Uber x NeurIPS 2020
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2:00pm

Understand

Lightning Talks on Business Goals

Learn to understand and tackle problems from many different points of view. Discussions should highlight business goals, success metrics, technical capabilities and potential challenges, and relevant user research.

12:00 PM

Schedule Element

Mike Zoppo is a host of exceptional ability. Studies show that a vast majority of guests attending events by Mike have been known to leave more elated than visitors to Santa's Workshop, The Lost of Continent of Atlantis, and the Fountain of Youth.

Speaker Name

Job Title

Company Name

Chelsea Kelly is a host of exceptional ability. Studies show that a vast majority of guests attending events by Chelsea have been known to leave more elated than visitors to Santa's Workshop, The Lost of Continent of Atlantis, and the Fountain of Youth.

2:00pm

Understand

Lightning Talks on Business Goals

Learn to understand and tackle problems from many different points of view. Discussions should highlight business goals, success metrics, technical capabilities and potential challenges, and relevant user research.

KATIE BOFSHEVER

Design Partner, GV

As VP of Digital Media at GV, Katie Bofshever crafts innovative and creative solutions for the digital space, specializing in minority consumers.

Mrs Robinson

2:00pm

Understand

Lightning Talks on Business Goals

Learn to understand and tackle problems from many different points of view. Discussions should highlight business goals, success metrics, technical capabilities and potential challenges, and relevant user research.

2:00pm

Understand

Lightning Talks on Business Goals

Learn to understand and tackle problems from many different points of view. Discussions should highlight business goals, success metrics, technical capabilities and potential challenges, and relevant user research.

Mrs Robinson

December 6 - 12

Uber x NeurIPS 2020

Uber is a proud silver sponsor of the 2020 virtual conference on Neural Information Processing Systems. We are redefining how the world moves using AI and machine learning.

Date TBD
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     Featured Leaders and Speakers

Zoubin Ghahramani

Chief scientist and vp of ai

Uber ai

Zoubin Ghahramani is Chief Scientist and VP of Artificial Intelligence at Uber, where he serves on the Engineering Leadership Team and leads the engineering and advanced research teams developing data-driven algorithms to optimize the services Uber provides users worldwide. 

Raquel Urtasun

Chief scientist & Head of atg toronto

uber atg

 Raquel Urtasun is Uber ATG’s Chief Scientist and the Head of Uber ATG Toronto. She is the author of 1 paper at NeurIPS 2019 and is a featured speaker at 2 workshops.

Ashley Edwards

RESEARCH SCIENTIST

UBer aI

Ashley Edwards is a Research Scientist at Uber AI. She is a published first author and is a featured speaker at this year's Women in Machine Learning workshop.

Orals at Main Conference

Tuesday, 12/10

Define

Parameter Elimination in Particle Gibbs Sampling

4:50 PM -- West Ballroom C

Anna Wingren, Riccardo Sven Risuleo,  Lawrence Murray, Fredrik Lindsten 

Spotlights at Main Conference

Tuesday, 12/10

Define

Scalable Global Optimization via Local Bayesian Optimization

4:25 PM-- West Ballroom C

David Eriksson, Michael Pearce, Jacob Gardner, Ryan Turner, Matthias Poloczek

Tuesday, 12/10

Understand

Variational Bayesian Optimal Experimental Design

4:40 PM-- West Ballroom C

Adam Foster, Martin Jankowiak, Elias Bingham, Paul Horsfall, Yee Whye Teh, Thomas Rainforth, Noah Goodman

Main Conference


Understand

MuSCLE: Multi Sweep Compression of LiDAR using Deep Entropy Models

Sourav Biswas, Jerry Liu, Kelvin Wong, Shenlong Wang, Raquel Urtasun


Understand

LoCo: Local Contrastive Representation Learning

Yuwen Xiong, Mengye Ren, Raquel Urtasun


Understand

Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights

Theofanis Karaletsos*, Thang Bui*

Papers at Workshops

Friday, 12/13

Understand

Meta-Graph: Few shot Link Prediction via Meta-Learning

Graph Representation Learning -- VCC, West Exhibition Hall A

Avishek Joey Bose, Ankit Jain, Piero Molino, William L. Hamilton

Friday, 12/13

Understand

Learned First-Order Preconditioning

Beyond First Order Methods in Machine Learning Systems -- VCC, West Level  2, Rooms 211 - 214 

Ted Moskowitz, Rui Wang, Janice Lan, Sanyam Kapoor, Thomas Miconi, Jason Yosinski, Aditya Rawal 

Friday, 12/13

Understand

Commonsense and Semantic-Guided Navigation through Language in Embodied Environment

Visually Grounded Interaction and Language (VIGIL) Workshop -- VCC, West Level 2, Rooms 202 - 204

Dian Yu, Chandra Khatri, Alexandros Papangelis, Andrea Madotto, Mahdi Namazifar, Joost Huizinga, Adrien Ecoffet, Huaixiu Zheng, Piero Molino, Jeff Clune, Zhou Yu, Kenji Sagae, Gokhan Tur

Saturday, 12/14

Understand

 Information-Theoretic Limitations on Novel Task Generalization

Workshop on Machine Learning with Guarantees -- VCC, West Ballroom B

James Lucas, Mengye Ren, Richard S. Zemel

Saturday, 12/14

Understand

Deformable Filter Convolution for Point Cloud Reasoning

Workshop on Sets & Partitions -- VCC, West Level 2, Rooms 215-216

Yuwen Xiong, Mengye Ren, Renjie Liao, Kelvin Wong , Raquel Urtasun 

Saturday, 12/14

Understand

Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro

Workshop on Program Transformations for Machine Learning -- VCC, West Level 1, Rooms 114-115

Du Phan, Neeraj Pradhan, Martin Jankowiak

Saturday, 12/14

Understand

Functional Tensors for Probabilistic Programming

Workshop on Program Transformations for Machine Learning -- VCC, West Level 1, Rooms 114-115

Fritz Obermeyer, Eli Bingham, Martin Jankowiak, Du Phan, Jonathan Chen

Workshops

Uber is proud to do our part to elevate the machine learning community by sponsoring, presenting research, and/or speaking at several workshops.

monday, december 7th

SPONSORED workshop:

Black in AI

About: 

Black in AI is a place for sharing ideas, fostering collaborations and discussing initiatives to increase the presence of Black people in the field of Artificial Intelligence. The workshop will feature invited talks from prominent researchers and practitioners, oral presentations, and a poster session. Uber is a sponsor.

WEDNESDAY, december 9th

sponsored workshop:

women in machine learning

About: 

This technical workshop gives female faculty, research scientists, and graduate students in the machine learning community an opportunity to meet, network and exchange ideas, participate in career-focused panel discussions with senior women in industry and academia and learn from each other. Uber is a Silver Sponsor.

Friday, December 11th

Deep learning through information geometry workshop

About: 

Statistical learning theory focuses on the complexity of the hypothesis class to bound the generalization gap, but it is clear that this approach won’t work for deep networks. How can we adapt existing theory to exploit the geometry of the hypothesis class? The learning algorithm can be viewed as an information processing procedure. What information-theoretic properties of this channel lead to good generalization?
How should we build an understanding of data in machine learning? Specifically, how does the dataset (task) in deep learning affect optimization and generalization? How can we adapt learning theory to understand the low-data regime?


Accepted Paper:

Annealed importance sampling with q-paths

Rob Brekelmans, Vaden Masrani, Thang D Bui, Frank Wood, Aram Galstyan, Greg Ver Steeg, Frank Nielsen

friday, december 11th

workshop on meta-learning

About:

This workshop aims to bring together researchers from all the different communities and topics that fall under the umbrella of meta-learning. We expect that the presence of these different communities will result in a fruitful exchange of ideas and stimulate an open discussion about the current challenges in meta-learning as well as possible solutions. 


Accepted Paper:

Flexible Few-Shot Learning of Contextual Similarity

Mengye Ren, Eleni Triantafillou, Kuan-Chieh Wang, James Lucas, Jake Snell, Xaq Pitkow, Andreas Tolias, Richard Zemel

friday, december 11th

workshop on machine learning for autonomous driving

About: 

Autonomous vehicles (AVs) offer a rich source of high-impact research problems for the machine learning (ML) community; including perception, state estimation, probabilistic modeling, time series forecasting, gesture recognition, robustness guarantees, real-time constraints, user-machine communication, multi-agent planning, and intelligent infrastructure. Further, the interaction between ML subfields towards a common goal of autonomous driving can catalyze interesting inter-field discussions that spark new avenues of research, which this workshop aims to promote. As an application of ML, autonomous driving has the potential to greatly improve society by reducing road accidents, giving independence to those unable to drive, and even inspiring younger generations with tangible examples of ML-based technology clearly visible on local streets.


Program Committee: Henggang Cui, Nemanja Djuric


Accepted Papers:

Investigating the Effect of Sensor Modalities in Multi-Sensor Detection-Prediction Models

Abhishek Mohta, Fang-Chieh Chou, Brian Becker, Carlos Vallespi-Gonzalez, Nemanja Djuric


Temporally-Continuous Probabilistic Prediction using Polynomial Trajectory Parameterization

Zhaoen Su, Chao Wang, Henggang Cui, Nemanja Djuric, Carlos Vallespi-Gonzalez, David Bradley

 
Uncertainty-aware Vehicle Orientation Estimation for Joint Detection-Prediction Models

Henggang Cui, Fang-Chieh Chou, Jake Charland, Carlos Vallespi-Gonzalez, Nemanja Djuric

Opportunities

Curious how you can set the world in motion with Uber? We're solving challenging problems and looking for great talent interested in scaling Uber's technologies and making a global impact!

Full Time

Android Engineer - Uber AI - Building Blocks

Backend Engineer - AI Engagements

Backend Engineer - AI Platform

Backend Engineer - Uber AI (Michelangelo Platform)

Engineering Manager II

Machine Learning Engineer - Uber AI (Engagements)

Machine Learning Engineer - Uber AI Recommendations

(Senior) Data Scientist - Applied Machine Learning or Operations Research

(Senior) Data Scientist - Pricing, Statistics and/or Econometrics

Senior iOS Engineer (Uber AI)

Senior Machine Learning Engineer - Maps

Senior Machine Learning Engineer - Uber AI Recommendations

Senior Motion Planning Engineer

Software Engineer - Deep Learning Platform

Staff Software Engineer, Uber AI

University

2021 PhD University Graduate - Data Scientist

Don't see what you are looking for above?

View All Open Roles
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AI Residency

Uber AI Residency applications are now open! Looking to jumpstart or advance your career in AI research? The Uber AI Residency is a 12-month training program for recent college and master’s graduates, professionals who are looking to reinforce their AI skills, and those with quantitative skills and interest in becoming an AI researcher at Uber. Read more on our eng blog!

Apply Now!
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Internships

We are looking for interns with computer vision/machine learning expertise to work on impactful problems. You will be partnering closely with world-class scientists and engineers to solve some of the toughest challenges related to transportation.

 
A variety of internship opportunities are available for multiple teams and locations, including but not limited to: ATG Research and Engineering internships in Perception, Prediction, Motion Planning, Controls, Simulation, Mapping, Localization, Core ML, and more. Stop by our booth to learn more about our internship opportunities for 2019-2020!

Research Intern, Uber ATG
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Featured Teams

advanced technologies group

At Uber we believe the future of mobility is increasingly shared, sustainable, and automated. Developing self-driving technology is one of the biggest technical challenges of our time. If successful, these vehicles have the potential to make our roads safer and transportation more affordable for everyone. 


From deep learning and neural networks, to robotics, maps, simulation, security and data science, if there's a type of software you're interested in, we probably do it. Uber is uniquely well-positioned to bring self-driving to the world through its ride-sharing network.

DATA Science


The Uber Data Science team works together to build world-class fundamental and innovative data science solutions. Our team works on solutions related to Rides, Eats, Safety & Insurance, Risk, Policy, Platform and Marketing.


We have a strong community of world-class domain experts who foster an environment of continuous learning and teaching. Our team helps implement solutions that are used by millions of people every day. 

uber ai


AI Engagements

Our world-class team at Uber AI Engagements connects cutting-edge models in machine learning to the broader business. Applications range from model-based simulation and time series forecasting to Bayesian optimization and automatic feature selection. Click to see our publications.


AI Platform
We leverage sensors as a source of truth and develop algorithms to solve our users' top pain points, ranging from crash detection to improved GPS, menu OCR to automatic driver license approval, and many more use cases, requiring expertise in signal processing, computer vision and NLP. Click to see our publications.

Uber is proud to be an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

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