Sergio Casas

Sergio Casas

Sr Staff TLM @ Waabi

Ph.D. @ UofT

About me

I am a Sr Staff Tech Lead Manager at Waabi, where I lead our Perception and Behavior Reasoning team. I completed my PhD at the University of Toronto supervised by Professor Raquel Urtasun. My research lies at the intersection of computer vision, machine learning, and robotics.

Interests

  • Artificial Intelligence
  • Machine Learning
  • Computer Vision
  • Robotics - Autonomous Driving
  • Generative Models
  • Imitation Learning

Education

  • PhD in Computer Science, 2020 - 2024

    University of Toronto

  • MSc in Computer Science, 2018 - 2020

    University of Toronto

  • BSc in Computer Science, 2013 - 2017

    Universitat Politècnica de Catalunya

  • BSc in Industrial Tech. Engineering, 2012 - 2017

    Universitat Politècnica de Catalunya

Selected Publications

For a complete and up-to-date list of publications visit my Google Scholar

(* denotes equal contribution)

DeTra: A Unified Model for Object Detection and Trajectory Forecasting

ECCV 2024
Unified object detection and trajectory prediction as trajectory refinement.
DeTra: A Unified Model for Object Detection and Trajectory Forecasting

UnO: Unsupervised Occupancy Fields for Perception and Forecasting

CVPR 2024 (Oral)
Occupancy Foundation Model (Unsupervised)
UnO: Unsupervised Occupancy Fields for Perception and Forecasting

QuAD: Query-based Interpretable Neural Motion Planning for Autonomous Driving

ICRA 2024
End-to-end autonomy leveraging implicit occupancy.
QuAD: Query-based Interpretable Neural Motion Planning for Autonomous Driving

Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion

ICLR 2024
LiDAR World Model.
Copilot4D: Learning Unsupervised World Models for Autonomous Driving via Discrete Diffusion

ImplicitO: Implicit Occupancy Flow Fields for Perception and Prediction in Self-Driving

CVPR 2023 (Highlight)
Efficient implicit occupancy perception and forecasting model.
ImplicitO: Implicit Occupancy Flow Fields for Perception and Prediction in Self-Driving

MP3: A Unified Model to Map, Perceive, Predict and Plan

CVPR 2021 (Best Paper Candidate, Oral)
Interpretable end-to-end neural motion planning without high-definition maps
MP3: A Unified Model to Map, Perceive, Predict and Plan

LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving

ICCV 2021
Contingency planning from diverse joint trajectory samples for all actors in the scene
LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving

TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors

CVPR 2021
Realistic long-term vehicle behavior simulation learned from imitation and common sense
TrafficSim: Learning to Simulate Realistic Multi-Agent Behaviors

Implicit Latent Variable Model for Scene-Consistent Motion Forecasting

ECCV 2020
ILVM characterizes the joint distribution over multiple actors’ future trajectories
Implicit Latent Variable Model for Scene-Consistent Motion Forecasting

End-to-end Interpretable Neural Motion Planner

CVPR 2019 (Oral)
Neural motion planner from LiDAR and HD maps
End-to-end Interpretable Neural Motion Planner

Intentnet: Learning to Predict Intention from Raw Sensor Data

CoRL 2018 (Spotlight)
Joint perception and prediction from LiDAR point clouds and HD maps
Intentnet:  Learning to Predict Intention from Raw Sensor Data

Experience

 
 
 
 
 

Staff Researcher

Waabi

Mar 2021 – Present Toronto, Canada
We are building the next generation of self-driving technology. Stay tuned!
 
 
 
 
 

Research Scientist

Uber Advanced Technologies Group (acquired by Aurora)

Oct 2017 – Feb 2021 Toronto, Canada
Research in Autonomous Driving: Perception, Prediction and Motion Planning systems.
 
 
 
 
 

Research Assistant

University of Toronto

Feb 2017 – Jul 2017 Toronto, Canada
Research in spatio-temporal reasoning for sports analytics. Worked on automatizing the NBA Play-by-Play reports. Supervised by Prof. Urtasun.
 
 
 
 
 

Data Analytics Consultant

Arcvi Big Data Agency

Jun 2016 – Jan 2017 Barcelona, Spain
Creation of strategy solutions using simple Machine Learning techniques. Advised multiple retail, insurance and credit companies.
 
 
 
 
 

Software Engineering Intern

Psycle Interactive Ltd.

Jun 2015 – Aug 2015 Whitchurch, United Kingdom
Mobile application development and UI/UX design. Research project on document topic classification and information retrieval.