Alireza Mostafizi

Alireza Mostafizi

San Diego, California, United States
1K followers 500+ connections

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About

Data analytics leader working at the intersection of data science and engineering. With…

Activity

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Experience

  • Databricks Graphic

    Databricks

    San Diego, California, United States

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    Corvallis, Oregon Area

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    Remote (Project-bsaed)

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    Corvallis, Oregon

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    Greater Atlanta Area

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    Corvallis, OR

Education

  • Oregon State University Graphic

    Oregon State University

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    Activities and Societies: Institute of Transportation Engineers (ITE) Student Chapter - Social Event Coordinator & Secretary

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Licenses & Certifications

Publications

Courses

  • Artificial Intelligence

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  • Data Visualization

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  • Deep Learning

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  • Engineering Economics

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  • Machine Learning

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  • Model Thinking

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  • Operation Research

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  • Parallel Programming

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  • Principles of Economics

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  • Risk Assessment

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  • Systems Engineering

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  • Traffic Engineering

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  • Traffic Operation and Design

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  • Traffic Simulation

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  • Transportation Engineering

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  • Web Development

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Projects

  • Percolation Phenomenon in Connected Vehicle Network through a Multi-agent Approach: Mobility and Market Penetration

    Analysis of the impacts and benefits of message communication through connected vehicle environment on real-time quickest route optimization in a transportation network, considering different market penetrations. Percolation Theory has been implemented to characterize the effect of clustering in CV network.

    Other creators

  • Centralized Traffic Assignment Control of Autonomous Vehicles in a network: Reinforcement Machine Learning Approach

    The future of autonomous vehicles, routing behavior in particular, relies on centralized control to a certain extent. In this project I aimed to replicate the learning environment of the centralized control system to find the quickest path for the intelligent agents travelling in a the transportation network using Q-learning algorithm. This project includes two major parts. In the first part, I focused on replicating the behavior of the controller in terms of learning the quickest path for a…

    The future of autonomous vehicles, routing behavior in particular, relies on centralized control to a certain extent. In this project I aimed to replicate the learning environment of the centralized control system to find the quickest path for the intelligent agents travelling in a the transportation network using Q-learning algorithm. This project includes two major parts. In the first part, I focused on replicating the behavior of the controller in terms of learning the quickest path for a single intelligent vehicle in a simplified transportation grid network with the background traffic. Then I studied how different percentages of intelligent vehicles, learning simultaneously in a competitive environment, impacts the total mobility of the whole system, measured by the average of the network travel time.

  • Design of a main road in Bazargan

    Other creators
    • Dr.Samimi

  • Full design of a 7-floored steel structure

    Other creators
    • Dr.Khonsari

  • Transportation Network Disruptions and Vulnerability Assessment in a Tsunami Evacuation Scenario

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    Assessment of the performance of transportation network through an agent-based modeling approach in a near-filed tsunami evacuation scenario was the focus of this research. A novel methodology have been developed and applied to the city of Seaside, Oregon, and retrofitting plan was optimized for vulnerable and critical links to minimize the mortality rate of the evacuation considering limited resources.

    Other creators

  • Applications of Disaster Evacuation Modeling Platform on City of Newport, Oregon

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    Assessment of evacuation strategies for Newport, Oregon, including Hatfield Marine Science Center, and South Beach and South Park, with the aim of developing optimal policies and proposing new potential evacuation routes to minimize the mortality rate of tsunami evacuation.

    Other creators

  • An Agent-based Modeling of the Evacuees’ Decision-Making in a Multimodal Nearfield Tsunami Evacuation, and its Applications on City of Seaside, Oregon

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    Impacts of different multi-modal evacuation policies have been assessed, along with the benefits of vertical evacuation shelters on the mortality rate of the near-file tsunami evacuation scenario. In addition, socio-physical and behavioral attributes of community and its effect on evacuation efficiency have been analyzed.

    Other creators

  • Devising a new model for liability insurance considering social equity and drivers’ behavior

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    Other creators

Honors & Awards

  • Bill Kloos Scholar

    Oregon Institute of Transportation Engineering

  • Best Poster Presentation Awardee

    PacTrans Student Conference

  • Graduate Research of the Year

    Oregon State University, College of Engineering

  • Michael Kyte Student of the Year

    PacTrans Consortium

  • Richard and Lilo Smith Fellow

    Oregon State University, Civil and Construction Eng Department

  • Institute of Transportation Engineering (ITE) Student Chapter Officer Board

    Oregon Stet University

    Social Event Coordinator - 2015
    Secretary - 2016

  • Ranked 273th among more than 400,000 students in National University Entrance Exam

    National Organization for Educational Testing (Ministry of Science, Research and Technology)

  • Ranked 5th among more than 40,000 students in the Azad University Entrance Exam

    Azad University

  • Semi-finalist in Physics National Olympiad competition

    Iranian Young Scholars Club

  • 3rd Rank in Junior Soccer International IranOpen RoboCup Competition

    IranOpen International RoboCup Competition

Test Scores

  • Graduate Record Examinations (GRE)

    Score: V149 Q168 AW3.5

    Verbal: 149 / 170
    Quantitative: 168 / 170
    Analytical Writing: 3.5 / 6

  • Test Of English as a Foreign Language (TOEFL)

    Score: 104 / 120

    Reading: 27 / 30
    Listening: 29 / 30
    Speaking: 22 / 30
    Writing: 26 / 30

Organizations

  • Oregon State Univeristy

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    - Present

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