Agenda

Predictive Analytics World Climate 2021

May 24-28, 2021 – Livestreamed


 

To view the full 7-track agenda for the six co-located conferences at Machine Learning Week click here or for the individual conference agendas here: PAW Business, PAW Financial, PAW Healthcare, PAW Industry 4.0, PAW Climate or Deep Learning World.

Session Levels:

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

All times are Pacific Daylight Time (PDT/UTC-7)

Workshops - Wednesday, May 19th, 2021

7:15 am
Workshop:

Full-day: 7:15am – 2:30pm PDT

This one-day session surveys standard and advanced methods for predictive modeling (aka machine learning).

The Workshop Description will be available shortly.
Instructor
John Elder Ph.D.Elder Research
Founder & Chair
Elder Research
7:30 am
Workshop:

Full-day: 7:30am – 3:30pm PDT

Gain experience driving R for predictive modeling across real examples and data sets. Survey the pertinent modeling packages.

The Workshop Description will be available shortly.
Instructor
Robert MuenchenUniversity of Tennessee
Manager of Research Computing Support
University of Tennessee
8:00 am
Workshop:

Full-day: 8:00am – 3:00pm PDT

This one day workshop reviews major big data success stories that have transformed businesses and created new markets.

The Workshop Description will be available shortly.
Instructors
Vladimir BarashGraphika Labs
Director
Graphika
Marc SmithConnected Action Consulting Group
Chief Social Scientist
Connected Action Consulting Group
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Workshops - Thursday, May 20th, 2021

8:00 am
Workshop:

Full-day: 8:00am – 3:00pm PDT

This workshop dives into the key ensemble approaches, inc   zluding Bagging, Random Forests, and Stochastic Gradient Boosting.

The Workshop Description will be available shortly.
Instructor
Dean AbbottSmarterHQ
Co-Founder and Chief Data Scientist
SmarterHQ
8:00 am
Workshop:

Full-day: 8:00am – 3:00pm PDT

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.

The Workshop Description will be available shortly.
Instructor
Clinton BrownleyWhatsApp
Data Scientist
WhatsApp
8:00 am
Workshop:

Full-day: 8:00am – 3:00pm PDT

Machine learning improves operations only when its predictive models are deployed, integrated and acted upon – that is, only when you operationalize it.

The Workshop Description will be available shortly.
Instructor
James TaylorDecision Management Solutions
CEO
Decision Management Solutions
8:30 am
Workshop:

Full-day: 8:30am – 3:30pm PDT

Gain the power to extract signals from big data on your own, without relying on data engineers and Hadoop specialists.

The Workshop Description will be available shortly.
Instructor
James Casaletto
PhD Candidate
UC Santa Cruz Genomics Institute and former Senior Solutions Architect, MapR
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Workshops - Friday, May 21st, 2021

7:15 am
Workshop:

Full-day: 7:15am – 2:30pm PDT

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.

The Workshop Description will be available shortly.
Instructor
John Elder Ph.D.Elder Research
Founder & Chair
Elder Research
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Predictive Analytics World for Climate - Virtual - Day 1 - Monday, May 24th, 2021

8:45 am
Eugene KirpichovWork On Climate
Co-founder
Work On Climate
David RolnickMcGill University
Assistant Professor, School of Computer Science
McGill University
Sasha LuccioniUniversité de Montréal
Postdoctoral Researcher
Université de Montréal
9:00 am
MACHINE LEARNING WEEK KEYNOTE
Lessons from: Lyft
The Keynote Description will be available shortly.
Session description
Speaker
Vladimir Iglovikov Ph.D.Lyft
Senior Computer Vision Engineer, Level5, Self-Driving Division
Lyft, Inc.
9:50 am
The Session Description will be available shortly.
Session description
Sponsored by
SAS
Speaker
Robert BlanchardSAS
SAS Senior Data Scientist.
SAS
10:10 am
Room change
10:20 am
Lessons from: Climate TRACE

Accurate, timely estimation of carbon emissions is critical for businesses and governments to take action on climate change. The Climate TRACE coalition aims to furnish these estimates for all major sources of emissions globally, on a near real-time basis. In this session we’ll give an overview of our work on estimating emissions from one of the most important sources of greenhouse gases, power generation from coal. The approach focuses upon detecting plumes using a variety of approaches, including multi instance deep learning.

Session description
Speaker
Joseph O’ConnorEnergy and Clean Air Analytics
Senior Data Scientist
Energy and Clean Air Analytics
11:05 am
Break & Expo Hall
11:30 am
Lessons from: Resync

The energy landscape is going through a drastic transformation. We are moving away from centralized power plants to more distributed energy resources such as solar, electric vehicles. This transformation makes it very difficult for the grid to handle and manage. Through this session we would explore how using data science and artificial intelligence, industries can optimize their energy usage while aiming to reduce costs and meet their sustainability goals. We'd be delving deeper into some of the forecasting and predictive analytics techniques we have created and measuring their impact. Also, we would share insights from real-life use cases of our customers and how AI has helped them monitor, control, and optimize their energy assets.

Session description
Speaker
Jayantika SoniResync
Cofounder & CTO
Resync
12:15 pm

Join your fellow practitioners in this interactive session where you can exchange approaches to shared challenges and hear how your peers are tackling similar issues.

12:45 pm
End of Day 1

Predictive Analytics World for Climate - Virtual - Day 2 - Tuesday, May 25th, 2021

8:00 am

Grab your real coffee and share experiences virtually with your peers to explore the new challenges of operating in a largely virtual world. Just like pre-show breakfast in a regular conference you’ll join a “round table” with seven fellow attendees and see where the conversation takes you.

8:55 am
9:00 am
The Keynote Description will be available shortly.
Session description
Speaker
John PlattGoogle
Director of Applied Science
Google
9:50 am
Presentation from Leading Vendor
10:10 am
Room change
10:20 am
Lessons from: Tracks GmbH

"Can I drive more efficiently?" was the question to be answered at the beginning of all data science efforts at Tracks. How can we accurately measure efficient driving of the thousands of truck drivers on the roads? This is a typical real-life question that is difficult to solve with ML methods. The answer to this question has sparked a number of follow up business questions that we are tackling with Tracks' complex AI system. In this session you will learn how Tracks' solution looks like, which ML methods are employed and which business questions are being answered. In a nutshell, how to turn ML into saved CO2. 

Session description
Speaker
Daniel RohrTracks GmbH
Senior Data Scientist
Tracks GmbH
11:05 am
Break & Expo Hall
11:30 am
Lessons from: SilviaTerra

As demand for carbon credits accelerates, there is an immense challenge in scaling the supply of carbon offsets. It’s hard to create credits that are additional, non-leaky, and durable, and it’s impossible for all but the largest landowners to participate in carbon programs. Over the last 10 years, SilviaTerra has built technology that generates comprehensive forest inventories of unprecedented resolution and scale, enabling measurement and payment for a comprehensive set of beneficial outcomes across the landscape. This new market is making carbon and other types of natural capital work for all landowners - for every acre, every value, every year.

Session description
Speaker
Nan PondSilviaTerra
Chief Biometric Officer
SilviaTerra
12:15 pm

Join your fellow practitioners in this interactive session where you can exchange approaches to shared challenges and hear how your peers are tackling similar issues.

12:45 pm
End of Day 2

Predictive Analytics World for Climate - Virtual - Day 3 - Wednesday, May 26th, 2021

8:00 am

Grab your real coffee and share experiences virtually with your peers to explore the new challenges of operating in a largely virtual world. Just like pre-show breakfast in a regular conference you’ll join a “round table” with seven fellow attendees and see where the conversation takes you.

8:55 am
9:00 am
The Session Description will be available shortly.
Session description
Speaker
John Elder Ph.D.Elder Research
Founder & Chair
Elder Research
9:50 am
Presentation from Leading Vendor
10:10 am
Room change
10:20 am
Case Study: One Concern

Climate change is increasing the frequency and severity of natural disasters. Natural catastrophes impact all critical infrastructures, and their resilience is essential for businesses and cities to operate effectively and safely. At One Concern, we combine machine learning and hazard modeling along with ML operational tools to better model the impacts of natural disasters on these critical infrastructures. By taking advantage of modeling, we can understand these potential impacts sooner to plan for and mitigate them. This helps to make our communities more resilient. This session will cover how One Concern applies Machine Learning algorithms to Natural Disaster Modeling. 

Session description
Speaker
Shabaz PatelOne Concern
Director of Data Science
One Concern
11:05 am

Take a break or join your fellow practitioners in this interactive session where you can exchange approaches to shared challenges and hear how your peers are tackling similar issues.

11:30 am
Lessons from: Terrafuse AI

We give an overview of recent developments in physics-informed AI and big data that are transforming the prediction of climate and weather in applications ranging from climate risk modeling for insurance to real-time forecasting for energy. Traditional climate and weather models require computationally expensive simulation of physical laws on supercomputers with hours to days of processing time and have limited capacity to incorporate ground-truth data sources. The development of cloud-based AI workflows based on deep neural networks provides an alternative approach to develop physical emulators of climate and weather processes that are highly scalable and natively tuned to utilize the petabytes of remote-sensing, ground-based and numerical simulation data from Earth observation that are generated daily. We present work that we are doing at Terrafuse AI, a startup out of Berkeley National Lab, to develop an AI-native climate risk and forecasting platform for problems ranging from high-resolution mapping of wildfire risk in California to real-time wind forecasting for aviation and renewable energy. 

Session description
Speaker
Brian WhiteTerrafuse AI
CTO and Chief Scientist
Terrafuse
12:15 pm
End of Day 3

Predictive Analytics World for Climate - Virtual - Day 4 - Thursday, May 27th, 2021

8:00 am

Grab your real coffee and share experiences virtually with your peers to explore the new challenges of operating in a largely virtual world. Just like pre-show breakfast in a regular conference you’ll join a “round table” with seven fellow attendees and see where the conversation takes you.

8:55 am
9:00 am
EXPERT PANEL

Discover how early-stage climate tech companies are using machine learning to help meet their challenges.

Session description
Panelists
Michel GelobterReflective Earth
Managing Director
REFLECTIVE EARTH
Diego Saez-GilPachama
Co-founder & CEO
Pachama
Elizabeth NyekoModularity Grid
CEO & Founder
Modularity Grid
Sierra Peterson
Climate Tech Investor
9:50 am

Join your fellow practitioners in this interactive session where you can exchange approaches to shared challenges and hear how your peers are tackling similar issues.

10:10 am
Room change
10:20 am
Lessons from: Kairos Aerospace

Methane, the primary component of natural gas, is responsible for 15% of global warming. Our mission of finding and stopping greenhouse gas emissions at huge scale is a critical step towards controlling climate change, but it also presents unique challenges. And, as a small startup, navigating the trade-offs between speed, accuracy, and cost in our data pipeline can often be the difference between survival and failure. In this talk, we will examine the difficulties ML pipeline design in cases where information, time, and money are constrained, and how to do so while hiding the sausage-making from our customers, who just want to know where their equipment is leaking, and want to know fast. By using a lean, iterative approach that involves input from every department, including engineering, operations, and business development, we stay focused on creating analytics that maximize value while reducing risk to the company. 

Session description
Speaker
Matthew GordonKairos Aerospace
Principal Software Engineer
Kairos Aerospace
11:05 am

Take a break or join your fellow practitioners in this interactive session where you can exchange approaches to shared challenges and hear how your peers are tackling similar issues.

11:30 am
Lessons from: AMP Robotics

The global recycling industry has been in economic crisis over the last few years as China and other international importers of recyclables enacted stricter requirements on the purity of recycled materials. COVID-19 exacerbated the recycling crisis, forcing many businesses to suspend operations due to concerns for worker safety. At the same time, the pandemic increased demand for high-quality recycled feedstock to overcome supply chain interruptions and shifts in raw material availability. AMP’s technology applies computer vision and deep learning to identify and differentiate recyclables found in the waste stream by color, size, shape, opacity, consumer brand, and more, storing data about each item it perceives. AMP’s AI can recognize and recover material as small as a bottlecap and as unique as a Keurig coffee pod from complex, mixed material streams of plastics, cardboard, paper, cans, cartons, and many other container and packaging types reclaimed for raw material processing for the global supply chain. Learn how AMP is helping the industry overcome the crisis by modernizing recycling—keeping recycling businesses open, ensuring worker safety, increasing productivity, improving bale purity, overcoming labor shortages, lowering the costs to recycle, diverting materials from landfill, and increasing overall rates of recycling. 

Session description
Speaker
Matanya HorowitzAMP Robotics
Founder
AMP Robotics
12:15 pm
End of Day 4

Predictive Analytics World for Climate - Virtual - Day 5 - Friday, May 28th, 2021

8:55 am
9:00 am
EXPERT PANEL

Coming soon!

Session description
9:50 am

Join your fellow practitioners in this interactive session where you can exchange approaches to shared challenges and hear how your peers are tackling similar issues.

10:10 am
Room change
10:20 am
Case Study: Sust Global

Financial institutions are playing an increasing role in the low-carbon transition by taking steps to accurately estimate, price, and disclose future climate risk. By quantifying their exposure to climate risks, financial institutions can more effectively allocate investments, avoid ‘stranded’ assets, and track adherence to Paris Agreement goals and shareholder commitments. However, it remains difficult for these institutions to assess climate related risks across a portfolio of assets and across different benchmark warming scenarios.I will cover large scale data transformation approaches as part of an end-to-end framework for quantifying annual, asset-level climate risk over multiple climate hazards including wildfires, inland flooding, and heat waves using simulations from global climate models participating in the Coupled Model Inter-comparison Project Phase 6 (CMIP6).We will be discussing techniques to quantify forward looking climate risk from 2020 to 2050 under multiple climate scenarios such as high-emissions (SSP5-8.5) and medium-emissions (SSP2-4.5) warming scenarios. I will also showcase intermediate steps to make the climate simulations and spatiotemporal data interpretable and actionable. We will cover ways to harmonize near real time observations from ground measurements and satellite derived data with forward looking climate risk projections for acute physical hazards for high accuracy predictive modeling.

Session description
Speaker
Gopal ErinjippurathSust Global
CTO, Head of Product
Sust Global
11:05 am

Take a break or join your fellow practitioners in this interactive session where you can exchange approaches to shared challenges and hear how your peers are tackling similar issues.

11:30 am
Lessons from: Afresh

About 30-40% of food produced worldwide is wasted. This represents a $165B loss to the US economy and poses major environmental problems: it is estimated that food waste contributes to up to 25% of all greenhouse gas emissions. This session explores how artificial intelligence can be used to automate decisions across the food supply chain in order to reduce waste and increase the quality and affordability of food. We focus our attention on supermarkets — combined with downstream consumer waste, these contribute to 40% of total US food losses — and we describe an intelligent decision support system for supermarket operators that optimizes purchasing decisions and minimizes losses. The core of our system is a model-based reinforcement learning engine for perishable inventory management. Our system is currently deployed across 220 supermarkets in the US (handling ~2% of US produce volume) and has led to waste reductions of up to 50%. We hope that this talk will bring the food waste problem to the attention of the machine learning community. 

Session description
Speaker
Volodymyr KuleshovAfresh
Co-Founder & Chief Technologist
Afresh Technologies
12:15 pm
End of Conference
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All times are Pacific Daylight Time (PDT/UTC-7)