I am currently pursuing a PhD at the Department of Infrastructure Engineering at the University of Melbourne in Australia. My current study aims to develop statistical machine learning-based solutions for Intelligent Transportation Systems (ITS) and the deployment of cost-effective solutions in low-and mid-income cities. Research interests ~ Network flow and optimization Spatial data science Machine learning and GeoAI Computational geometry Remote sensing and GIS Intelligent Transportation Systems (ITS) Wireless Sensor Networks and Internet of Things (IoT) Unmanned Aerial Vehicles (UAV) Skills ~ Programming languages: Python, MATLAB, C++, Java. Data analysis and visualization: Pandas, PostgreSQL, Geopandas, Matplotlib, Seaborn. Machine learning, optimization: Scikit-learn, Scipy, Statsmodels, Numpy, Sympy, TensorFlow, Gurobipy, Opencv. Network and computational geometry: Networkx, OSMnx, Shapely, Fiona, QGIS, Arcpy. Web scrapper, automation and GUI: Selenium, Urllib, Beautifulsoup, Tkinter. Hardware and protocols: ARM Embedded Systems, Vector signal transceiver, Software Defined Radio, ZigBee IEEE 802.15.4, VHDL, Verilog, SPI, UART, I2C protocol, CMOS camera, Arduino, Ardupilot.