Pedro Chumpitaz-Flores
Pedro Chumpitaz-Flores
PhD Student
Deterministic Algorithms and Trustworthy Analytics (DATA)
IMSE Department
University of South Florida
pedrochumpitazflores [at] usf [dot] edu | Google Scholar | Linkedin
I am a Ph.D. student in Industrial Engineering at the University of South Florida (USF), advised by Dr. Kaixun Hua. My work develops scalable deterministic global-optimization algorithms for large-scale machine learning, with emphasis on policy optimization for MDPs and constrained clustering at massive scale.
My research focuses on: (1) mathematical optimization for large-scale ML with provable guarantees; (2) scalable solvers for combinatorial problems leveraging parallel and distributed computing (HPC/GPU acceleration); and (3) optimization methods at the intersection of ML and emerging paradigms, including quantum-inspired optimization.
My work was recognized by INFORMS, Runner Up in the Data Mining Best Paper Competition (Theoretical Track) and Honorable Mention in the Minority Issues Forum Student Poster Competition, both in 2025. I also received a Student Travel Award from the IEEE International Conference on Big Data in 2025.
RECENT NEWS
🏆 [New!] Student Travel Award, IEEE International Conference on Big Data.
🏆 [New!] INFORMS 2025 recognition: Runner Up, Data Mining Best Paper Competition (Theoretical track), for "A Scalable Global Optimization Algorithm for Constrained Clustering" paper.
🏆 [New!] INFORMS 2025 recognition: Honorable Mention, Minority Issues Forum Student Poster Competition for "A Scalable Global Optimization Algorithm for Constrained Clustering" paper.
📄 [Nov, 2025] “qc-kmeans: A Quantum Compressive K-Means Algorithm for NISQ Devices” (with M. Duong, Y. Mao, K. Hua) accepted in IEEE BigData 2025. paper
📄 [Nov, 2025] “QIBONN: A Quantum Inspired Bilevel Optimizer for Neural Networks on Tabular Classification” (with M. Duong, Y. Mao, K. Hua) accepted in IEEE BigData 2025. paper
📄 [Oct, 2025] Attended INFORMS Annual Meetings 2025 to present "A Scalable Global Optimization Algorithm for Constrained Clustering".
📄 [Oct, 2025] “A Scalable Global Optimization Algorithm for Constrained Clustering” is on arXiv. paper
📄 [Sep, 2025] “SPOT: Scalable Policy Optimization with Trees for Markov Decision Processes” (with X. Xiong, K. Hua, C. Hua) accepted in NeurIPS 2025. paper
📄 [June, 2025] “Survival Analysis for the Evolution of Lifespan of Electrical and Electronic Equipment” (with M. Gusukuma) published in TEMSCON LATAM 2025. doi