Daniel Ovalle Varela Email and Phone Number

I am a 4th year PhD candidate at Carnegie Mellon University, specializing in mathematical programming, algorithms, decomposition methods, and the integration of optimization and machine learning. My work focuses on the development of software to solve optimization problems and integrate machine learning models that enhance optimization processes. With substantial experience in Python and a solid background in software development, I work in both theoretical research and practical implementations for real-world problem-solving.My doctoral research aims to efficiently solve large-scale optimization problems by leveraging machine learning techniques. I employ a variety of methods, including stochastic programming, mixed-integer linear and nonlinear programming, global optimization, and algorithm development. My work includes developing theory in heuristics for discrete optimization and convex relaxations. Similarly I have used my research in various applications spanning supply chain management, membrane design, oil and gas operations, disease control, water networks, and customer product design.My academic training, coupled with extensive interaction with industry, has provided me with significant experience in machine learning. I hold a PhD Minor in Machine Learning, having completed coursework from the masters program, which has enabled me to integrate optimization with machine learning effectively in my research.Internships in the financial industry have fueled my interest in quantitative research. I have modeled and deployed algorithms for large-scale portfolio optimization, applied machine learning methods for financial time series clustering and anomaly detection, and utilized AI integration through retrieval augmented generation (RAG) agents to enhance risk analysis.