Pedro Chumpitaz is a Ph.D. student in Industrial Engineering at the University of South Florida (USF). His research integrates optimization models into machine learning frameworks, with interests in convex/non-convex optimization, statistical modeling, and engineering-informed machine learning.

Pedro holds a B.Sc. in Industrial Engineering from the Pontifical Catholic University of Peru (PUCP), ranking in the top 5% of his class. His thesis, supervised by Dr. Gusukuma, focused on television equipment trends in Peru using data mining and survival analysis. He participated in international programs like the OxML 2023 Machine Learning Program at the University of Oxford and Huawei’s Seeds for the Future. He also holds a diploma in digital transformation from CETAM-PUCP, specializing in IoT, cloud computing, data analytics, AI, and cybersecurity.

At PUCP, Pedro collaborated with Dr. Marco Gusukuma and Dr. Oscar Miranda, researching longevity and consumer trends of electronic equipment in Peru and using deep learning and NLP to predict copper prices. His professional experience includes roles at PepsiCo, Yape, and Belcorp, applying data science for decision-making and designing data analytics solutions. Fluent in English and Spanish, and skilled in Python, R, C++, SQL, and Java, Pedro is committed to industrial systems innovation and technological advancement.