Publications by Mohammadhossein Bahari

Certified Human Trajectory Prediction

Alexandre Massoud Alahi, Seyed Mohsen Moosavi Dezfooli, Saeed Saadatnejad, Mohammadhossein Bahari

Predicting human trajectories is essential for the safe operation of autonomous vehicles, yet current data-driven models often lack robustness in case of noisy inputs such as adversarial examples or imperfect observations. Although some trajectory predicti ...

2025

A journey toward generalizable trajectory forecasting models

Mohammadhossein Bahari

Autonomous driving is a revolutionary technology that has seen considerable advancements through the adoption of deep learning solutions. One of the major challenges in this field is the interaction with other road users. This interaction necessitates a "t ...

EPFL2024

Are socially-aware trajectory prediction models really socially-aware?

Alexandre Massoud Alahi, Seyed Mohsen Moosavi Dezfooli, Saeed Saadatnejad, Mohammadhossein Bahari, Pedram Khorsandi

Our transportation field has recently witnessed an arms race of neural network-based trajectory predictors. While these predictors are at the core of many applications such as autonomous navigation or pedestrian flow simulations, their adversarial robustne ...

2022

Are the trajectory prediction models generalizable?

Alexandre Massoud Alahi, Mohammadhossein Bahari

2022

Vehicle trajectory prediction works, but not everywhere

Alexandre Massoud Alahi, Seyed Mohsen Moosavi Dezfooli, Saeed Saadatnejad, Mohammadhossein Bahari, Ahmad Rahimi

Vehicle trajectory prediction is nowadays a fundamental pillar of self-driving cars. Both the industry and research communities have acknowledged the need for such a pillar by providing public benchmarks. While state-of-the-art methods are impressive, i.e. ...

IEEE2022

Injecting Knowledge in Data-driven Vehicle Trajectory Predictors

Alexandre Massoud Alahi, Ismail Nejjar, Mohammadhossein Bahari

Vehicle trajectory prediction tasks have been commonly tackled from two distinct perspectives: either with knowledge-driven methods or more recently with data-driven ones. On the one hand, we can explicitly implement domain-knowledge or physical priors suc ...

2021

Modified Joint Channel-and-Data Estimation for One-Bit Massive MIMO

Saeed Saadatnejad, Mohammadhossein Bahari, Mahdi Amiri

Centralized and cloud computing-based network architectures are the promising tracks of future communication systems where a large scale compute power can be virtualized for various algorithms. These architectures rely on high-performance communication lin ...

IEEE2021

Feed-forwards meet recurrent networks in vehicle trajectory prediction

Alexandre Massoud Alahi, Mohammadhossein Bahari

For an autonomous car, getting surprised is the worst thing that can happen. To prevent that, plenty of studies are trying to forecast traffic participants’ actions especially in an urban scene using recurrent networks. Recurrent networks are used for temp ...

2019