Filipe Rodrigues

About Filipe Rodrigues

Filipe Rodrigues, With an exceptional h-index of 21 and a recent h-index of 20 (since 2020), a distinguished researcher at Danmarks Tekniske Universitet, specializes in the field of Machine Learning, Crowdsourcing, Intelligent Transportation Systems, Urban Mobility.

His recent articles reflect a diverse array of research interests and contributions to the field:

Bayesian Active Learning for Censored Regression

Arrival Time Prediction for Autonomous Shuttle Services in the Real World: Evidence from Five Cities

Predicting injury-severity for cyclist crashes using natural language processing and neural network modelling

Mixture of Gaussian Processes for Bayesian Active Learning

Railway Network Delay Evolution: A Heterogeneous Graph Neural Network Approach

Learning to Control Autonomous Fleets from Observation via Offline Reinforcement Learning

Forecasting Parking Search Times Using Big Data

Graph Reinforcement Learning for Network Control via Bi-Level Optimization

Filipe Rodrigues Information

University

Position

(DTU)

Citations(all)

2466

Citations(since 2020)

2061

Cited By

1110

hIndex(all)

21

hIndex(since 2020)

20

i10Index(all)

36

i10Index(since 2020)

32

Email

University Profile Page

Google Scholar

Filipe Rodrigues Skills & Research Interests

Machine Learning

Crowdsourcing

Intelligent Transportation Systems

Urban Mobility

Top articles of Filipe Rodrigues

Bayesian Active Learning for Censored Regression

arXiv preprint arXiv:2402.11973

2024/2/19

Christoffer Riis
Christoffer Riis

H-Index: 1

Filipe Rodrigues
Filipe Rodrigues

H-Index: 14

Arrival Time Prediction for Autonomous Shuttle Services in the Real World: Evidence from Five Cities

arXiv preprint arXiv:2401.05322

2024/1/10

Filipe Rodrigues
Filipe Rodrigues

H-Index: 14

Predicting injury-severity for cyclist crashes using natural language processing and neural network modelling

Safety Science

2023/8/1

Mixture of Gaussian Processes for Bayesian Active Learning

Authorea Preprints

2023/10/31

Christoffer Riis
Christoffer Riis

H-Index: 1

Filipe Rodrigues
Filipe Rodrigues

H-Index: 14

Railway Network Delay Evolution: A Heterogeneous Graph Neural Network Approach

arXiv preprint arXiv:2303.15489

2023/3/27

Learning to Control Autonomous Fleets from Observation via Offline Reinforcement Learning

arXiv preprint arXiv:2302.14833

2023/2/28

Daniele Gammelli
Daniele Gammelli

H-Index: 2

Filipe Rodrigues
Filipe Rodrigues

H-Index: 14

Forecasting Parking Search Times Using Big Data

2023/2/20

Thomas Jansson
Thomas Jansson

H-Index: 47

Filipe Rodrigues
Filipe Rodrigues

H-Index: 14

Graph Reinforcement Learning for Network Control via Bi-Level Optimization

2023/7/23

Distribution and impacts of long-lasting marine heat waves on phytoplankton biomass

Frontiers in Marine Science

2023/7/3

Filipe Rodrigues
Filipe Rodrigues

H-Index: 14

Patrizio Mariani
Patrizio Mariani

H-Index: 17

Unboxing the graph: Towards interpretable graph neural networks for transport prediction through neural relational inference

Transportation research part C: emerging technologies

2023/1/1

Filipe Rodrigues
Filipe Rodrigues

H-Index: 14

Short-term bus travel time prediction for transfer synchronization with intelligent uncertainty handling

Expert Systems with Applications

2023/12/1

Filipe Rodrigues
Filipe Rodrigues

H-Index: 14

Incident congestion propagation prediction using incident reports

2023/11/13

Filipe Rodrigues
Filipe Rodrigues

H-Index: 14

Rose Yu
Rose Yu

H-Index: 17

Prediction of departure delays at original stations using deep learning approaches: A combination of route conflicts and rolling stock connections

Expert Systems with Applications

2023/11/1

Representation learning of rare temporal conditions for travel time prediction

2023/9/24

Filipe Rodrigues
Filipe Rodrigues

H-Index: 14

On the importance of stationarity, strong baselines and benchmarks in transport prediction problems

2023/9/24

Filipe Rodrigues
Filipe Rodrigues

H-Index: 14

Reconstruction of subsurface ocean state variables using Convolutional Neural Networks with combined satellite and in situ data

Frontiers in Marine Science

2023/9/20

Filipe Rodrigues
Filipe Rodrigues

H-Index: 14

Patrizio Mariani
Patrizio Mariani

H-Index: 17

The Dynamic RORO Stowage Planning Problem

2023/9/6

Filipe Rodrigues
Filipe Rodrigues

H-Index: 14

Dario Pacino
Dario Pacino

H-Index: 13

Deep Evidential Learning for Bayesian Quantile Regression

arXiv preprint arXiv:2308.10650

2023/8/21

Filipe Rodrigues
Filipe Rodrigues

H-Index: 14

Analyzing the Reporting Error of Public Transport Trips in the Danish National Travel Survey Using Smart Card Data

arXiv preprint arXiv:2308.01198

2023/8/2

Mind the gap: Modelling difference between censored and uncensored electric vehicle charging demand

Transportation Research Part C: Emerging Technologies

2023/8/1

Filipe Rodrigues
Filipe Rodrigues

H-Index: 14

See List of Professors in Filipe Rodrigues University(Danmarks Tekniske Universitet)

Co-Authors

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