Kaveh Khoshkhah

Data Scientist and Quantitative Researcher with interdisciplinary experience in modelling, simulation, and statistical analysis. Highly proficient in computational thinking and a broad range of programming tools, with a strong ability to develop and deploy end-to-end analytical workflows. Specialized in extracting insights from large-scale and complex datasets, including mobility, geospatial, and remote sensing data.

Strong foundation in mathematical modelling, optimization, and machine learning, with a focus on solving real-world problems through data-driven methods. Collaborative and research-oriented, with experience across academic, industry, and government settings.

• Programming and Frameworks: Python (NumPy, Pandas, SciPy, Scikit-learn, PyTorch), C++, Julia, SQL,

  MATLAB, ROS, Git, Docker, Unix/Linux

• Machine Learning and modelling: Supervised and unsupervised learning, statistical inference, deep learning, mathematical and agent-based modelling, traffic simulation, optimization (Gurobi, CVXPY, PuLP)
• Data Engineering and Processing: Data pipeline development, high-performance computing (HPC), distributed data handling (PySpark), working with structured and unstructured data
• Data Sources and Types: Spatiotemporal data, mobile CDR, GPS traces, IoT sensor streams, GTFS feeds, satellite imagery (Sentinel-½)
• Visualization and Communication: Data storytelling, custom Python dashboards, Power BI, Tableau

PhD in Mathematics

MSc in Computer Science