Analysis and modeling of complex data using mathematical, statistical, and numerical methods.

• Exploratory data analysis
• Statistical modeling
• Time series forecasting
• Uncertainty and noise analysis
• Mathematical interpretation of results

Design and implementation of algorithmic solutions for data analysis and machine learning applications.

• Implementation of machine learning algorithms
• Model training and validation workflows
• Translating mathematical models into code
• Python-based prototyping and experimentation
• Performance analysis and model limitations

A rigorous approach to algorithm design, grounded in theory and formal analysis.

• Efficient algorithm design
• Data structures
• Complexity analysis
• Formal languages and logic
• Abstract problem solving

Study and experimental implementation of the mathematical foundations of modern cryptography.

• Algebraic and probabilistic foundations
• Analysis of cryptographic schemes
• Experimental implementation of encryption mechanisms
• Understanding security assumptions

• Python (scientific computing, data analysis, ML)
• C++ (performance-oriented programming)
• Structured and well-documented code
• Strong understanding of computer systems fundamentals

• Machine learning internships
• Cryptography internships
• Advanced data analysis projects
• Algorithmic or mathematically intensive roles