Nazib Siddique Email & Phone Number

Lemont, Illinois, United States

Lemont, Illinois, United States

Greater Seattle Area

• Using large scale location data from ride-sourcing vehicles of DIDI(similar to Uber and Lyft), developed clustering algorithms to detect ‘trip ends’ for origin-destination (OD) analysis using GPS based vehicle trajectory data in R• Using Convolutional Neural Networks (CNN), Partial Least Square (PLS), and Dynamic Mode Decomposition (DMD) methods for short term speed and travel time prediction and subsequent performance comparison of loop detector data and GPS data from INRIX• Using Python in conjunction with ESRI ArcPy package to batch process billions of rows of GPS based vehicle trajectory data which were later used for OD estimation and travel-time prediction• Using ESRI ArcGIS performed spatial analysis and developed visualizations for origin-destination (OD) estimation results by manipulating shapefiles and raster data• Using R and REST APIs, collected and analyzed incident, weather, and loop detector-based traffic volume data from Freeways (I-5 in the state of Washington) for short-term speed and travel time prediction• Using Microsoft SQL Server for managing, cleaning, and aggregating multiple large-scale datasets (millions to billions of rows) and Microsoft PowerApps for making an interactive dashboard to visualize the outcomes • Using R, performed Linear, and Logistic (Binomial, Multinomial and Nested) Regression analyses for different steps of travel demand modeling with household survey and census data• Using VISSIM to simulate signalized intersections, generate lane-wise traffic volumes in a controlled environment, and evaluate the performance of different ramp-metering algorithms• Using Synchro to design signal timings and estimate Level of Service (LOS) for isolated and coordinated signalized intersections• Prepared papers and reports to publish the findings of numerous projects with supporting visual aids including maps, tables, and graphs

Seattle, Us

• Instructed the Introduction to Transportation Engineering course to a class of 70-80 students where basics of transportation engineering and planning were explained to students to facilitate their understanding• Led student teams to conduct field studies where vehicle and pedestrian count data were collected for traffic signal design purposes

• Using machine learning techniques, developed methods to identify the Vehicle Flow State that can explain the underlying nature of the movement of an individual vehicle• Developed an Android app to collect GPS data using smartphones and managed the collected data in an online SQL server

• Instructed multiple courses on Transportation Planning and Highway Engineering. • Helped students about interpreting and analyzing traffic information and formulating solutions to problems

Doctor Of Philosophy (Phd), Transportation And Highway Engineering

• Developed machine learning methods to estimate Vehicle Flow State (VFS) from GPS based vehicle trajectory data using Hidden Markov Model.

Master'S Degree, Transportation And Highway Engineering

Transportation And Highway Engineering

Bachelor'S Degree, Civil Engineering