e Homepage for Mozhgan Nasr

Mozhgan Nasr, Ph.D.

Postdoc Fellow at University of Waterloo
I'm

About Me

About Me

Ph.D. in computer science, motion planning

Hello and welcome! I am Mozhgan, a recent Ph.D. graduate in Computer Science from University of Ottawa, where I had the privilege of working under the guidance of Prof. Azzedine Boukerche at the esteemed PARADISE Laboratory. My dissertation focused on driving behavior analysis and prediction for safe autonomous vehicles, and I am passionate about pushing the boundaries of autonomous driving. Prior to Uottawa, I worked with Dr. Nasser Ghadiri at Data and Knowledge Research Laboratory during my M.Sc. study at Isfahan University of Technology.

  • Affiliation: University of Waterloo
  • E-mail: mnasraza AT gmail DOT com
  • Address: Website

 

Research Interest

My research interests center around the intersection of machine learning, temporal convolutional networks, graph neural networks, computer vision, and reinforcement learning, with a specific focus on their application in scene understanding, motion planning, driver identification, and profiling for intelligent transportation systems and autonomous vehicles. In my work on Driving Behavior Analysis (DBA), I have developed several end-to-end deep learning and inverse reinforcement learning-based models for multimodal, context-aware, and interaction-aware motion forecasting. Moreover, I was dedicated to extracting efficient driver embeddings from driving time series using scalable representation learning techniques. I also leverage graph-based spatiotemporal convolutions to model interactive behavioral patterns among multiple agents within driving scenes.

News

News

  • 04/2024: I will be joining the WISE lab team at the University of Waterloo as a Postdoc!
  • 01/2024: One paper is accepted at IEEE ICC 2024!
  • 11/2023: I successfully defended my Ph.D. thesis and was nominated for the Best Thesis Award!
  • 09/2023: Our paper is accepted at IEEE transaction on Vehicular Technology!
  • 08/2023: One paper is accepted at IEEE Globecom 2023!
  • 02/2023: Invited talk for Principle of Intelligent Transportation Systems at University of ottawa!
Resume

Resume

To view my full CV please click Here (01/2024)

Publications

Publications

To be published/Under Review

Hierarchical Transformers for Motion Forecasting based on Inverse Reinforcement Learning
IEEE transaction on Vehicular Technology (submitted)
M.N. Azadani and A. Boukerche
IEEE (soon)

 

2024

A Novel Transformer-Based Model for Motion Forecasting in Connected Automated Vehicles
IEEE ICC 2024 (accepted)
M.N. Azadani and A. Boukerche
IEEE (soon)

 

2023

CAPHA: Context-Aware Path Prediction of Heterogeneous Agents
IEEE transaction on Vehicular Technology
M.N. Azadani and A. Boukerche
IEEE
GMP: Goal-based Multimodal Motion Prediction for Automated Vehicles
IEEE Globecom 2023 (accepted)
M.N. Azadani and A. Boukerche
IEEE
A Context-Aware Path Forecasting Method for Connected Autonomous Vehicles
2023 IEEE ICC
M.N. Azadani and A. Boukerche
IEEE
STAG: A novel interaction-aware path prediction method based on Spatio-Temporal Attention Graphs for connected automated vehicles
Adhoc Networks
M.N. Azadani and A. Boukerche
Elsevier

 

2022

A Novel Multimodal Vehicle Path Prediction Method Based on Temporal Convolutional Networks
IEEE Transactions on Intelligent Transportation Systems
M.N. Azadani and A. Boukerche
IEEE
An Interaction-Aware Vehicle Behavior Prediction for Connected Automated Vehicles
2022 IEEE ICC
M.N. Azadani and A. Boukerche
IEEE
Siamese Temporal Convolutional Networks for Driver Identification Using Driver Steering Behavior Analysis
IEEE Transactions on Intelligent Transportation Systems
M.N. Azadani and A. Boukerche
IEEE
An Internet-of-Vehicles Powered Defensive Driving Warning Approach for Traffic Safety
2021 IEEE Global Communications Conference (GLOBECOM)
M.N. Azadani and A. Boukerche
IEEE
DriverRep: Driver Identication through Driving Behavior Embeddings
JPDC journal
M.N. Azadani and A. Boukerche
ELSEVIER
Convolutional and Recurrent Neural Networks for Driver Identification: An Empirical Study
2022 IEEE ITAVT
M.N. Azadani and A. Boukerche
IEEE

 

2021

Driving Behavior Analysis Guidelines for Intelligent Transportation Systems
IEEE Transactions on Intelligent Transportation Systems
M.N. Azadani and A. Boukerche
IEEE
Toward Driver Intention Prediction for Intelligent Vehicles: A Deep Learning Approach
2021 IEEE 46th Conference on Local Computer Networks (LCN)
M.N. Azadani and A. Boukerche
IEEE
Driver Identification Using Vehicular Sensing Data: A Deep Learning Approach
2021 IEEE Wireless Communications and Networking Conference (WCNC)
M.N. Azadani and A. Boukerche
IEEE Code

 

2020

Performance Evaluation of Driving Behavior Identification Models through CAN-BUS Data
2020 IEEE Wireless Communications and Networking Conference (WCNC)
M.N. Azadani and A. Boukerche
IEEE

 

Prior to 2019

Graph-based biomedical text summarization: An itemset mining and sentence clustering approach
Journal of Biomedical Informatics
M.N. Azadani, N. Ghadiri, and E. Davoodijam
ELSEVIER Code
Evaluating Different Similarity Measures for Automatic Biomedical Text Summarization
International Conference on Intelligent Systems Design and Applications
M.N. Azadani and N. Ghadiri
SpringerLink Code
Performance evaluation of SpatialHadoop for big web mapping data
2016 Second International Conference on Web Research (ICWR)
E.F. Maleki*, M.N. Azadani*, and N. Ghadiri
IEEE

 

* co-first author

© Mozhgan Nasr (2024)