Shockwave identification and critical parameter estimation using a detailed dataset from a swarm of drones

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Models trained with counterfactually augmented data learn representations of the causal structure of tasks, enabling robust generalization. However, high-quality counterfactual data is scarce for most tasks and not easily generated at scale. When crowdsour ...

State-of-the-art object detection and segmentation methods for microscopy images rely on supervised machine learning, which requires laborious manual annotation of training data. Here we present a self-supervised method based on time arrow prediction pre-t ...

This research is the result of four years of practical and scientific investigation of the phenomenon of traffic evaporation, which was considered and then demonstrated to be the opposite of traffic induction. It has anchored, in practice and in time, an o ...

Traffic congestion constitutes one of the most frequent, yet challenging, problems to address in the urban space. Caused by the concentration of population, whose mobility needs surpass the serving capacity of urban networks, congestion cannot be resolved ...

This dissertation introduces traffic forecasting methods for different network configurations and data availability. Chapter 2 focuses on single freeway cases. Although its topology is simple, the non-linearity of traffic features makes this prediction sti ...

Signalized intersections are a fundamental part of urban networks. Their understanding is crucial to identify congestion patterns, queues, delays, and safety issues in local and network level. In this work, we analyze multimodal vehicle trajectories and pr ...

Moving walkways are pedestrian dedicated hardware which generally decrease pedestrian travel time. We propose the utilization of these devices to dynamically control pedestrian flows in order to improve pedestrian dynamics. Three variations of a control st ...

We propose a stochastic conditional gradient method (CGM) for minimizing convex finitesum objectives formed as a sum of smooth and non-smooth terms. Existing CGM variants for this template either suffer from slow convergence rates, or require carefully inc ...

Shockwave identification and critical parameter estimation using a detailed dataset from a swarm of drones

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DISCO: Distilling Counterfactuals with Large Language Models

Self-supervised Dense Representation Learning for Live-Cell Microscopy with Time Arrow Prediction

L'évaporation du trafic, opportunités et défis pour la mobilité d'aujourd'hui et demain

Large-scale traffic signal control and multimodal network design

Multivariate time series forecasting for freeway networks

An automatized signal timing detection at signalized intersections with detailed vehicle trajectory data

Controlling pedestrian flows with moving walkways

Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization