Sobhan Moosavi
Engineering · The Ohio State University
Publications
26
Citations
234
Est. group size
~1
Recurring co-author estimate
Active years
14
Publishing since 2012
Sobhan Moosavi's research focuses on applying machine learning and deep learning methods to traffic safety problems, including predicting traffic accidents, estimating driving risk from telematics and sensor data, and identifying driving patterns and driver styles from vehicle trajectory data. This work combines techniques from data mining, time-series analysis, and neural network modeling to address real-world transportation and road-safety challenges.
Publication output has been variable over the last decade, with an early peak in 2017, a lull around 2019-2020, and a modest resurgence from 2021-2025, averaging under two publications per year in the most recent five-year period.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Accident Impact Prediction Based on a Deep Convolutional and Recurrent Neural Network Model
Urban Science · 2025
- Human and Algorithm in Tandem: Insights from Automation in Sequential Decision-Making Tasks
SSRN Electronic Journal · 2025
- Recent Advances in Traffic Accident Analysis and Prediction: A Comprehensive Review of Machine Learning Techniques
arXiv (Cornell University) · 2024
- Accident Impact Prediction based on a deep convolutional and recurrent neural network model
arXiv (Cornell University) · 2024
- Context-aware driver risk prediction with telematics data
Accident Analysis & Prevention · 2023
- CrashFormer: A Multimodal Architecture to Predict the Risk of Crash
2023
- Judge Me in Context: A Telematics-Based Driving Risk Prediction Framework in Presence of Weak Risk Labels
arXiv (Cornell University) · 2023
- Judge Me in Context: A Telematics-Based Driving Risk Prediction Framework in Presence of Weak Risk Labels
SSRN Electronic Journal · 2023
- Will there be a construction?
Proceedings of the 30th International Conference on Advances in Geographic Information Systems · 2022
- Driving Style Representation in Convolutional Recurrent Neural Network\n Model of Driver Identification
arXiv (Cornell University) · 2021
- LocationTrails
2021
- Driving Style Representation in Convolutional Recurrent Neural Network Model of Driver Identification
arXiv (Cornell University) · 2021
- A Countrywide Traffic Accident Dataset
arXiv (Cornell University) · 2019
- QDEE: Question Difficulty and Expertise Estimation in Community Question Answering Sites
Proceedings of the International AAAI Conference on Web and Social Media · 2018
- QDEE: Question Difficulty and Expertise Estimation in Community Question Answering Sites
arXiv (Cornell University) · 2018
- arXiv (Cornell University)×11
- SSRN Electronic Journal×2
- Accident Analysis & Prevention×1
- Urban Science×1
- Proceedings of the International AAAI Conference on Web and Social Media×1
- Justin Mukai
Engineering · Purdue University West Lafayette
- Rahul Suryakant Sakhare
Engineering · Purdue University West Lafayette
- Jairaj Desai
Engineering · Purdue University West Lafayette
- Jijo K. Mathew
Engineering · Purdue University West Lafayette
- Enrique D. Saldivar-Carranza
Engineering · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 19, 2026.
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