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Nael Alsaleh, Ph.D.
Postdoctoral Research Fellow,
Mobility Network, 

University of Toronto , Toronto, Ontario.

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About Nael

Nael Alsaleh was born in Jordan on July 30, 1993. He is currently a postdoctoral researcher at the Mobility Network, University of Toronto. Nael completed his B.Sc. in Civil Engineering in 2015 and M.Sc. in Transportation Engineering in 2017, from Jordan University of Science and Technology (JUST). His M.Sc. thesis won the first-place award in The Best Master’s Thesis Competition at JUST for the 2017-2018 academic year. He earned his Ph.D. in Transportation Engineering in 2022 from Toronto Metropolitan University. During his Ph.D. studies, he worked on different emerging on-demand transit projects with leading transportation service providers, and his dissertation focused on exploring network designs, developing demand models, and evaluating the sustainability of on-demand public transit systems. Nael has over five years of experience in transportation, working with universities and private consultants both in the Middle East and Canada. He has worked on various transportation projects, including public transit operation and design, traffic operations, traffic impact studies, and parking analysis. He also has extensive teaching experience, having taught several undergraduate engineering courses at Jordanian and Canadian universities. His research interests include travel demand modelling, connected and autonomous vehicles, on-demand shared mobility services, and transportation systems simulation. During his free time, he enjoys watching movies, playing sports, and participating in social activities.

Education

Ph.D., Transportation Engineering
Toronto Metropolitan University (TMU)
Sep. 2019 - Dec. 2022 

M.Sc., Transportation Engineering
Jordan University of Science & Technology (JUST)
Feb. 2016 - Oct. 2017 

B.Sc., Civil Engineering
Jordan University of Science & Technology (JUST)
Sep. 2011 - Aug. 2015 

Interests

  • Travel Demand Modelling
     

  • Shared On-Demand Mobility Services
     

  • Application of Machine Learning in Transportation
     

  • Transportation Systems Simulation
     

  • Connected and Autonomous Vehicles
     

  •  On-Demand Goods Delivery 

Skills

Interpretable Machine Learning Modelling
Advanced Discrete Choice Modelling
Transport Modelling
Programming

Honuors & Awards

  • International Ontario Graduate Scholarship (OGS) Award (Merit Based) for the 2022-2023 academic year.

  • International PhD Tuition Fees Conversion Scholarship (Competitive Based).

  • The First Place Award in The Best Master Thesis at JUST for the 2017-2018 academic year (Competitive Based).

  • Full-Funded Masters Scholarship Award (Competitive Based), Scientific Research Support Fund, Ministry of Higher Education, Jordan.

  • 2016-2017 Dean's Honour List, Faculty of Graduate Studies, JUST.

  •  2014-2015 Dean's Honour List, Faculty of Engineering, JUST.

  • 2011-2012 Dean's Honour List, Faculty of Engineering, JUST.  

Leadership Skills

  • President, TMU-ITE student chapter, September 2021 - August 2022.
     

  • Moderator, Innovative Sessions, ITS Canada 2021 Conference, June 21-22, 2021.
     

  • Student Supervision (Co-supervised undergraduate and graduate students).
     

  • Reviewer for International Scientific Journals.
     

  •  Speaker at University of Cambridge, Martin Centre for Architectural and Urban Studies, January 2021 and June 2022.

In the Media

Research Experience

Graduate Research Assistant, Laboratory of Innovations in Transportation (LiTrans), Toronto Metropolitan University, September 2019 - December 2022.

Working on several emerging on-demand public transit projects, including:

1. On-Demand Transit Service offered by Pantonium Inc., City of Belleville, Ontario.

  • Perform an in-depth spatio-temporal demand and supply analysis.

  • Develop data-driven models for trip production and distribution.

  • Explore factors affecting the demand levels.

  • Establish advanced discrete choice models to explain public transit user's service preference between the fixed-route transit and on-demand transit services.
     

2. On-Demand Transit Service offered by Uber Technologies Inc., Town of Innisfil, Ontario.

  • Analyzing and modelling the impact of the COVID-19 pandemic on the spatio-temporal patterns of demand.

  • Develop a micro-simulation model aimed at:

    • Analyzing the sustainability of several on-demand public transit designs from the perspective of efficiency, environmental footprint, and social equity and inclusion.

    • Identifying the demand switching point between several on-demand public transit designs, e.g., crowdsourced, dedicated fleet, and hybrid transit systems.

Publications

The COVID-19 pandemic has significantly influenced all modes of transportation. However, it is still unclear how the pandemic affected the demand for ridesourcing services and whether these effects varied between small towns and large cities .........

N. Alsaleh, B. Farooq (2022)

PLoS ONE

Behavioural Modelling of Automated to Manual Control Transition in Conditionally Automated Driving

Human-vehicle interaction in the presence of automated driving features (ADFs) poses significant challenges in behavioural adaptation. At the current level of automation, the mixed right-of-control of connected and automated vehicle (CAV) ......

S. M. Ansar, N. Alsaleh, B. Farooq (2022)

(Under Review)

Interpretable Data-Driven Demand Modelling for On-Demand Transit Services

In recent years, with the advancements in information and communication technology, different emerging on-demand shared mobility services have been introduced as innovative solutions in the low- density areas, including ...

N. Alsaleh, B. Farooq (2021)

Transportation Research Part A: Policy and Practice

Spatio-Temporal Analysis of On Demand Transit: A Case Study of Belleville, Canada

The rapid increase in the cyber-physical nature of transportation, availability of GPS data, mobile applications, and effective communication technologies have led to the emergence of On-Demand Transit (ODT) systems. In September 2018, the City of Belleville in Canada …

I. Sanaullah (equal contribution) , N. Alsaleh (equal contribution), S. Djavadian, B. Farooq (2021)

Transportation Research Part A: Policy and Practice

Artificial Neural Network (ANN) Approach to Predict LWST Values from Friction and Texture Measurements.

The paper aims to find whether friction values namely skid numbers obtained by the Locked Wheel Skid Trailer (LWST) device can be predicted using values obtained by the Dynamic Friction Tester (DFT) and the Circular Texture Meter (CTM) ..........

M. A. Khasawneh, M. Aljarrah, N. Alsaleh (2021)

International Journal of Engineering and Technology 

On-Demand Transit User Preference Analysis using Hybrid Choice Models

In light of the increasing interest to transform the fixed-route public transit (FRT) services into on-demand transit (ODT) services, there exists a strong need for a comprehensive evaluation of the effects of this shift on the users. Such an analysis can help the …

N. Alsaleh, B. Farooq, Y. Zhang, S. Farber (2021)

(Under Review)

Turbo Roundabout Usage in Lieu of Conventional Roundabouts for the Jordanian Traffic Conditions

The main objective of this study is to check the possibility of upgrading at-grade roundabouts to Turbo roundabouts considering the Jordanian driving conditions. It is also to check how such upgrade is going to affect performance measures of the studied ...

M. A. Khasawneh, N. Alsaleh (2018)

International Journal of Civil Engineering

Turbo, flower and conventional roundabouts in Jordan

In Jordan, we are looking for an innovative and cost efficient solutions for the poorly functioning at-grade roundabouts; considering the required bulk cost for grade separation or intersections signalization. Thus, the study aims to evaluate the compatibility ...

N. Alsaleh, L. Shbeeb (2018)

In Proceedings of 6th Annual international Conference on Architecture and Civil Engineering (ACE 2018)

Evaluation of School Zone Improvement Schemes

This research work focused on the impact of implementing safety measures in the vicinity of school area as part of “safer home-zone” program on driving speed and behavior of both drivers and pedestrians. Demographic characteristics ...

L. Shbeeb, N. Alsaleh (2018)

In Proceedings of 6th Annual international Conference on Architecture and Civil Engineering (ACE 2018)

Teaching & Practical Experience

Teaching

  1. Graduate Assistant at Toronto Metropolitan University, Ontario

Winter 2020 / Winter 2021

I have been working as a graduate teaching assistant for Transportation Engineering Course for two semesters.

2.  Full-Time Lecturer at Al-Ahliyya Amman University, Jordan

Oct. 2017 until Sep. 2019 

I have worked as an instructor for the following Civil Engineering courses:

  • Transportation Engineering.

  • Engineering Statistics.

  • Geotechnical Engineering.

  • Geotechnical Engineering Laboratory.

  • Computer Applications in Civil Engineering.

  • Civil Engineering Drawing.

  • Numerical Analysis.

Practical

  1. Traffic Simulator Consultant, Dar Al Omran Company, Jordan

April 2018 until Jan. 2019

I have worked as a Part-time traffic simulator consultant at Irbid City Center Upgrading Project with Dar Al Omran Company

2.  Trainee at Consolidated Contractors Company (CCC), Qatar

June 2015 until August. 2015

Project: Doha New Port and Container Terminal Project.

Full professional engineering training as a pre-requirement to achieve the B.Sc. degree in Civil Engineering.

3.  Part-Time Lecturer at Al Hussein Technical University, Jordan

Feb. 2019 until July. 2019 

I have worked as an instructor for the Geotechnical Engineering Course at the School of Construction Technology and Built Environment that follows Pearson BTEC (Business and Technology Education Council) qualifications and standards.

Recent Presentations

On-Demand Transit User Preference Analysis using Hybrid Choice Models

March 9, 2021

Travel Demand Analysis Course, Toronto Metropolitan University

On-Demand Transit User Preference Analysis using Hybrid Choice Models

February 19, 2021

Laboratory of Innovations in Transportation (LiTrans), Toronto Metropolitan University

Spatio-Temporal Demand Modelling for On-Demand Transit Services

January 28, 2021

Applied Urban Modelling Workshop (AUM2020), Martin Centre for Architectural and Urban Studies, University of Cambridge.

Machine Learning Based Demand Modelling for On-Demand Transit Services

January 26, 2021

Seminar Presentation, Toronto Metropolitan University

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