Data: Foundation of Python & Pandas with Daniel Gerlanc
—
2:00-6:00 | Half-Day Training: Scalable Machine Learning with Kubernetes and Kubeflow by John Tate
Oct 30
9:00-1:00 and 2:00-6:00 | Full-Day Training: Introduction to Deep Learning for Engineers with Lukas Biewald, Chris Van Pelt, and Stacey Svetlichnaya
Oct 31
Keynotes until 10:30
—
11:00-11:45 | Talk: Model-based Learning and Optimization with Emo Todorov, PhD
—
12:00-12:45 | Talk: Machine Learning (ML) on Devices: Beyond the Hype with Divya Jain
—
2:00-2:45 | Talk: Deploying AI for Near Real-Time Engineering Decisions with Heather Gorr, PhD
—
3:00-3:45 | Talk: Scaling Machine Learning from 0 to Millions of Users with Shashank Prasanna
—
4:00-5:30 | Workshop: Pomegranate: Fast and Flexible Probabilistic Modeling in Python with Jacob Schreiber
Nov 1
Keynotes until 10:30
—
11:00 – 11:45 | Talk: diff software_dev software_dev*ai with Jana Eggers
—
12:00-12:45 | Talk: Combining Word Embeddings with Knowledge Engineering by Sanjana Ramprasad
—
2:00-2:45 | Talk: Building Modern ML/AI Pipelines with the Latest Open Source Technologies with Chris Fregly
—
3:00-3:45 | Talk: Product Search in E-Commerce: What to Optimize? with Liang Wu, PhD
—
4:00-4:45 | Talk: Looking from Above: Object Detection and Other Computer Vision Tasks on Satellite Imagery with Xiaoyong Zhu
In just a few days thousands of data scientists will come together to learn, connect, and be inspired. We hope that the above pathways help you have the best possible conference learning experience, but don’t forget to also take some time to relax and have fun at our community-focused events. We can’t wait to see you soon.